the impact of social media research paper

ORIGINAL RESEARCH article

Effects of social media use on psychological well-being: a mediated model.

• 1 School of Finance and Economics, Jiangsu University, Zhenjiang, China
• 2 Research Unit of Governance, Competitiveness, and Public Policies (GOVCOPP), Center for Economics and Finance (cef.up), School of Economics and Management, University of Porto, Porto, Portugal
• 3 Department of Business Administration, Sukkur Institute of Business Administration (IBA) University, Sukkur, Pakistan
• 4 CETYS Universidad, Tijuana, Mexico
• 5 Department of Business Administration, Al-Quds University, Jerusalem, Israel
• 6 Business School, Shandong University, Weihai, China

The growth in social media use has given rise to concerns about the impacts it may have on users' psychological well-being. This paper's main objective is to shed light on the effect of social media use on psychological well-being. Building on contributions from various fields in the literature, it provides a more comprehensive study of the phenomenon by considering a set of mediators, including social capital types (i.e., bonding social capital and bridging social capital), social isolation, and smartphone addiction. The paper includes a quantitative study of 940 social media users from Mexico, using structural equation modeling (SEM) to test the proposed hypotheses. The findings point to an overall positive indirect impact of social media usage on psychological well-being, mainly due to the positive effect of bonding and bridging social capital. The empirical model's explanatory power is 45.1%. This paper provides empirical evidence and robust statistical analysis that demonstrates both positive and negative effects coexist, helping to reconcile the inconsistencies found so far in the literature.

Introduction

The use of social media has grown substantially in recent years ( Leong et al., 2019 ; Kemp, 2020 ). Social media refers to “the websites and online tools that facilitate interactions between users by providing them opportunities to share information, opinions, and interest” ( Swar and Hameed, 2017 , p. 141). Individuals use social media for many reasons, including entertainment, communication, and searching for information. Notably, adolescents and young adults are spending an increasing amount of time on online networking sites, e-games, texting, and other social media ( Twenge and Campbell, 2019 ). In fact, some authors (e.g., Dhir et al., 2018 ; Tateno et al., 2019 ) have suggested that social media has altered the forms of group interaction and its users' individual and collective behavior around the world.

Consequently, there are increased concerns regarding the possible negative impacts associated with social media usage addiction ( Swar and Hameed, 2017 ; Kircaburun et al., 2020 ), particularly on psychological well-being ( Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ). Smartphones sometimes distract their users from relationships and social interaction ( Chotpitayasunondh and Douglas, 2016 ; Li et al., 2020a ), and several authors have stressed that the excessive use of social media may lead to smartphone addiction ( Swar and Hameed, 2017 ; Leong et al., 2019 ), primarily because of the fear of missing out ( Reer et al., 2019 ; Roberts and David, 2020 ). Social media usage has been associated with anxiety, loneliness, and depression ( Dhir et al., 2018 ; Reer et al., 2019 ), social isolation ( Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ), and “phubbing,” which refers to the extent to which an individual uses, or is distracted by, their smartphone during face-to-face communication with others ( Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ).

However, social media use also contributes to building a sense of connectedness with relevant others ( Twenge and Campbell, 2019 ), which may reduce social isolation. Indeed, social media provides several ways to interact both with close ties, such as family, friends, and relatives, and weak ties, including coworkers, acquaintances, and strangers ( Chen and Li, 2017 ), and plays a key role among people of all ages as they exploit their sense of belonging in different communities ( Roberts and David, 2020 ). Consequently, despite the fears regarding the possible negative impacts of social media usage on well-being, there is also an increasing number of studies highlighting social media as a new communication channel ( Twenge and Campbell, 2019 ; Barbosa et al., 2020 ), stressing that it can play a crucial role in developing one's presence, identity, and reputation, thus facilitating social interaction, forming and maintaining relationships, and sharing ideas ( Carlson et al., 2016 ), which consequently may be significantly correlated to social support ( Chen and Li, 2017 ; Holliman et al., 2021 ). Interestingly, recent studies (e.g., David et al., 2018 ; Bano et al., 2019 ; Barbosa et al., 2020 ) have suggested that the impact of smartphone usage on psychological well-being depends on the time spent on each type of application and the activities that users engage in.

Hence, the literature provides contradictory cues regarding the impacts of social media on users' well-being, highlighting both the possible negative impacts and the social enhancement it can potentially provide. In line with views on the need to further investigate social media usage ( Karikari et al., 2017 ), particularly regarding its societal implications ( Jiao et al., 2017 ), this paper argues that there is an urgent need to further understand the impact of the time spent on social media on users' psychological well-being, namely by considering other variables that mediate and further explain this effect.

One of the relevant perspectives worth considering is that provided by social capital theory, which is adopted in this paper. Social capital theory has previously been used to study how social media usage affects psychological well-being (e.g., Bano et al., 2019 ). However, extant literature has so far presented only partial models of associations that, although statistically acceptable and contributing to the understanding of the scope of social networks, do not provide as comprehensive a vision of the phenomenon as that proposed within this paper. Furthermore, the contradictory views, suggesting both negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Van Den Eijnden et al., 2016 ; Jiao et al., 2017 ; Whaite et al., 2018 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) and positive impacts ( Carlson et al., 2016 ; Chen and Li, 2017 ; Twenge and Campbell, 2019 ) of social media on psychological well-being, have not been adequately explored.

Given this research gap, this paper's main objective is to shed light on the effect of social media use on psychological well-being. As explained in detail in the next section, this paper explores the mediating effect of bonding and bridging social capital. To provide a broad view of the phenomenon, it also considers several variables highlighted in the literature as affecting the relationship between social media usage and psychological well-being, namely smartphone addiction, social isolation, and phubbing. The paper utilizes a quantitative study conducted in Mexico, comprising 940 social media users, and uses structural equation modeling (SEM) to test a set of research hypotheses.

This article provides several contributions. First, it adds to existing literature regarding the effect of social media use on psychological well-being and explores the contradictory indications provided by different approaches. Second, it proposes a conceptual model that integrates complementary perspectives on the direct and indirect effects of social media use. Third, it offers empirical evidence and robust statistical analysis that demonstrates that both positive and negative effects coexist, helping resolve the inconsistencies found so far in the literature. Finally, this paper provides insights on how to help reduce the potential negative effects of social media use, as it demonstrates that, through bridging and bonding social capital, social media usage positively impacts psychological well-being. Overall, the article offers valuable insights for academics, practitioners, and society in general.

The remainder of this paper is organized as follows. Section Literature Review presents a literature review focusing on the factors that explain the impact of social media usage on psychological well-being. Based on the literature review, a set of hypotheses are defined, resulting in the proposed conceptual model, which includes both the direct and indirect effects of social media usage on psychological well-being. Section Research Methodology explains the methodological procedures of the research, followed by the presentation and discussion of the study's results in section Results. Section Discussion is dedicated to the conclusions and includes implications, limitations, and suggestions for future research.

Literature Review

Putnam (1995 , p. 664–665) defined social capital as “features of social life – networks, norms, and trust – that enable participants to act together more effectively to pursue shared objectives.” Li and Chen (2014 , p. 117) further explained that social capital encompasses “resources embedded in one's social network, which can be assessed and used for instrumental or expressive returns such as mutual support, reciprocity, and cooperation.”

Putnam (1995 , 2000) conceptualized social capital as comprising two dimensions, bridging and bonding, considering the different norms and networks in which they occur. Bridging social capital refers to the inclusive nature of social interaction and occurs when individuals from different origins establish connections through social networks. Hence, bridging social capital is typically provided by heterogeneous weak ties ( Li and Chen, 2014 ). This dimension widens individual social horizons and perspectives and provides extended access to resources and information. Bonding social capital refers to the social and emotional support each individual receives from his or her social networks, particularly from close ties (e.g., family and friends).

Overall, social capital is expected to be positively associated with psychological well-being ( Bano et al., 2019 ). Indeed, Williams (2006) stressed that interaction generates affective connections, resulting in positive impacts, such as emotional support. The following sub-sections use the lens of social capital theory to explore further the relationship between the use of social media and psychological well-being.

Social Media Use, Social Capital, and Psychological Well-Being

The effects of social media usage on social capital have gained increasing scholarly attention, and recent studies have highlighted a positive relationship between social media use and social capital ( Brown and Michinov, 2019 ; Tefertiller et al., 2020 ). Li and Chen (2014) hypothesized that the intensity of Facebook use by Chinese international students in the United States was positively related to social capital forms. A longitudinal survey based on the quota sampling approach illustrated the positive effects of social media use on the two social capital dimensions ( Chen and Li, 2017 ). Abbas and Mesch (2018) argued that, as Facebook usage increases, it will also increase users' social capital. Karikari et al. (2017) also found positive effects of social media use on social capital. Similarly, Pang (2018) studied Chinese students residing in Germany and found positive effects of social networking sites' use on social capital, which, in turn, was positively associated with psychological well-being. Bano et al. (2019) analyzed the 266 students' data and found positive effects of WhatsApp use on social capital forms and the positive effect of social capital on psychological well-being, emphasizing the role of social integration in mediating this positive effect.

Kim and Kim (2017) stressed the importance of having a heterogeneous network of contacts, which ultimately enhances the potential social capital. Overall, the manifest and social relations between people from close social circles (bonding social capital) and from distant social circles (bridging social capital) are strengthened when they promote communication, social support, and the sharing of interests, knowledge, and skills, which are shared with other members. This is linked to positive effects on interactions, such as acceptance, trust, and reciprocity, which are related to the individuals' health and psychological well-being ( Bekalu et al., 2019 ), including when social media helps to maintain social capital between social circles that exist outside of virtual communities ( Ellison et al., 2007 ).

Grounded on the above literature, this study proposes the following hypotheses:

H1a: Social media use is positively associated with bonding social capital.

H1b: Bonding social capital is positively associated with psychological well-being.

H2a: Social media use is positively associated with bridging social capital.

H2b: Bridging social capital is positively associated with psychological well-being.

Social Media Use, Social Isolation, and Psychological Well-Being

Social isolation is defined as “a deficit of personal relationships or being excluded from social networks” ( Choi and Noh, 2019 , p. 4). The state that occurs when an individual lacks true engagement with others, a sense of social belonging, and a satisfying relationship is related to increased mortality and morbidity ( Primack et al., 2017 ). Those who experience social isolation are deprived of social relationships and lack contact with others or involvement in social activities ( Schinka et al., 2012 ). Social media usage has been associated with anxiety, loneliness, and depression ( Dhir et al., 2018 ; Reer et al., 2019 ), and social isolation ( Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ). However, some recent studies have argued that social media use decreases social isolation ( Primack et al., 2017 ; Meshi et al., 2020 ). Indeed, the increased use of social media platforms such as Facebook, WhatsApp, Instagram, and Twitter, among others, may provide opportunities for decreasing social isolation. For instance, the improved interpersonal connectivity achieved via videos and images on social media helps users evidence intimacy, attenuating social isolation ( Whaite et al., 2018 ).

Chappell and Badger (1989) stated that social isolation leads to decreased psychological well-being, while Choi and Noh (2019) concluded that greater social isolation is linked to increased suicide risk. Schinka et al. (2012) further argued that, when individuals experience social isolation from siblings, friends, family, or society, their psychological well-being tends to decrease. Thus, based on the literature cited above, this study proposes the following hypotheses:

H3a: Social media use is significantly associated with social isolation.

H3b: Social isolation is negatively associated with psychological well-being.

Social Media Use, Smartphone Addiction, Phubbing, and Psychological Well-Being

Smartphone addiction refers to “an individuals' excessive use of a smartphone and its negative effects on his/her life as a result of his/her inability to control his behavior” ( Gökçearslan et al., 2018 , p. 48). Regardless of its form, smartphone addiction results in social, medical, and psychological harm to people by limiting their ability to make their own choices ( Chotpitayasunondh and Douglas, 2016 ). The rapid advancement of information and communication technologies has led to the concept of social media, e-games, and also to smartphone addiction ( Chatterjee, 2020 ). The excessive use of smartphones for social media use, entertainment (watching videos, listening to music), and playing e-games is more common amongst people addicted to smartphones ( Jeong et al., 2016 ). In fact, previous studies have evidenced the relationship between social use and smartphone addiction ( Salehan and Negahban, 2013 ; Jeong et al., 2016 ; Swar and Hameed, 2017 ). In line with this, the following hypotheses are proposed:

H4a: Social media use is positively associated with smartphone addiction.

H4b: Smartphone addiction is negatively associated with psychological well-being.

While smartphones are bringing individuals closer, they are also, to some extent, pulling people apart ( Tonacci et al., 2019 ). For instance, they can lead to individuals ignoring others with whom they have close ties or physical interactions; this situation normally occurs due to extreme smartphone use (i.e., at the dinner table, in meetings, at get-togethers and parties, and in other daily activities). This act of ignoring others is called phubbing and is considered a common phenomenon in communication activities ( Guazzini et al., 2019 ; Chatterjee, 2020 ). Phubbing is also referred to as an act of snubbing others ( Chatterjee, 2020 ). This term was initially used in May 2012 by an Australian advertising agency to describe the “growing phenomenon of individuals ignoring their families and friends who were called phubbee (a person who is a recipients of phubbing behavior) victim of phubber (a person who start phubbing her or his companion)” ( Chotpitayasunondh and Douglas, 2018 ). Smartphone addiction has been found to be a determinant of phubbing ( Kim et al., 2018 ). Other recent studies have also evidenced the association between smartphones and phubbing ( Chotpitayasunondh and Douglas, 2016 ; Guazzini et al., 2019 ; Tonacci et al., 2019 ; Chatterjee, 2020 ). Vallespín et al. (2017 ) argued that phubbing behavior has a negative influence on psychological well-being and satisfaction. Furthermore, smartphone addiction is considered responsible for the development of new technologies. It may also negatively influence individual's psychological proximity ( Chatterjee, 2020 ). Therefore, based on the above discussion and calls for the association between phubbing and psychological well-being to be further explored, this study proposes the following hypotheses:

H5: Smartphone addiction is positively associated with phubbing.

H6: Phubbing is negatively associated with psychological well-being.

Indirect Relationship Between Social Media Use and Psychological Well-Being

Beyond the direct hypotheses proposed above, this study investigates the indirect effects of social media use on psychological well-being mediated by social capital forms, social isolation, and phubbing. As described above, most prior studies have focused on the direct influence of social media use on social capital forms, social isolation, smartphone addiction, and phubbing, as well as the direct impact of social capital forms, social isolation, smartphone addiction, and phubbing on psychological well-being. Very few studies, however, have focused on and evidenced the mediating role of social capital forms, social isolation, smartphone addiction, and phubbing derived from social media use in improving psychological well-being ( Chen and Li, 2017 ; Pang, 2018 ; Bano et al., 2019 ; Choi and Noh, 2019 ). Moreover, little is known about smartphone addiction's mediating role between social media use and psychological well-being. Therefore, this study aims to fill this gap in the existing literature by investigating the mediation of social capital forms, social isolation, and smartphone addiction. Further, examining the mediating influence will contribute to a more comprehensive understanding of social media use on psychological well-being via the mediating associations of smartphone addiction and psychological factors. Therefore, based on the above, we propose the following hypotheses (the conceptual model is presented in Figure 1 ):

H7: (a) Bonding social capital; (b) bridging social capital; (c) social isolation; and (d) smartphone addiction mediate the relationship between social media use and psychological well-being.

Figure 1 . Conceptual model.

Research Methodology

Sample procedure and online survey.

This study randomly selected students from universities in Mexico. We chose University students for the following reasons. First, students are considered the most appropriate sample for e-commerce studies, particularly in the social media context ( Oghazi et al., 2018 ; Shi et al., 2018 ). Second, University students are considered to be frequent users and addicted to smartphones ( Mou et al., 2017 ; Stouthuysen et al., 2018 ). Third, this study ensured that respondents were experienced, well-educated, and possessed sufficient knowledge of the drawbacks of social media and the extreme use of smartphones. A total sample size of 940 University students was ultimately achieved from the 1,500 students contacted, using a convenience random sampling approach, due both to the COVID-19 pandemic and budget and time constraints. Additionally, in order to test the model, a quantitative empirical study was conducted, using an online survey method to collect data. This study used a web-based survey distributed via social media platforms for two reasons: the COVID-19 pandemic; and to reach a large number of respondents ( Qalati et al., 2021 ). Furthermore, online surveys are considered a powerful and authenticated tool for new research ( Fan et al., 2021 ), while also representing a fast, simple, and less costly approach to collecting data ( Dutot and Bergeron, 2016 ).

Data Collection Procedures and Respondent's Information

Data were collected by disseminating a link to the survey by e-mail and social network sites. Before presenting the closed-ended questionnaire, respondents were assured that their participation would remain voluntary, confidential, and anonymous. Data collection occurred from July 2020 to December 2020 (during the pandemic). It should be noted that, because data were collected during the pandemic, this may have had an influence on the results of the study. The reason for choosing a six-month lag time was to mitigate common method bias (CMB) ( Li et al., 2020b ). In the present study, 1,500 students were contacted via University e-mail and social applications (Facebook, WhatsApp, and Instagram). We sent a reminder every month for 6 months (a total of six reminders), resulting in 940 valid responses. Thus, 940 (62.6% response rate) responses were used for hypotheses testing.

Table 1 reveals that, of the 940 participants, three-quarters were female (76.4%, n = 719) and nearly one-quarter (23.6%, n = 221) were male. Nearly half of the participants (48.8%, n = 459) were aged between 26 and 35 years, followed by 36 to 35 years (21.9%, n = 206), <26 (20.3%, n = 191), and over 45 (8.9%, n = 84). Approximately two-thirds (65%, n = 611) had a bachelor's degree or above, while one-third had up to 12 years of education. Regarding the daily frequency of using the Internet, nearly half (48.6%, n = 457) of the respondents reported between 5 and 8 h a day, and over one-quarter (27.2%) 9–12 h a day. Regarding the social media platforms used, over 38.5 and 39.6% reported Facebook and WhatsApp, respectively. Of the 940 respondents, only 22.1% reported Instagram (12.8%) and Twitter (9.2%). It should be noted, however, that the sample is predominantly female and well-educated.

Table 1 . Respondents' characteristics.

Measurement Items

The study used five-point Likert scales (1 = “strongly disagree;” 5 = “strongly agree”) to record responses.

Social Media Use

Social media use was assessed using four items adapted from Karikari et al. (2017) . Sample items include “Social media is part of my everyday activity,” “Social media has become part of my daily life,” “I would be sorry if social media shut down,” and “I feel out of touch, when I have not logged onto social media for a while.” The adapted items had robust reliability and validity (CA = 783, CR = 0.857, AVE = 0.600).

Social Capital

Social capital was measured using a total of eight items, representing bonding social capital (four items) and bridging social capital (four items) adapted from Chan (2015) . Sample construct items include: bonging social capital (“I am willing to spend time to support general community activities,” “I interact with people who are quite different from me”) and bridging social capital (“My social media community is a good place to be,” “Interacting with people on social media makes me want to try new things”). The adapted items had robust reliability and validity [bonding social capital (CA = 0.785, CR = 0.861, AVE = 0.608) and bridging social capital (CA = 0.834, CR = 0.883, AVE = 0.601)].

Social Isolation

Social isolation was assessed using three items from Choi and Noh (2019) . Sample items include “I do not have anyone to play with,” “I feel alone from people,” and “I have no one I can trust.” This adapted scale had substantial reliability and validity (CA = 0.890, CR = 0.928, AVE = 0.811).

Smartphone Addiction

Smartphone addiction was assessed using five items taken from Salehan and Negahban (2013) . Sample items include “I am always preoccupied with my mobile,” “Using my mobile phone keeps me relaxed,” and “I am not able to control myself from frequent use of mobile phones.” Again, these adapted items showed substantial reliability and validity (CA = 903, CR = 0.928, AVE = 0.809).

Phubbing was assessed using four items from Chotpitayasunondh and Douglas (2018) . Sample items include: “I have conflicts with others because I am using my phone” and “I would rather pay attention to my phone than talk to others.” This construct also demonstrated significant reliability and validity (CA = 770, CR = 0.894, AVE = 0.809).

Psychological Well-Being

Psychological well-being was assessed using five items from Jiao et al. (2017) . Sample items include “I lead a purposeful and meaningful life with the help of others,” “My social relationships are supportive and rewarding in social media,” and “I am engaged and interested in my daily on social media.” This study evidenced that this adapted scale had substantial reliability and validity (CA = 0.886, CR = 0.917, AVE = 0.688).

Data Analysis

Based on the complexity of the association between the proposed construct and the widespread use and acceptance of SmartPLS 3.0 in several fields ( Hair et al., 2019 ), we utilized SEM, using SmartPLS 3.0, to examine the relationships between constructs. Structural equation modeling is a multivariate statistical analysis technique that is used to investigate relationships. Further, it is a combination of factor and multivariate regression analysis, and is employed to explore the relationship between observed and latent constructs.

SmartPLS 3.0 “is a more comprehensive software program with an intuitive graphical user interface to run partial least square SEM analysis, certainly has had a massive impact” ( Sarstedt and Cheah, 2019 ). According to Ringle et al. (2015) , this commercial software offers a wide range of algorithmic and modeling options, improved usability, and user-friendly and professional support. Furthermore, Sarstedt and Cheah (2019) suggested that structural equation models enable the specification of complex interrelationships between observed and latent constructs. Hair et al. (2019) argued that, in recent years, the number of articles published using partial least squares SEM has increased significantly in contrast to covariance-based SEM. In addition, partial least squares SEM using SmartPLS is more appealing for several scholars as it enables them to predict more complex models with several variables, indicator constructs, and structural paths, instead of imposing distributional assumptions on the data ( Hair et al., 2019 ). Therefore, this study utilized the partial least squares SEM approach using SmartPLS 3.0.

Common Method Bias (CMB) Test

This study used the Kaiser–Meyer–Olkin (KMO) test to measure the sampling adequacy and ensure data suitability. The KMO test result was 0.874, which is greater than an acceptable threshold of 0.50 ( Ali Qalati et al., 2021 ; Shrestha, 2021 ), and hence considered suitable for explanatory factor analysis. Moreover, Bartlett's test results demonstrated a significance level of 0.001, which is considered good as it is below the accepted threshold of 0.05.

The term CMB is associated with Campbell and Fiske (1959) , who highlighted the importance of CMB and identified that a portion of variance in the research may be due to the methods employed. It occurs when all scales of the study are measured at the same time using a single questionnaire survey ( Podsakoff and Organ, 1986 ); subsequently, estimates of the relationship among the variables might be distorted by the impacts of CMB. It is considered a serious issue that has a potential to “jeopardize” the validity of the study findings ( Tehseen et al., 2017 ). There are several reasons for CMB: (1) it mainly occurs due to response “tendencies that raters can apply uniformity across the measures;” and (2) it also occurs due to similarities in the wording and structure of the survey items that produce similar results ( Jordan and Troth, 2019 ). Harman's single factor test and a full collinearity approach were employed to ensure that the data was free from CMB ( Tehseen et al., 2017 ; Jordan and Troth, 2019 ; Ali Qalati et al., 2021 ). Harman's single factor test showed a single factor explained only 22.8% of the total variance, which is far below the 50.0% acceptable threshold ( Podsakoff et al., 2003 ).

Additionally, the variance inflation factor (VIF) was used, which is a measure of the amount of multicollinearity in a set of multiple regression constructs and also considered a way of detecting CMB ( Hair et al., 2019 ). Hair et al. (2019) suggested that the acceptable threshold for the VIF is 3.0; as the computed VIFs for the present study ranged from 1.189 to 1.626, CMB is not a key concern (see Table 2 ). Bagozzi et al. (1991) suggested a correlation-matrix procedure to detect CMB. Common method bias is evident if correlation among the principle constructs is >0.9 ( Tehseen et al., 2020 ); however, no values >0.9 were found in this study (see section Assessment of Measurement Model). This study used a two-step approach to evaluate the measurement model and the structural model.

Table 2 . Common method bias (full collinearity VIF).

Assessment of Measurement Model

Before conducting the SEM analysis, the measurement model was assessed to examine individual item reliability, internal consistency, and convergent and discriminant validity. Table 3 exhibits the values of outer loading used to measure an individual item's reliability ( Hair et al., 2012 ). Hair et al. (2017) proposed that the value for each outer loading should be ≥0.7; following this principle, two items of phubbing (PHUB3—I get irritated if others ask me to get off my phone and talk to them; PHUB4—I use my phone even though I know it irritated others) were removed from the analysis Hair et al. (2019) . According to Nunnally (1978) , Cronbach's alpha values should exceed 0.7. The threshold values of constructs in this study ranged from 0.77 to 0.903. Regarding internal consistency, Bagozzi and Yi (1988) suggested that composite reliability (CR) should be ≥0.7. The coefficient value for CR in this study was between 0.857 and 0.928. Regarding convergent validity, Fornell and Larcker (1981) suggested that the average variance extracted (AVE) should be ≥0.5. Average variance extracted values in this study were between 0.60 and 0.811. Finally, regarding discriminant validity, according to Fornell and Larcker (1981) , the square root of the AVE for each construct should exceed the inter-correlations of the construct with other model constructs. That was the case in this study, as shown in Table 4 .

Table 3 . Study measures, factor loading, and the constructs' reliability and convergent validity.

Table 4 . Discriminant validity and correlation.

Hence, by analyzing the results of the measurement model, it can be concluded that the data are adequate for structural equation estimation.

Assessment of the Structural Model

This study used the PLS algorithm and a bootstrapping technique with 5,000 bootstraps as proposed by Hair et al. (2019) to generate the path coefficient values and their level of significance. The coefficient of determination ( R 2 ) is an important measure to assess the structural model and its explanatory power ( Henseler et al., 2009 ; Hair et al., 2019 ). Table 5 and Figure 2 reveal that the R 2 value in the present study was 0.451 for psychological well-being, which means that 45.1% of changes in psychological well-being occurred due to social media use, social capital forms (i.e., bonding and bridging), social isolation, smartphone addiction, and phubbing. Cohen (1998) proposed that R 2 values of 0.60, 0.33, and 0.19 are considered substantial, moderate, and weak. Following Cohen's (1998) threshold values, this research demonstrates a moderate predicting power for psychological well-being among Mexican respondents ( Table 6 ).

Table 5 . Summary of path coefficients and hypothesis testing.

Figure 2 . Structural model.

Table 6 . Strength of the model (Predictive relevance, coefficient of determination, and model fit indices).

Apart from the R 2 measure, the present study also used cross-validated redundancy measures, or effect sizes ( q 2 ), to assess the proposed model and validate the results ( Ringle et al., 2012 ). Hair et al. (2019) suggested that a model exhibiting an effect size q 2 > 0 has predictive relevance ( Table 6 ). This study's results evidenced that it has a 0.15 <0.29 <0.35 (medium) predictive relevance, as 0.02, 0.15, and 0.35 are considered small, medium, and large, respectively ( Cohen, 1998 ). Regarding the goodness-of-fit indices, Hair et al. (2019) suggested the standardized root mean square residual (SRMR) to evaluate the goodness of fit. Standardized root mean square is an absolute measure of fit: a value of zero indicates perfect fit and a value <0.08 is considered good fit ( Hair et al., 2019 ). This study exhibits an adequate model fitness level with an SRMR value of 0.063 ( Table 6 ).

Table 5 reveals that all hypotheses of the study were accepted base on the criterion ( p -value < 0.05). H1a (β = 0.332, t = 10.283, p = 0.001) was confirmed, with the second most robust positive and significant relationship (between social media use and bonding social capital). In addition, this study evidenced a positive and significant relationship between bonding social capital and psychological well-being (β = 0.127, t = 4.077, p = 0.001); therefore, H1b was accepted. Regarding social media use and bridging social capital, the present study found the most robust positive and significant impact (β = 0.439, t = 15.543, p = 0.001); therefore, H2a was accepted. The study also evidenced a positive and significant association between bridging social capital and psychological well-being (β = 0.561, t = 20.953, p = 0.001); thus, H2b was accepted. The present study evidenced a significant effect of social media use on social isolation (β = 0.145, t = 4.985, p = 0.001); thus, H3a was accepted. In addition, this study accepted H3b (β = −0.051, t = 2.01, p = 0.044). Furthermore, this study evidenced a positive and significant effect of social media use on smartphone addiction (β = 0.223, t = 6.241, p = 0.001); therefore, H4a was accepted. Furthermore, the present study found that smartphone addiction has a negative significant influence on psychological well-being (β = −0.068, t = 2.387, p = 0.017); therefore, H4b was accepted. Regarding the relationship between smartphone addiction and phubbing, this study found a positive and significant effect of smartphone addiction on phubbing (β = 0.244, t = 7.555, p = 0.001); therefore, H5 was accepted. Furthermore, the present research evidenced a positive and significant influence of phubbing on psychological well-being (β = 0.137, t = 4.938, p = 0.001); therefore, H6 was accepted. Finally, the study provides interesting findings on the indirect effect of social media use on psychological well-being ( t -value > 1.96 and p -value < 0.05); therefore, H7a–d were accepted.

Furthermore, to test the mediating analysis, Preacher and Hayes's (2008) approach was used. The key characteristic of an indirect relationship is that it involves a third construct, which plays a mediating role in the relationship between the independent and dependent constructs. Logically, the effect of A (independent construct) on C (the dependent construct) is mediated by B (a third variable). Preacher and Hayes (2008) suggested the following: B is a construct acting as a mediator if A significantly influences B, A significantly accounts for variability in C, B significantly influences C when controlling for A, and the influence of A on C decreases significantly when B is added simultaneously with A as a predictor of C. According to Matthews et al. (2018) , if the indirect effect is significant while the direct insignificant, full mediation has occurred, while if both direct and indirect effects are substantial, partial mediation has occurred. This study evidenced that there is partial mediation in the proposed construct ( Table 5 ). Following Preacher and Hayes (2008) this study evidenced that there is partial mediation in the proposed construct, because the relationship between independent variable (social media use) and dependent variable (psychological well-being) is significant ( p -value < 0.05) and indirect effect among them after introducing mediator (bonding social capital, bridging social capital, social isolation, and smartphone addiction) is also significant ( p -value < 0.05), therefore it is evidenced that when there is a significant effect both direct and indirect it's called partial mediation.

The present study reveals that the social and psychological impacts of social media use among University students is becoming more complex as there is continuing advancement in technology, offering a range of affordable interaction opportunities. Based on the 940 valid responses collected, all the hypotheses were accepted ( p < 0.05).

H1a finding suggests that social media use is a significant influencing factor of bonding social capital. This implies that, during a pandemic, social media use enables students to continue their close relationships with family members, friends, and those with whom they have close ties. This finding is in line with prior work of Chan (2015) and Ellison et al. (2007) , who evidenced that social bonding capital is predicted by Facebook use and having a mobile phone. H1b findings suggest that, when individuals believe that social communication can help overcome obstacles to interaction and encourage more virtual self-disclosure, social media use can improve trust and promote the establishment of social associations, thereby enhancing well-being. These findings are in line with those of Gong et al. (2021) , who also witnessed the significant effect of bonding social capital on immigrants' psychological well-being, subsequently calling for the further evidence to confirm the proposed relationship.

The findings of the present study related to H2a suggest that students are more likely to use social media platforms to receive more emotional support, increase their ability to mobilize others, and to build social networks, which leads to social belongingness. Furthermore, the findings suggest that social media platforms enable students to accumulate and maintain bridging social capital; further, online classes can benefit students who feel shy when participating in offline classes. This study supports the previous findings of Chan (2015) and Karikari et al. (2017) . Notably, the present study is not limited to a single social networking platform, taking instead a holistic view of social media. The H2b findings are consistent with those of Bano et al. (2019) , who also confirmed the link between bonding social capital and psychological well-being among University students using WhatsApp as social media platform, as well as those of Chen and Li (2017) .

The H3a findings suggest that, during the COVID-19 pandemic when most people around the world have had limited offline or face-to-face interaction and have used social media to connect with families, friends, and social communities, they have often been unable to connect with them. This is due to many individuals avoiding using social media because of fake news, financial constraints, and a lack of trust in social media; thus, the lack both of offline and online interaction, coupled with negative experiences on social media use, enhances the level of social isolation ( Hajek and König, 2021 ). These findings are consistent with those of Adnan and Anwar (2020) . The H3b suggests that higher levels of social isolation have a negative impact on psychological well-being. These result indicating that, consistent with Choi and Noh (2019) , social isolation is negatively and significantly related to psychological well-being.

The H4a results suggests that substantial use of social media use leads to an increase in smartphone addiction. These findings are in line with those of Jeong et al. (2016) , who stated that the excessive use of smartphones for social media, entertainment (watching videos, listening to music), and playing e-games was more likely to lead to smartphone addiction. These findings also confirm the previous work of Jeong et al. (2016) , Salehan and Negahban (2013) , and Swar and Hameed (2017) . The H4b results revealed that a single unit increase in smartphone addiction results in a 6.8% decrease in psychological well-being. These findings are in line with those of Tangmunkongvorakul et al. (2019) , who showed that students with higher levels of smartphone addiction had lower psychological well-being scores. These findings also support those of Shoukat (2019) , who showed that smartphone addiction inversely influences individuals' mental health.

This suggests that the greater the smartphone addiction, the greater the phubbing. The H5 findings are in line with those of Chatterjee (2020) , Chotpitayasunondh and Douglas (2016) , Guazzini et al. (2019) , and Tonacci et al. (2019) , who also evidenced a significant impact of smartphone addiction and phubbing. Similarly, Chotpitayasunondh and Douglas (2018) corroborated that smartphone addiction is the main predictor of phubbing behavior. However, these findings are inconsistent with those of Vallespín et al. (2017 ), who found a negative influence of phubbing.

The H6 results suggests that phubbing is one of the significant predictors of psychological well-being. Furthermore, these findings suggest that, when phubbers use a cellphone during interaction with someone, especially during the current pandemic, and they are connected with many family members, friends, and relatives; therefore, this kind of action gives them more satisfaction, which simultaneously results in increased relaxation and decreased depression ( Chotpitayasunondh and Douglas, 2018 ). These findings support those of Davey et al. (2018) , who evidenced that phubbing has a significant influence on adolescents and social health students in India.

The findings showed a significant and positive effect of social media use on psychological well-being both through bridging and bonding social capital. However, a significant and negative effect of social media use on psychological well-being through smartphone addiction and through social isolation was also found. Hence, this study provides evidence that could shed light on the contradictory contributions in the literature suggesting both positive (e.g., Chen and Li, 2017 ; Twenge and Campbell, 2019 ; Roberts and David, 2020 ) and negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) effects of social media use on psychological well-being. This study concludes that the overall impact is positive, despite some degree of negative indirect impact.

Theoretical Contributions

This study's findings contribute to the current literature, both by providing empirical evidence for the relationships suggested by extant literature and by demonstrating the relevance of adopting a more complex approach that considers, in particular, the indirect effect of social media on psychological well-being. As such, this study constitutes a basis for future research ( Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ) aiming to understand the impacts of social media use and to find ways to reduce its possible negative impacts.

In line with Kim and Kim (2017) , who stressed the importance of heterogeneous social networks in improving social capital, this paper suggests that, to positively impact psychological well-being, social media usage should be associated both with strong and weak ties, as both are important in building social capital, and hence associated with its bonding and bridging facets. Interestingly, though, bridging capital was shown as having the greatest impact on psychological well-being. Thus, the importance of wider social horizons, the inclusion in different groups, and establishing new connections ( Putnam, 1995 , 2000 ) with heterogeneous weak ties ( Li and Chen, 2014 ) are highlighted in this paper.

Practical Contributions

These findings are significant for practitioners, particularly those interested in dealing with the possible negative impacts of social media use on psychological well-being. Although social media use is associated with factors that negatively impact psychological well-being, particularly smartphone addiction and social isolation, these negative impacts can be lessened if the connections with both strong and weak ties are facilitated and featured by social media. Indeed, social media platforms offer several features, from facilitating communication with family, friends, and acquaintances, to identifying and offering access to other people with shared interests. However, it is important to access heterogeneous weak ties ( Li and Chen, 2014 ) so that social media offers access to wider sources of information and new resources, hence enhancing bridging social capital.

Limitations and Directions for Future Studies

This study is not without limitations. For example, this study used a convenience sampling approach to reach to a large number of respondents. Further, this study was conducted in Mexico only, limiting the generalizability of the results; future research should therefore use a cross-cultural approach to investigate the impacts of social media use on psychological well-being and the mediating role of proposed constructs (e.g., bonding and bridging social capital, social isolation, and smartphone addiction). The sample distribution may also be regarded as a limitation of the study because respondents were mainly well-educated and female. Moreover, although Internet channels represent a particularly suitable way to approach social media users, the fact that this study adopted an online survey does not guarantee a representative sample of the population. Hence, extrapolating the results requires caution, and study replication is recommended, particularly with social media users from other countries and cultures. The present study was conducted in the context of mainly University students, primarily well-educated females, via an online survey on in Mexico; therefore, the findings represent a snapshot at a particular time. Notably, however, the effect of social media use is increasing due to COVID-19 around the globe and is volatile over time.

Two of the proposed hypotheses of this study, namely the expected negative impacts of social media use on social isolation and of phubbing on psychological well-being, should be further explored. One possible approach is to consider the type of connections (i.e., weak and strong ties) to explain further the impact of social media usage on social isolation. Apparently, the prevalence of weak ties, although facilitating bridging social capital, may have an adverse impact in terms of social isolation. Regarding phubbing, the fact that the findings point to a possible positive impact on psychological well-being should be carefully addressed, specifically by psychology theorists and scholars, in order to identify factors that may help further understand this phenomenon. Other suggestions for future research include using mixed-method approaches, as qualitative studies could help further validate the results and provide complementary perspectives on the relationships between the considered variables.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by Jiangsu University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

This study is supported by the National Statistics Research Project of China (2016LY96).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: smartphone addiction, social isolation, bonding social capital, bridging social capital, phubbing, social media use

Citation: Ostic D, Qalati SA, Barbosa B, Shah SMM, Galvan Vela E, Herzallah AM and Liu F (2021) Effects of Social Media Use on Psychological Well-Being: A Mediated Model. Front. Psychol. 12:678766. doi: 10.3389/fpsyg.2021.678766

Received: 10 March 2021; Accepted: 25 May 2021; Published: 21 June 2021.

Reviewed by:

Copyright © 2021 Ostic, Qalati, Barbosa, Shah, Galvan Vela, Herzallah and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Sikandar Ali Qalati, sidqalati@gmail.com ; 5103180243@stmail.ujs.edu.cn ; Esthela Galvan Vela, esthela.galvan@cetys.mx

† ORCID: Dragana Ostic orcid.org/0000-0002-0469-1342 Sikandar Ali Qalati orcid.org/0000-0001-7235-6098 Belem Barbosa orcid.org/0000-0002-4057-360X Esthela Galvan Vela orcid.org/0000-0002-8778-3989 Feng Liu orcid.org/0000-0001-9367-049X

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• Published: 01 July 2020

The effect of social media on well-being differs from adolescent to adolescent

• Ine Beyens   ORCID: orcid.org/0000-0001-7023-867X 1 ,
• J. Loes Pouwels   ORCID: orcid.org/0000-0002-9586-392X 1 ,
• Irene I. van Driel   ORCID: orcid.org/0000-0002-7810-9677 1 ,
• Loes Keijsers   ORCID: orcid.org/0000-0001-8580-6000 2 &
• Patti M. Valkenburg   ORCID: orcid.org/0000-0003-0477-8429 1  

Scientific Reports volume  10 , Article number:  10763 ( 2020 ) Cite this article

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The question whether social media use benefits or undermines adolescents’ well-being is an important societal concern. Previous empirical studies have mostly established across-the-board effects among (sub)populations of adolescents. As a result, it is still an open question whether the effects are unique for each individual adolescent. We sampled adolescents’ experiences six times per day for one week to quantify differences in their susceptibility to the effects of social media on their momentary affective well-being. Rigorous analyses of 2,155 real-time assessments showed that the association between social media use and affective well-being differs strongly across adolescents: While 44% did not feel better or worse after passive social media use, 46% felt better, and 10% felt worse. Our results imply that person-specific effects can no longer be ignored in research, as well as in prevention and intervention programs.

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Introduction.

Ever since the introduction of social media, such as Facebook and Instagram, researchers have been studying whether the use of such media may affect adolescents’ well-being. These studies have typically reported mixed findings, yielding either small negative, small positive, or no effects of the time spent using social media on different indicators of well-being, such as life satisfaction and depressive symptoms (for recent reviews, see for example 1 , 2 , 3 , 4 , 5 ). Most of these studies have focused on between-person associations, examining whether adolescents who use social media more (or less) often than their peers experience lower (or higher) levels of well-being than these peers. While such between-person studies are valuable in their own right, several scholars 6 , 7 have recently called for studies that investigate within-person associations to understand whether an increase in an adolescent’s social media use is associated with an increase or decrease in that adolescent’s well-being. The current study aims to respond to this call by investigating associations between social media use and well-being within single adolescents across multiple points in time 8 , 9 , 10 .

Person-specific effects

To our knowledge, four recent studies have investigated within-person associations of social media use with different indicators of adolescent well-being (i.e., life satisfaction, depression), again with mixed results 6 , 11 , 12 , 13 . Orben and colleagues 6 found a small negative reciprocal within-person association between the time spent using social media and life satisfaction. Likewise, Boers and colleagues 12 found a small within-person association between social media use and increased depressive symptoms. Finally, Coyne and colleagues 11 and Jensen and colleagues 13 did not find any evidence for within-person associations between social media use and depression.

Earlier studies that investigated within-person associations of social media use with indicators of well-being have all only reported average effect sizes. However, it is possible, or even plausible, that these average within-person effects may have been small and nonsignificant because they result from sizeable heterogeneity in adolescents’ susceptibility to the effects of social media use on well-being (see 14 , 15 ). After all, an average within-person effect size can be considered an aggregate of numerous individual within-person effect sizes that range from highly positive to highly negative.

Some within-person studies have sought to understand adolescents’ differential susceptibility to the effects of social media by investigating differences between subgroups. For instance, they have investigated the moderating role of sex to compare the effects of social media on boys versus girls 6 , 11 . However, such a group-differential approach, in which potential differences in susceptibility are conceptualized by group-level moderators (e.g., gender, age) does not provide insights into more fine-grained differences at the level of the single individual 16 . After all, while girls and boys each represent a homogenous group in terms of sex, they may each differ on a wide array of other factors.

As such, although worthwhile, the average within-person effects of social media on well-being obtained in previous studies may have been small or non-significant because they are diluted across a highly heterogeneous population (or sub-population) of adolescents 14 , 15 . In line with the proposition of media effects theories that each adolescent may have a unique susceptibility to the effects of social media 17 , a viable explanation for the small and inconsistent findings in earlier studies may be that the effect of social media differs from adolescent to adolescent. The aim of the current study is to investigate this hypothesis and to obtain a better understanding of adolescents’ unique susceptibility to the effects of social media on their affective well-being.

Social media and affective well-being

Within-person studies have provided important insights into the associations of social media use with cognitive well-being (e.g., life satisfaction 6 ), which refers to adolescents’ cognitive judgment of how satisfied they are with their life 18 . However, the associations of social media use with adolescents’ affective well-being (i.e., adolescents’ affective evaluations of their moods and emotions 18 ) are still unknown. In addition, while earlier within-person studies have focused on associations with trait-like conceptualizations of well-being 11 , 12 , 13 , that is, adolescents’ average well-being across specific time periods 18 , there is a lack of studies that focus on well-being as a momentary affective state. Therefore, we extend previous research by examining the association between adolescents’ social media use and their momentary affective well-being. Like earlier experience sampling (ESM) studies among adults 19 , 20 , we measured adolescents’ momentary affective well-being with a single item. Adolescents’ momentary affective well-being was defined as their current feelings of happiness, a commonly used question to measure well-being 21 , 22 , which has high convergent validity, as evidenced by the strong correlations with the presence of positive affect and absence of negative affect.

To assess adolescents’ momentary affective well-being (henceforth referred to as well-being), we conducted a week-long ESM study among 63 middle adolescents ages 14 and 15. Six times a day, adolescents were asked to complete a survey using their own mobile phone, covering 42 assessments per adolescent, assessing their affective well-being and social media use. In total, adolescents completed 2,155 assessments (83.2% average compliance).

We focused on middle adolescence, since this is the period in life characterized by most significant fluctuations in well-being 23 , 24 . Also, in comparison to early and late adolescents, middle adolescents are more sensitive to reactions from peers and have a strong tendency to compare themselves with others on social media and beyond. Because middle adolescents typically use different social media platforms, in a complementary way 25 , 26 , 27 , each adolescent reported on his/her use of the three social media platforms that s/he used most frequently out of the five most popular social media platforms among adolescents: WhatsApp, followed by Instagram, Snapchat, YouTube, and, finally, the chat function of games 28 . In addition to investigating the association between overall social media use and well-being (i.e., the summed use of adolescents’ three most frequently used platforms), we examined the unique associations of the two most popular platforms, WhatsApp and Instagram 28 .

Like previous studies on social media use and well-being, we distinguished between active social media use (i.e., “activities that facilitate direct exchanges with others” 29 ) and passive social media use (i.e., “consuming information without direct exchanges” 29 ). Within-person studies among young adults have shown that passive but not active social media use predicts decreases in well-being 29 . Therefore, we examined the unique associations of adolescents’ overall active and passive social media use with their well-being, as well as active and passive use of Instagram and WhatsApp, specifically. We investigated categorical associations, that is, whether adolescents would feel better or worse if they had actively or passively used social media. And we investigated dose–response associations to understand whether adolescents’ well-being would change as a function of the time they had spent actively or passively using social media.

The hypotheses and the design, sampling and analysis plan were preregistered prior to data collection and are available on the Open Science Framework, along with the code used in the analyses ( https://osf.io/nhks2 ). For details about the design of the study and analysis approach, see Methods.

In more than half of all assessments (68.17%), adolescents had used social media (i.e., one or more of their three favorite social media platforms), either in an active or passive way. Instagram (50.90%) and WhatsApp (53.52%) were used in half of all assessments. Passive use of social media (66.21% of all assessments) was more common than active use (50.86%), both on Instagram (48.48% vs. 20.79%) and WhatsApp (51.25% vs. 40.07%).

Strong positive between-person correlations were found between the duration of active and passive social media use (overall: r  = 0.69, p  < 0.001; Instagram: r  = 0.38, p  < 0.01; WhatsApp: r  = 0.85, p  < 0.001): Adolescents who had spent more time actively using social media than their peers, had also spent more time passively using social media than their peers. Likewise, strong positive within-person correlations were found between the duration of active and passive social media use (overall: r  = 0.63, p  < 0.001; Instagram: r  = 0.37, p  < 0.001; WhatsApp: r  = 0.57, p  < 0.001): The more time an adolescent had spent actively using social media at a certain moment, the more time s/he had also spent passively using social media at that moment.

Table 1 displays the average number of minutes that adolescents had spent using social media in the past hour at each assessment, and the zero-order between- and within-person correlations between the duration of social media use and well-being. At the between-person level, the duration of active and passive social media use was not associated with well-being: Adolescents who had spent more time actively or passively using social media than their peers did not report significantly higher or lower levels of well-being than their peers. At the within-person level, significant but weak positive correlations were found between the duration of active and passive overall social media use and well-being. This indicates that adolescents felt somewhat better at moments when they had spent more time actively or passively using social media (overall), compared to moments when they had spent less time actively or passively using social media. When looking at specific platforms, a positive correlation was only found for passive WhatsApp use, but not for active WhatsApp use, and not for active and passive Instagram use.

Average and person-specific effects

The within-person associations of social media use with well-being and differences in these associations were tested in a series of multilevel models. We ran separate models for overall social media use (i.e., active use and passive use of adolescents’ three favorite social media platforms, see Table 2 ), Instagram use (see Table 3 ), and WhatsApp use (see Table 4 ). In a first step we examined the average categorical associations for each of these three social media uses using fixed effects models (Models 1A, 3A, and 5A) to investigate whether, on average, adolescents would feel better or worse at moments when they had used social media compared to moments when they had not (i.e., categorical predictors: active use versus no active use, and passive use versus no passive use). In a second step, we examined heterogeneity in the within-person categorical associations by adding random slopes to the fixed effects models (Models 1B, 3B, and 5B). Next, we examined the average dose–response associations using fixed effects models (Models 2A, 4A, and 6A), to investigate whether, on average, adolescents would feel better or worse when they had spent more time using social media (i.e., continuous predictors: duration of active use and duration of passive use). Finally, we examined heterogeneity in the within-person dose–response associations by adding random slopes to the fixed effects models (Models 2B, 4B, and 6B).

Overall social media use.

The model with the categorical predictors (see Table 2 ; Model 1A) showed that, on average, there was no association between overall use and well-being: Adolescents’ well-being did not increase or decrease at moments when they had used social media, either in a passive or active way. However, evidence was found that the association of passive (but not active) social media use with well-being differed from adolescent to adolescent (Model 1B), with effect sizes ranging from − 0.24 to 0.68. For 44.26% of the adolescents the association was non-existent to small (− 0.10 <  r  < 0.10). However, for 45.90% of the adolescents there was a weak (0.10 <  r  < 0.20; 8.20%), moderate (0.20 <  r  < 0.30; 22.95%) or even strong positive ( r  ≥ 0.30; 14.75%) association between overall passive social media use and well-being, and for almost one in ten (9.84%) adolescents there was a weak (− 0.20 <  r  < − 0.10; 6.56%) or moderate negative (− 0.30 <  r  < − 0.20; 3.28%) association.

The model with continuous predictors (Model 2A) showed that, on average, there was a significant dose–response association for active use. At moments when adolescents had used social media, the time they spent actively (but not passively) using social media was positively associated with well-being: Adolescents felt better at moments when they had spent more time sending messages, posting, or sharing something on social media. The associations of the time spent actively and passively using social media with well-being did not differ across adolescents (Model 2B).

Instagram use

As shown in Model 3A in Table 3 , on average, there was a significant categorical association between passive (but not active) Instagram use and well-being: Adolescents experienced an increase in well-being at moments when they had passively used Instagram (i.e., viewing posts/stories of others). Adolescents did not experience an increase or decrease in well-being when they had actively used Instagram. The associations of passive and active Instagram use with well-being did not differ across adolescents (Model 3B).

On average, no significant dose–response association was found for Instagram use (Model 4A): At moments when adolescents had used Instagram, the time adolescents spent using Instagram (either actively or passively) was not associated with their well-being. However, evidence was found that the association of the time spent passively using Instagram differed from adolescent to adolescent (Model 4B), with effect sizes ranging from − 0.48 to 0.27. For most adolescents (73.91%) the association was non-existent to small (− 0.10 <  r  < 0.10), but for almost one in five adolescents (17.39%) there was a weak (0.10 <  r  < 0.20; 10.87%) or moderate (0.20 <  r  < 0.30; 6.52%) positive association, and for almost one in ten adolescents (8.70%) there was a weak (− 0.20 <  r  < − 0.10; 2.17%), moderate (− 0.30 <  r  < − 0.20; 4.35%), or strong ( r  ≤ − 0.30; 2.17%) negative association. Figure  1 illustrates these differences in the dose–response associations.

The dose–response association between passive Instagram use (in minutes per hour) and affective well-being for each individual adolescent (n = 46). Red lines represent significant negative within-person associations, green lines represent significant positive within-person associations, and gray lines represent non-significant within-person associations. A graph was created for each participant who had completed at least 10 assessments. A total of 13 participants were excluded because they had completed less than 10 assessments of passive Instagram use. In addition, one participant was excluded because no graph could be computed, since this participant's passive Instagram use was constant across assessments.

WhatsApp use

As shown in Model 5A in Table 4 , just as for Instagram, we found that, on average, there was a significant categorical association between passive (but not active) WhatsApp use and well-being: Adolescents reported that they felt better at moments when they had passively used WhatsApp (i.e., read WhatsApp messages). For active WhatsApp use, no significant association was found. Also, in line with the results for Instagram use, no differences were found regarding the associations of active and passive WhatsApp use (Model 5B).

In addition, a significant dose–response association was found for passive (but not active) use (Model 6A). At moments when adolescents had used WhatsApp, we found that, on average, the time adolescents spent passively using WhatsApp was positively associated with well-being: Adolescents felt better at moments when they had spent more time reading WhatsApp messages. The time spent actively using WhatsApp was not associated with well-being. No differences were found in the dose–response associations of active and passive WhatsApp use (Model 6B).

This preregistered study investigated adolescents’ unique susceptibility to the effects of social media. We found that the associations of passive (but not active) social media use with well-being differed substantially from adolescent to adolescent, with effect sizes ranging from moderately negative (− 0.24) to strongly positive (0.68). While 44.26% of adolescents did not feel better or worse if they had passively used social media, 45.90% felt better, and a small group felt worse (9.84%). In addition, for Instagram the majority of adolescents (73.91%) did not feel better or worse when they had spent more time viewing post or stories of others, whereas some felt better (17.39%), and others (8.70%) felt worse.

These findings have important implications for social media effects research, and media effects research more generally. For decades, researchers have argued that people differ in their susceptibility to the effects of media 17 , leading to numerous investigations of such differential susceptibility. These investigations have typically focused on moderators, based on variables such as sex, age, or personality. Yet, over the years, studies have shown that such moderators appear to have little power to explain how individuals differ in their susceptibility to media effects, probably because a group-differential approach does not account for the possibility that media users may differ across a range of factors, that are not captured by only one (or a few) investigated moderator variables.

By providing insights into each individual’s unique susceptibility, the findings of this study provide an explanation as to why, up until now, most media effects research has only found small effects. We found that the majority of adolescents do not experience any short-term changes in well-being related to their social media use. And if they do experience any changes, these are more often positive than negative. Because only small subsets of adolescents experience small to moderate changes in well-being, the true effects of social media reported in previous studies have probably been diluted across heterogeneous samples of individuals that differ in their susceptibility to media effects (also see 30 ). Several scholars have noted that overall effect sizes may mask more subtle individual differences 14 , 15 , which may explain why previous studies have typically reported small or no effects of social media on well-being or indicators of well-being 6 , 11 , 12 , 13 . The current study seems to confirm this assumption, by showing that while the overall effect sizes are small at best, the person-specific effect sizes vary considerably, from tiny and small to moderate and strong.

As called upon by other scholars 5 , 31 , we disentangled the associations of active and passive use of social media. Research among young adults found that passive (but not active) social media use is associated with lower levels of affective well-being 29 . In line with these findings, the current study shows that active and passive use yielded different associations with adolescents’ affective well-being. Interestingly though, in contrast to previous findings among adults, our study showed that, on average, passive use of Instagram and WhatsApp seemed to enhance rather than decrease adolescents’ well-being. This discrepancy in findings may be attributed to the fact that different mechanisms might be involved. Verduyn and colleagues 29 found that passive use of Facebook undermines adults’ well-being by enhancing envy, which may also explain the decreases in well-being found in our study among a small group of adolescents. Yet, adolescents who felt better by passively using Instagram and WhatsApp, might have felt so because they experienced enjoyment. After all, adolescents often seek positive content on social media, such as humorous posts or memes 32 . Also, research has shown that adolescents mainly receive positive feedback on social media 33 . Hence, their passive Instagram and WhatsApp use may involve the reading of positive feedback, which may explain the increases in well-being.

Overall, the time spent passively using WhatsApp improved adolescents’ well-being. This did not differ from adolescent to adolescent. However, the associations of the time spent passively using Instagram with well-being did differ from adolescent to adolescent. This discrepancy suggests that not all social media uses yield person-specific effects on well-being. A possible explanation may be that adolescents’ responses to WhatsApp are more homogenous than those to Instagram. WhatsApp is a more private platform, which is mostly used for one-to-one communication with friends and acquaintances 26 . Instagram, in contrast, is a more public platform, which allows its users to follow a diverse set of people, ranging from best friends to singers, actors, and influencers 28 , and to engage in intimate communication as well as self-presentation and social comparison. Such diverse uses could lead to more varied, or even opposing responses, such as envy versus inspiration.

Limitations and directions for future research

The current study extends our understanding of differential susceptibility to media effects, by revealing that the effect of social media use on well-being differs from adolescent to adolescent. The findings confirm our assumption that among the great majority of adolescents, social media use is unrelated to well-being, but that among a small subset, social media use is either related to decreases or increases in well-being. It must be noted, however, that participants in this study felt relatively happy, overall. Studies with more vulnerable samples, consisting of clinical samples or youth with lower social-emotional well-being may elicit different patterns of effects 27 . Also, the current study focused on affective well-being, operationalized as happiness. It is plausible that social media use relates differently with other types of well-being, such as cognitive well-being. An important next step is to identify which adolescents are particularly susceptible to experience declines in well-being. It is conceivable, for instance, that the few adolescents who feel worse when they use social media are the ones who receive negative feedback on social media 33 .

In addition, future ESM studies into the effects of social media should attempt to include one or more follow-up measures to improve our knowledge of the longer-term influence of social media use on affective well-being. While a week-long ESM is very common and applied in most earlier ESM studies 34 , a week is only a snapshot of adolescent development. Research is needed that investigates whether the associations of social media use with adolescents’ momentary affective well-being may cumulate into long-lasting consequences. Such investigations could help clarify whether adolescents who feel bad in the short term would experience more negative consequences in the long term, and whether adolescents who feel better would be more resistant to developing long-term negative consequences. And while most adolescents do not seem to experience any short-term increases or decreases in well-being, more research is needed to investigate whether these adolescents may experience a longer-term impact of social media.

While the use of different platforms may be differently associated with well-being, different types of use may also yield different effects. Although the current study distinguished between active and passive use of social media, future research should further differentiate between different activities. For instance, because passive use entails many different activities, from reading private messages (e.g., WhatsApp messages, direct messages on Instagram) to browsing a public feed (e.g., scrolling through posts on Instagram), research is needed that explores the unique effects of passive public use and passive private use. Research that seeks to explore the nuances in adolescents’ susceptibility as well as the nuances in their social media use may truly improve our understanding of the effects of social media use.

Participants

Participants were recruited via a secondary school in the south of the Netherlands. Our preregistered sampling plan set a target sample size of 100 adolescents. We invited adolescents from six classrooms to participate in the study. The final sample consisted of 63 adolescents (i.e., 42% consent rate, which is comparable to other ESM studies among adolescents; see, for instance 35 , 36 ). Informed consent was obtained from all participants and their parents. On average, participants were 15 years old ( M  = 15.12 years, SD  = 0.51) and 54% were girls. All participants self-identified as Dutch, and 41.3% were enrolled in the prevocational secondary education track, 25.4% in the intermediate general secondary education track, and 33.3% in the academic preparatory education track.

The study was approved by the Ethics Review Board of the Faculty of Social and Behavioral Sciences at the University of Amsterdam and was performed in accordance with the guidelines formulated by the Ethics Review Board. The study consisted of two phases: A baseline survey and a personalized week-long experience sampling (ESM) study. In phase 1, researchers visited the school during school hours. Researchers informed the participants of the objective and procedure of the study and assured them that their responses would be treated confidentially. Participants were asked to sign the consent form. Next, participants completed a 15-min baseline survey. The baseline survey included questions about demographics and assessed which social media each adolescent used most frequently, allowing to personalize the social media questions presented during the ESM study in phase 2. After completing the baseline survey, participants were provided detailed instructions about phase 2.

In phase 2, which took place two and a half weeks after the baseline survey, a 7-day ESM study was conducted, following the guidelines for ESM studies provided by van Roekel and colleagues 34 . Aiming for at least 30 assessments per participant and based on an average compliance rate of 70 to 80% reported in earlier ESM studies among adolescents 34 , we asked each participant to complete a total of 42 ESM surveys (i.e., six 2-min surveys per day). Participants completed the surveys using their own mobile phone, on which the ESM software application Ethica Data was installed during the instruction session with the researchers (phase 1). Each 2-min survey consisted of 22 questions, which assessed adolescents’ well-being and social media use. Two open-ended questions were added to the final survey of the day, which asked about adolescents’ most pleasant and most unpleasant events of the day.

The ESM sampling scheme was semi-random, to allow for randomization and avoid structural patterns in well-being, while taking into account that adolescents were not allowed to use their phone during school time. The Ethica Data app was programmed to generate six beep notifications per day at random time points within a fixed time interval that was tailored to the school’s schedule: before school time (1 beep), during school breaks (2 beeps), and after school time (3 beeps). During the weekend, the beeps were generated during the morning (1 beep), afternoon (3 beeps), and evening (2 beeps). To maximize compliance, a 30-min time window was provided to complete each survey. This time window was extended to one hour for the first survey (morning) and two hours for the final survey (evening) to account for travel time to school and time spent on evening activities. The average compliance rate was 83.2%. A total of 2,155 ESM assessments were collected: Participants completed an average of 34.83 surveys ( SD  = 4.91) on a total of 42 surveys, which is high compared to previous ESM studies among adolescents 34 .

The questions of the ESM study were personalized based on the responses to the baseline survey. During the ESM study, each participant reported on his/her use of three different social media platforms: WhatsApp and either Instagram, Snapchat, YouTube, and/or the chat function of games (i.e., the most popular social media platforms among adolescents 28 ). Questions about Instagram and WhatsApp use were only included if the participant had indicated in the baseline survey that s/he used these platforms at least once a week. If a participant had indicated that s/he used Instagram or WhatsApp (or both) less than once a week, s/he was asked to report on the use of Snapchat, YouTube, or the chat function of games, depending on what platform s/he used at least once a week. In addition to Instagram and WhatsApp, questions were asked about a third platform, that was selected based on how frequently the participant used Snapchat, YouTube, or the chat function of games (i.e., at least once a week). This resulted in five different combinations of three platforms: Instagram, WhatsApp, and Snapchat (47 participants); Instagram, WhatsApp, and YouTube (11 participants); Instagram, WhatsApp, and chatting via games (2 participants); WhatsApp, Snapchat, and YouTube (1 participant); and WhatsApp, YouTube, and chatting via games (2 participants).

Frequency of social media use

In the baseline survey, participants were asked to indicate how often they used and checked Instagram, WhatsApp, Snapchat, YouTube, and the chat function of games, using response options ranging from 1 ( never ) to 7 ( more than 12 times per day ). These platforms are the five most popular platforms among Dutch 14- and 15-year-olds 28 . Participants’ responses were used to select the three social media platforms that were assessed in the personalized ESM study.

Duration of social media use

In the ESM study, duration of active and passive social media use was measured by asking participants how much time in the past hour they had spent actively and passively using each of the three platforms that were included in the personalized ESM surveys. Response options ranged from 0 to 60 min , with 5-min intervals. To measure active Instagram use, participants indicated how much time in the past hour they had spent (a) “posting on your feed or sharing something in your story on Instagram” and (b) “sending direct messages/chatting on Instagram.” These two items were summed to create the variable duration of active Instagram use. Sum scores exceeding 60 min (only 0.52% of all assessments) were recoded to 60 min. To measure duration of passive Instagram use, participants indicated how much time in the past hour they had spent “viewing posts/stories of others on Instagram.” To measure the use of WhatsApp, Snapchat, YouTube and game-based chatting, we asked participants how much time they had spent “sending WhatsApp messages” (active use) and “reading WhatsApp messages” (passive use); “sending snaps/messages or sharing something in your story on Snapchat” (active use) and “viewing snaps/stories/messages from others on Snapchat” (passive use); “posting YouTube clips” (active use) and “watching YouTube clips” (passive use); “sending messages via the chat function of a game/games” (active use) and “reading messages via the chat function of a game/games” (passive use). Duration of active and passive overall social media use were created by summing the responses across the three social media platforms for active and passive use, respectively. Sum scores exceeding 60 min (2.13% of all assessments for active overall use; 2.90% for passive overall use) were recoded to 60 min. The duration variables were used to investigate whether the time spent actively or passively using social media was associated with well-being (dose–response associations).

Use/no use of social media

Based on the duration variables, we created six dummy variables, one for active and one for passive overall social media use, one for active and one for passive Instagram use, and one for active and one for passive WhatsApp use (0 =  no active use and 1 =  active use , and 0 =  no passive use and 1 =  passive use , respectively). These dummy variables were used to investigate whether the use of social media, irrespective of the duration of use, was associated with well-being (categorical associations).

Consistent with previous ESM studies 19 , 20 , we measured affective well-being using one item, asking “How happy do you feel right now?” at each assessment. Adolescents indicated their response to the question using a 7-point scale ranging from 1 ( not at all ) to 7 ( completely ), with 4 ( a little ) as the midpoint. Convergent validity of this item was established in a separate pilot ESM study among 30 adolescents conducted by the research team of the fourth author: The affective well-being item was strongly correlated with the presence of positive affect and absence of negative affect (assessed by a 10-item positive and negative affect schedule for children; PANAS-C) at both the between-person (positive affect: r  = 0.88, p < 0.001; negative affect: r  = − 0.62, p < 0.001) and within-person level (positive affect: r  = 0.74, p < 0.001; negative affect: r  = − 0.58, p < 0.001).

Statistical analyses

Before conducting the analyses, several validation checks were performed (see 34 ). First, we aimed to only include participants in the analyses who had completed more than 33% of all ESM assessments (i.e., at least 14 assessments). Next, we screened participants’ responses to the open questions for unserious responses (e.g., gross comments, jokes). And finally, we inspected time series plots for patterns in answering tendencies. Since all participants completed more than 33% of all ESM assessments, and no inappropriate responses or low-quality data patterns were detected, all participants were included in the analyses.

Following our preregistered analysis plan, we tested the proposed associations in a series of multilevel models. Before doing so, we tested the homoscedasticity and linearity assumptions for multilevel analyses 37 . Inspection of standardized residual plots indicated that the data met these assumptions (plots are available on OSF at  https://osf.io/nhks2 ). We specified separate models for overall social media use, use of Instagram, and use of WhatsApp. To investigate to what extent adolescents’ well-being would vary depending on whether they had actively or passively used social media/Instagram/WhatsApp or not during the past hour (categorical associations), we tested models including the dummy variables as predictors (active use versus no active use, and passive use versus no passive use; models 1, 3, and 5). To investigate whether, at moments when adolescents had used social media/Instagram/WhatsApp during the past hour, their well-being would vary depending on the duration of social media/Instagram/WhatsApp use (dose–response associations), we tested models including the duration variables as predictors (duration of active use and duration of passive use; models 2, 4, and 6). In order to avoid negative skew in the duration variables, we only included assessments during which adolescents had used social media in the past hour (overall, Instagram, or WhatsApp, respectively), either actively or passively. All models included well-being as outcome variable. Since multilevel analyses allow to include all available data for each individual, no missing data were imputed and no data points were excluded.

We used a model building approach that involved three steps. In the first step, we estimated an intercept-only model to assess the relative amount of between- and within-person variance in affective well-being. We estimated a three-level model in which repeated momentary assessments (level 1) were nested within adolescents (level 2), who, in turn, were nested within classrooms (level 3). However, because the between-classroom variance in affective well-being was small (i.e., 0.4% of the variance was explained by differences between classes), we proceeded with estimating two-level (instead of three-level) models, with repeated momentary assessments (level 1) nested within adolescents (level 2).

In the second step, we assessed the within-person associations of well-being with (a) overall active and passive social media use (i.e., the total of the three platforms), (b) active and passive use of Instagram, and (c) active and passive use of WhatsApp, by adding fixed effects to the model (Models 1A-6A). To facilitate the interpretation of the associations and control for the effects of time, a covariate was added that controlled for the n th assessment of the study week (instead of the n th assessment of the day, as preregistered). This so-called detrending is helpful to interpret within-person associations as correlated fluctuations beyond other changes in social media use and well-being 38 . In order to obtain within-person estimates, we person-mean centered all predictors 38 . Significance of the fixed effects was determined using the Wald test.

In the third and final step, we assessed heterogeneity in the within-person associations by adding random slopes to the models (Models 1B-6B). Significance of the random slopes was determined by comparing the fit of the fixed effects model with the fit of the random effects model, by performing the Satorra-Bentler scaled chi-square test 39 and by comparing the Bayesian information criterion (BIC 40 ) and Akaike information criterion (AIC 41 ) of the models. When the random effects model had a significantly better fit than the fixed effects model (i.e., pointing at significant heterogeneity), variance components were inspected to investigate whether heterogeneity existed in the association of either active or passive use. Next, when evidence was found for significant heterogeneity, we computed person-specific effect sizes, based on the random effect models, to investigate what percentages of adolescents experienced better well-being, worse well-being, and no changes in well-being. In line with Keijsers and colleagues 42 we only included participants who had completed at least 10 assessments. In addition, for the dose–response associations, we constructed graphical representations of the person-specific slopes, based on the person-specific effect sizes, using the xyplot function from the lattice package in R 43 .

Three improvements were made to our original preregistered plan. First, rather than estimating the models with multilevel modelling in R 43 , we ran the preregistered models in Mplus 44 . Mplus provides standardized estimates for the fixed effects models, which offers insight into the effect sizes. This allowed us to compare the relative strength of the associations of passive versus active use with well-being. Second, instead of using the maximum likelihood estimator, we used the maximum likelihood estimator with robust standard errors (MLR), which are robust to non-normality. Sensitivity tests, uploaded on OSF ( https://osf.io/nhks2 ), indicated that the results were almost identical across the two software packages and estimation approaches. Third, to improve the interpretation of the results and make the scales of the duration measures of social media use and well-being more comparable, we transformed the social media duration scores (0 to 60 min) into scales running from 0 to 6, so that an increase of 1 unit reflects 10 min of social media use. The model estimates were unaffected by this transformation.

Reporting summary

Further information on the research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The dataset generated and analysed during the current study is available in Figshare 45 . The preregistration of the design, sampling and analysis plan, and the analysis scripts used to analyse the data for this paper are available online on the Open Science Framework website ( https://osf.io/nhks2 ).

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Acknowledgements

This study was funded by the NWO Spinoza Prize and the Gravitation grant (NWO Grant 024.001.003; Consortium on Individual Development) awarded to P.M.V. by the Dutch Research Council (NWO). Additional funding was received from the VIDI grant (NWO VIDI Grant 452.17.011) awarded to L.K. by the Dutch Research Council (NWO). The authors would like to thank Savannah Boele (Tilburg University) for providing her pilot ESM results.

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I.B., J.L.P., I.I.v.D., L.K., and P.M.V. designed the study; I.B., J.L.P., and I.I.v.D. collected the data; I.B., J.L.P., and L.K. analyzed the data; and I.B., J.L.P., I.I.v.D., L.K., and P.M.V. contributed to writing and reviewing the manuscript.

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Pros & cons: impacts of social media on mental health

• Ágnes Zsila 1 , 2 &
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The use of social media significantly impacts mental health. It can enhance connection, increase self-esteem, and improve a sense of belonging. But it can also lead to tremendous stress, pressure to compare oneself to others, and increased sadness and isolation. Mindful use is essential to social media consumption.

Social media has become integral to our daily routines: we interact with family members and friends, accept invitations to public events, and join online communities to meet people who share similar preferences using these platforms. Social media has opened a new avenue for social experiences since the early 2000s, extending the possibilities for communication. According to recent research [ 1 ], people spend 2.3 h daily on social media. YouTube, TikTok, Instagram, and Snapchat have become increasingly popular among youth in 2022, and one-third think they spend too much time on these platforms [ 2 ]. The considerable time people spend on social media worldwide has directed researchers’ attention toward the potential benefits and risks. Research shows excessive use is mainly associated with lower psychological well-being [ 3 ]. However, findings also suggest that the quality rather than the quantity of social media use can determine whether the experience will enhance or deteriorate the user’s mental health [ 4 ]. In this collection, we will explore the impact of social media use on mental health by providing comprehensive research perspectives on positive and negative effects.

Social media can provide opportunities to enhance the mental health of users by facilitating social connections and peer support [ 5 ]. Indeed, online communities can provide a space for discussions regarding health conditions, adverse life events, or everyday challenges, which may decrease the sense of stigmatization and increase belongingness and perceived emotional support. Mutual friendships, rewarding social interactions, and humor on social media also reduced stress during the COVID-19 pandemic [ 4 ].

On the other hand, several studies have pointed out the potentially detrimental effects of social media use on mental health. Concerns have been raised that social media may lead to body image dissatisfaction [ 6 ], increase the risk of addiction and cyberbullying involvement [ 5 ], contribute to phubbing behaviors [ 7 ], and negatively affects mood [ 8 ]. Excessive use has increased loneliness, fear of missing out, and decreased subjective well-being and life satisfaction [ 8 ]. Users at risk of social media addiction often report depressive symptoms and lower self-esteem [ 9 ].

Overall, findings regarding the impact of social media on mental health pointed out some essential resources for psychological well-being through rewarding online social interactions. However, there is a need to raise awareness about the possible risks associated with excessive use, which can negatively affect mental health and everyday functioning [ 9 ]. There is neither a negative nor positive consensus regarding the effects of social media on people. However, by teaching people social media literacy, we can maximize their chances of having balanced, safe, and meaningful experiences on these platforms [ 10 ].

We encourage researchers to submit their research articles and contribute to a more differentiated overview of the impact of social media on mental health. BMC Psychology welcomes submissions to its new collection, which promises to present the latest findings in the emerging field of social media research. We seek research papers using qualitative and quantitative methods, focusing on social media users’ positive and negative aspects. We believe this collection will provide a more comprehensive picture of social media’s positive and negative effects on users’ mental health.

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Acknowledgements

Ágnes Zsila was supported by the ÚNKP-22-4 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund.

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AZ conceived and drafted the Editorial. MESR wrote the abstract and revised the Editorial. All authors read and approved the final manuscript.

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Zsila, Á., Reyes, M.E.S. Pros & cons: impacts of social media on mental health. BMC Psychol 11 , 201 (2023). https://doi.org/10.1186/s40359-023-01243-x

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Virtual lab coats: The effects of verified source information on social media post credibility

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Interdisciplinary Hub on Digitisation and Society, Radboud University, Nijmegen, The Netherlands, Institute of Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – review & editing

Affiliation Interdisciplinary Hub on Digitisation and Society, Radboud University, Nijmegen, The Netherlands

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

Affiliation Department of Communication Science, Vrije Universiteit, Amsterdam, The Netherlands

Affiliation Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands

• Jorrit Geels, 
• Paul Graßl, 
• Hanna Schraffenberger, 
• Martin Tanis, 
• Mariska Kleemans

• Published: May 29, 2024
• https://doi.org/10.1371/journal.pone.0302323
• Peer Review
• Reader Comments

Social media platform’s lack of control over its content made way to the fundamental problem of misinformation. As users struggle with determining the truth, social media platforms should strive to empower users to make more accurate credibility judgements. A good starting point is a more accurate perception of the credibility of the message’s source. Two pre-registered online experiments ( N = 525; N = 590) were conducted to investigate how verified source information affects perceptions of Tweets (study 1) and generic social media posts (study 2). In both studies, participants reviewed posts by an unknown author and rated source and message credibility, as well as likelihood of sharing. Posts varied by the information provided about the account holder: (1) none, (2) the popular method of verified source identity, or (3) verified credential of the account holder (e.g., employer, role), a novel approach. The credential was either relevant to the content of the post or not. Study 1 presented the credential as a badge, whereas study 2 included the credential as both a badge and a signature. During an initial intuitive response, the effects of these cues were generally unpredictable. Yet, after explanation how to interpret the different source cues, two prevalent reasoning errors surfaced. First, participants conflated source authenticity and message credibility. Second, messages from sources with a verified credential were perceived as more credible, regardless of whether this credential was context relevant (i.e., virtual lab coat effect). These reasoning errors are particularly concerning in the context of misinformation. In sum, credential verification as tested in this paper seems ineffective in empowering users to make more accurate credibility judgements. Yet, future research could investigate alternative implementations of this promising technology.

Citation: Geels J, Graßl P, Schraffenberger H, Tanis M, Kleemans M (2024) Virtual lab coats: The effects of verified source information on social media post credibility. PLoS ONE 19(5): e0302323. https://doi.org/10.1371/journal.pone.0302323

Editor: Nicola Diviani, Swiss Paraplegic Research, SWITZERLAND

Received: August 9, 2023; Accepted: April 2, 2024; Published: May 29, 2024

Copyright: © 2024 Geels et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

In our digital- & information-society, misinformation has become a fundamental problem. A recent example includes a wave of misinformation in November 2022, right after Twitter (now ‘X’) announced it paid subscription [ 1 ]. The new policy included that every user could pay $8 to get a blue verification badge, implying their identity was verified. However, users abused this badge to imply a verified identity with the goal of impersonating companies and spread misinformation. Many readers believed the accounts belonged to the impersonated companies and accepted their misinformation posts as true. Consequently, the stocks of the impersonated companies dropped [ 1 ].

Events like these illustrate the relevance of reliable source information when users look for credible information online. Source information is typically provided by verifying the identity of account holders. For company accounts, certainty over their identity is often sufficient to prevent impersonation and misinformation. Yet, for (unknown) people, certainty over their identity provides little extra information on the credibility of their information. It can therefore be dangerous if users conflate verified source identity and message credibility.

For more accurate content evaluation, certainty over their credentials (e.g., employer, role) can be desired instead [ 2 ], as they could signal expertise. For example, if an unknown person makes a medical claim and one were to doubt its credibility, it is much more valuable to know their medical credentials rather than their identity. Therefore, this paper compares the behavioural effects of source identity verification and the novel approach of source credential verification to reduce the impact of misinformation in social media.

The birth of modern misinformation

It is incredibly important that internet users can easily find accurate information. In the traditional media landscape (e.g., newspapers), information is typically checked on its truthfulness by so-called gatekeepers (e.g., journalists) prior to publishing [ 3 ]. However, people increasingly use social media as their primary source of news [ 4 ]. Because social media’s nature, anyone can say something, and traditional institutions have less authority [ 5 ]. However, this could come at the expense of information quality because not everyone has the same expertise [ 6 ]. For example, social media has become an important source of medical information [ 7 , 8 ]. Especially in that case, it is crucial that people rely primarily on expert advice.

Given the reduced authority of the traditional gatekeepers on social media, the responsibility of checking for truthfulness is shifted away from these gatekeepers to the end-users [ 9 , 10 ]. However, accuracy assessments can be difficult and time-consuming for users [ 10 ]. Hence, they often use simple rules of thumb (i.e., heuristics) to quickly make accuracy assessments and decisions regarding whether to share certain information [ 11 – 13 ]. When such quick assessments are inaccurate, it can have disastrous consequences. For example, take the prominent role of online misinformation in the COVID-19 pandemic (e.g., [ 14 , 15 ]), the US Capitol riot (e.g., [ 16 ]), and the war in Ukraine (e.g., [ 17 ]).

To help people make these decisions more accurately yet still quickly, a popular approach is fact-checking. However, research has shown various problems with fact-checking. First, despite many social platforms using tags such as ‘disputed’ or ‘false’ [ 18 ], the effect of such tags is limited [ 19 – 22 ]. Moreover, manually tagging all social media posts is infeasible [ 23 – 25 ], and automated detection cannot fully replace this process [ 26 ]. Next, when only tagging a subset of social media posts, unlabelled posts could then be perceived as accurate even if they are not [ 27 ]. Last but certainly not least, countering inaccurate beliefs through debunks might not be effective (e.g., [ 28 ]), if such debunks are even noticed at all. It thus seems the user cannot be completely excluded from credibility assessment.

Instead of a platform-centred approach to reducing the impact of misinformation using truth labels or debunking information, another (perhaps more promising) approach is to empower the end-user themselves. Examples of this alternative user-centred approach often include media literacy education [ 29 ], to help users improve the accuracy of their judgements. Yet, media literacy education might not be accessible to all [ 24 ], and there is also evidence suggesting that media literacy education by itself does not necessarily influence the impact of misinformation [ 29 – 31 ]. Hence, users should be empowered through the platform itself [ 24 , 32 ].

Empowering users for more accurate truth assessment

A social media platform cannot fully control its content, but it can instead make its users smarter about which content they believe to be true. A user’s accuracy of determining truths is shaped by how credible the content appears to be to a user [ 33 ]. For online content, these accuracy assessments are known to depend on four types of factors, namely the characteristics of the end-user, platform cues, message cues, and source cues [ 34 ]. Characteristics of the end-user that can affect determining credibility include factors such as their prior knowledge, frequency and purpose of internet usage, as well as demographic variables like age. Platform cues, such as the aesthetics of the website or the presence of certificates or recommendations from trusted sources, can also impact credibility perception. Next, message cues like the presence of a timestamp, the use of professional and clear writing, or the plausibility of the message itself can influence its perceived credibility [ 34 ].

Lastly, the credibility of content is heavily evaluated through the lens of perceived source credibility [ 35 ]. Moreover, source credibility is arguably the feature that yields the most accurate message credibility perception [ 36 ]. Source cues that influence credibility judgements include factors such as the degree to which a user identifies with the author, author qualifications and credentials signalling their expertise, or their reputation [ 34 ]. For example, knowing the origin of a message, such as the newspaper or journalist behind it, can greatly impact how users perceive its credibility. The underlying assumption here is that statements from credible sources are considered more trustworthy than those from less reliable sources.

Therefore, providing information about the source can help users make more accurate source and message credibility judgements. Unfortunately, social media platforms often provide limited information about a source and its credibility. Still, source credibility cues yield a useful heuristic against misinformation [ 37 , 38 ]. With the goal of empowering users to make more accurate credibility judgements of online information, this paper aims to explore how various cues of source credibility on social media influence users’ evaluations of credibility.

Verified source information

Most social media platforms, to some degree, already provide source cues in the form of verification badges. Namely, accounts of public interest (e.g., celebrities, public institutions, governments, etc.) can obtain a verification badge: the social media platform has then verified that the holders of these accounts are indeed who they claim to be [ 39 , 40 ], i.e., authentic . Current developments on Twitter, Instagram and Facebook include paid subscriptions to obtain verification badges [ 1 , 41 ]. Introducing verification badges as a subscription makes these badges slightly more accessible to the public. However, there is reason to believe that users might conflate source authenticity (i.e., verified source identity) and message credibility [ 42 , 43 ]. The literature is unclear on the effects of source authenticity on source and message credibility, partly due to its methodology (see Related work for more details). This paper therefore re-explores the effects of source authenticity badges on social media.

Moreover, this study explores potential new solutions to improve source credibility judgements on social media. As posed before, it seems more useful to have certainty about the source’s credentials rather than their identity when judging information. To elaborate, a verification badge confirms that the unknown sources are who they claim to be, i.e., its authenticity. Yet, it often is more relevant to be sure they are what they claim to be (i.e., in terms of credentials or expertise). For example, it might be helpful to know whether a post about COVID-19 comes from a medical professional, whether someone predicting earthquakes is a geologist, or whether someone describing political unrest is located in the city they are writing about.

Such (verified) credentials can be a useful heuristic for assessing credibility [ 44 ], and potentially mitigate the influence of misinformation on an individual’s beliefs and their inclination to share the information [ 45 ]. However, credentials of an unknown author are currently commonly displayed (if available) in their account’s biography, which is rarely used in credibility judgements as it is not directly accessible [ 37 ]. Even when such information is disclosed in the biography, it is self-reported, and users are unlikely verify this information [ 13 , 46 ], possibly because it requires more effort [ 46 ]. Still, when visible at a glance, credential verification could empower the user in evaluating the accuracy of content, while reducing the required effort to do so [ 47 ]. Lastly, credential verification could make social media more accessible, as it could give a voice to those whose expertise is not well-known, i.e., evident from their identity being verified.

An interesting development here is the introduction of digital identity wallets [ 48 ], which are mobile applications that enable users to collect, store, and share verified (identifying or non-identifying) personal data. Examples of such data are city of residence, nationality, educational degrees, or certificates [ 49 ]. Thus, credential verification could prove an unknown author’s credential and be displayed together with their social media post [ 2 ], following the suggestion that source information should be visible at a glance [ 36 , 37 ].

However, providing such verified information comes with technical, ethical, and societal challenges. The technical feasibility of a credential verification system on Twitter has been demonstrated [ 2 ]. Still, showing verified attributes of a person comes at the cost of privacy, could emphasise more verifiable data (e.g., degrees) over less tangible expertise (e.g., self-taught skills), and could potentially be misinterpreted.

Overall, credential verification sounds like a promising heuristic. However, we fear that the credibility of a source with verified credentials might be inflated when discussing topics outside their domain of expertise (henceforth the “virtual lab coat effect”). Therefore, before developing an infrastructure that provides verified credentials, it is crucial to evaluate its potential impact on users. Though user perceptions and potential misconceptions have been explored in pilot studies [ 50 , 51 ], this paper presents the first two large-scale empirical studies on identity and credential verification of unknown sources on social media. Intermediate results are discussed per study, after which the paper concludes with a general discussion.

Related work

Metzger et al. [ 52 ] conducted research on how users make reliability judgements online. They argue that credibility judgements of information from traditional media may not necessarily be formed in the same way as judgements of information from online media. Their study identified five heuristics that users employ to assess the credibility of online information. They show that the reputation of a source is an important heuristic for evaluating the credibility of online content. Here, the credibility judgement is primarily based on prior interaction with the source and its familiarity. Next, using the expectancy violation heuristic, users consider whether their expectations are met by the content (e.g., in professionalism). The other three heuristics users tend to employ are endorsement (i.e., credibility judgements based on the assessments of others), consistency (i.e., cross-checking content with different sources), and persuasive intent (i.e., suspicion of hidden agendas, such as with commercial content).

However, the findings by Metzger et al. [ 52 ] do not exclude the possibility of users considering additional information when it is provided to them. Namely, users are likely to incorporate all available information to form credibility judgements about the source [ 53 ]. Therefore, it is interesting to examine additional cues, such as verified identity or credentials, and explore their effects on source and message credibility.

Furthermore, many studies have investigated sharing behaviour of users in the context of misinformation (see, e.g., [ 29 , 54 – 62 ]). An important notion in this domain is that credibility and sharing judgements have recently been found to be two separate, not necessarily related decisions (see, e.g., [ 29 , 56 , 62 ]). For example, users might share information they know to be inaccurate but would be ‘interesting if it were true’ [ 59 ]. Moreover, misinformation is often shared without sharers being aware of its inaccuracy [ 61 , 62 ]. Hence, credibility judgements and sharing intentions should be considered independently.

The relationship between source credibility and sharing has been explored in a similar research by Kim & Dennis [ 12 ]. In their experiment, some posts included source credibility ratings in the form of, e.g., star ratings. They found that when including such credibility ratings, users became more critical of all incoming information and decreased in sharing behaviour. These results illustrate how the design of social media posts can affect both credibility and sharing behaviours. The authors call for investigations on how author information influences credibility and sharing behaviour. The present paper investigates the effects of two types of (verified) author information: identity verification, and credential verification. Related work on either approach is discussed below.

Identity verification

A handful of researchers have investigated the effects of verified source identity on the credibility of their message. There namely is reason to suspect that users conflate source authenticity and message credibility, implying that messages from authors whose identity is verified are more credible. For example, there is evidence to suggest that claiming to be an ‘official’ (i.e., authentic) source positively affects ones perceived message credibility [ 63 ]. However, that study used websites as stimuli, so the results do not necessarily generalise to social media accounts. Next, participants in the experiment of Morris et al. [ 37 ] explicitly mentioned that verification of a source’s identity positively affected the credibility of the message. Yet, Morris et al. do not provide behavioural evidence. It thus remains unclear whether their findings represent analytical thinking or heuristic thinking, which is an important distinction as the latter dominates credibility judgements on social media [ 52 ].

In contrast, some scholars did not detect a relationship between account verification and message credibility [ 39 , 42 ]. This suggests users may simply not conflate source authenticity and message credibility. For example, Vaidya et al. state “users generally understand the meaning of verified accounts” [ 42 ] (p11). Still, some caveats in the methodology of [ 39 , 42 ] are to be noted. First, Vaidya et al. [ 42 ] measure message credibility as the degree to which one is likely to adopt or share the message. However, as mentioned, credibility and sharing judgements are not necessarily related. Alternatively, their results can possibly explained by that only few people tend to often re-share information (e.g., [ 56 , 58 ]). Hence, separately measuring message credibility instead (e.g., through the scale by Appelman & Sundar [ 64 ]) reveals more insightful information about whether users conflate source authenticity and message credibility. Moreover, research on the relationship between account verification and message credibility concludes there is no effect based on the absence of evidence of an effect [ 39 , 42 ]. However, absence of evidence does not mean evidence of absence [ 65 ]. The analysis methods used in their studies cannot detect absence of an effect (e.g., [ 66 ]).

In sum, the effects of identity verification badges on perceived source and message credibility are unclear. Still, social media platforms like Twitter and Meta employ verified identity badges [ 1 , 40 ], but also signed the Code of Practice, thus promised to aid users in identifying trustworthy content [ 32 ]. If a verified identity makes any content more credible, these badges may even boost misinformation, especially if they are more accessible to the public. Therefore, the effects of identity verification on source and message credibility as well as sharing behaviour should be explored more in-depth using methods that can detect whether an effect is present, e.g., Bayesian models (e.g., [ 66 ]). Namely, in contrast to classical frequentist statistical methods, Bayesian models can both reject as well as accept null hypotheses.

Credential verification

Still, theoretically, it is sound that learning the identity of some unknown source is verified does not affect credibility of their message. A potentially more useful heuristic to approach message credibility, is source credentials [ 36 ]. Namely, users perceive messages from experts as more credible, but this effect only seems to occur when the user is uncertain about the information accuracy [ 44 ], e.g., when the topic is not in the domain of expertise of the user. For instance, scholars [ 67 – 69 ] found that online health information from a source with medical expertise is perceived as more credible compared to a source without clear expertise. Lee & Sundar [ 70 ] found that when a source has many online followers, their content is perceived as more credible when the source claims expertise. Yet, when an author has a small audience, information from an expert is perceived as less credible compared to an author without claimed expertise.

In terms of the heuristics identified by Metzger et al. [ 52 ], verified credentials align with the reputation heuristic. For instance, although the specific medical professional may not be familiar, the general reputation of medical professionals is. Verified credentials are thus likely more informative than verified identity for unknown sources, as verifying the identity of a source reveals nothing about their credentials (i.e., reputation), an important heuristic [ 52 ]. Yet, the reputation heuristic poses the danger of a “virtual lab coat effect” (i.e., verified expertise yielding increased credibility on topics outside of domain expertise), as users might not consider whether the reputation is relevant to the message. For example, evidence from online review literature suggests that every extra piece of information about a source improves the credibility of their review [ 71 – 73 ].

However, the expectancy violation heuristic could be interpreted more broadly to serve as a counterargument against the occurrence of such a virtual lab coat effect. Namely, if some medical professional provides information on a different topic, this may deviate from the user’s expectations and therefore be perceived as less credible. In sum, it is unclear whether verifying source credentials yields a virtual lab coat effect. Therefore, it is crucial to carefully examine the effects of verified source credentials on social media.

The goal of this first study was to explore the effect of source credibility cues on information of unknown sources on social media, contributing to research on countering misinformation. The misinformation problem is fuelled by people believing and/or sharing misinformation. Hence, it is investigated how source credibility cues affect perceived source and message credibility, as well as sharing intentions. Note that this paper refers to Twitter rather than ‘X’, as we conducted our study before X was launched. Specifically, study 1 was conducted in August 2021, i.e., before the big changes on Twitter [ 1 ].

To enable easier comparison of our results, we adopted the stimuli and hypotheses 1a/b/c based on the work by Vaidya et al. [ 42 ]. Next, study 1 used a similar methodology, thus focusing on Twitter. Compared to Vaidya et al. [ 42 ], the present study differs in the conceptualisation of credibility. Namely, we separately measured source credibility, message credibility, and sharing intentions. As noted above, previous work in this area used frequentist statistical methods, which, in contrast to Bayesian methods, cannot yield conclusions on the presence or absence of an effect (e.g., [ 66 ]). Hence, the data were analysed with Bayesian models to determine the presence or absence of the relationship between source credibility cues and the aforementioned measures. Another important reason to conduct a Bayesian analysis instead of a frequentist analysis, is because Bayesian models often align more closely with how humans conceptualise and interpret parameter estimates [ 74 ].

We conducted an online experiment to investigate the effects of two types of source credibility cues on social media. First, we investigated the effects of the commonly used identity verification badges, formulating H1a/b/c to confirm the results by Vaidya et al. [ 42 ]. Namely, the authors report that identity verification badges have limited to no effect on perceived credibility or sharing on Twitter. Second, we investigated the effects of new envisioned credential-badges, containing verified employer information about social media sources. Such extra information should help users make more accurate judgements, thus only affect the user’s judgement if the verified credential is relevant to the context. Accordingly, this led to the following hypotheses:

• Hypotheses 1a/b/c : People find Tweets with an identity verification badge equally credible (a: source credibility, b: message credibility), and are equally inclined to share them (c: likelihood of sharing), compared to those without a badge.
• Hypotheses 2a/b/c : People find Tweets with a credential verification badge more credible (a: source credibility, b: message credibility), and are more inclined to share them (c: likelihood of sharing), compared to those without a badge, only if the credential is relevant to the context.

Moreover, this study focuses on how users intuitively form credibility judgements and sharing intentions based on looking at the Tweets. First, this aligns with the heuristic evaluation commonly employed on social media [ 52 ]. Second, to the best of our knowledge, social media on-boarding does not include information about how to interpret identity badges. Hence, not including information on the interpretation of these badges prior to exposure seems most ecologically valid.

Still, the study aimed to empower users to more accurately assess online information. Therefore, the experiment consisted of two rounds: a first round with intuitive responses , and a second round with informed responses as part of an exploratory analysis. Namely, prior to this second round, users were provided with information about the interpretation of the identity and credential verification badges. This setup loosely followed the advice of Fallis [ 33 ] that users should receive instructions of what features are indicative of information accuracy.

Method study 1

Before running the experiment, we preregistered the sample size estimation, hypotheses, and planned statistical analysis. The preregistration and all used stimuli, data, and analysis scripts are available on the Open Science Framework ( https://osf.io/cyh8e/ ).

Study 1 was approved by the Ethics Committee and Faculty Board of Social Sciences at Radboud University. The ethical approval used reference number ECSW-2021–079. As part of the ethical research procedure, participants expressed informed consent through an electronic form prior to the experiment.

The experiment used a 3x2 between-subjects design, with each participant viewing one Tweet. There were two independent variables: First, the source credibility cue, with the three conditions: no badge (control condition), identity verification badge, and credential badge which confirmed the author works for University College Hospital. Second, the Tweet context , with two conditions: a health -related context where the medical profession is relevant and a non-health (household) context where the medical employment is not relevant. There were three dependent variables: First, sharing likelihood, indicating how likely a participant is to share the information in the Tweet with others. Second, source credibility, indicating how much credibility a participant attributes to the Twitter account. Third, message credibility, indicating how much credibility a participant attributes to the Twitter post.

Stimuli and setup.

A (fictional) Tweet was created for each of the six conditions, where each of the six conditions was a combination of one of three badge types and one of two contexts. The medical Tweets are displayed in S1 Fig (all stimuli are available on Open Science Framework). The experiment was hosted on a licensed LimeSurvey server from the host university, where the Tweets were displayed as screenshots.

For the experiment, a realistic yet generic profile picture and name was chosen. All factors of the Tweet apart from the source credibility badge were kept constant across conditions. The number of retweets (101) and likes (260) as well as Tweet contents were taken from [ 42 ] to enable more direct comparison of results. The text for the medical Tweet therefore read “There is an increased risk of hypertrophic cardiomyopathy in people who drink 4+ cups of coffee per day.” Next, the non-medical, household-related Tweet read “This year’s increase in cattle disease will cause 12% jump in average household’s grocery bill”.

Participants.

On 30 August 2021, we recruited a total of N = 525 participants, based on a G*power analysis. Note that this analysis is typically only used for frequentist statistic analyses, as opposed to Bayesian analyses. Still, the G*power analysis was purposely used to indicate an ‘ethical’ sample size and to enable other researchers to re-use our data for frequentist analyses.

Our sample was recruited through Prolific Academic, recruiting anyone with an age between 18 and 65 years (to represent a broad range of society) and their current living location in the United Kingdom (to minimise noise in the data because of cultural differences). Participants were compensated with £1 for successfully completing the study, which was estimated to take around 8 minutes (£7.50/h). On average, it took participants 4.13 minutes ( SD = 2.68) to complete the study. The total sample population had a mean age of 31.36 years ( SD = 11.11). A pilot study with 20 people was conducted prior to the main data collection to confirm whether everything was clear for the participants and worked as expected.

Before the experiment, we presented participants with information about the study. The topic only indicated ‘Perception of Twitter posts’ as a topic, intentionally not touching upon credibility to circumvent possible bias. After the informed consent procedure, we asked participants demographic questions and background questions about their Twitter use, trust in medical organisations, and media literacy. Subsequently, participants were randomly assigned to one of the six conditions and thus presented one of the six Twitter posts. They were asked to look at the Tweet and read its contents. Then, they were asked to report on their likelihood of sharing and perceived source and message credibility. In that order, to not bias the sharing decision by the explicit credibility questions. The questions were displayed on a separate page from the Tweet, to assess user’s heuristic evaluation rather than their critical evaluation. Next, the survey included several questions to check if they had paid attention to the Tweet and could recall whether—if any—account badge they had seen.

After this ‘first round’, it was explained to the participants how to interpret the different possible badges included in the experiment. Here, it was explained the Tweet’s author could either have no badge, an identity badge, or a credential badge. The information also included explanation on how to interpret the two badges, namely either as verified identity or as verified credentials respectively. The full explanation text can be found in S1 File .

This information was followed up by the Tweet they had already seen and were asked to complete the same credibility and sharing questions as before, to explore the effects of this information. In the end, we thanked the participants for taking part in the experiment and debriefed them about the purpose of this study. The debriefing made clear that all shown Tweets and their content were purely fictional.

Prior to viewing the Tweet, the participants answered a few background questions. First, Twitter use was assessed on a four-point scale ranging from Never to Often (higher values indicate more Twitter use; M = 3.39, SD = 0.73). Next, it was measured how much participants trust employees of medical organisations, by asking “How much of the time do you think you can trust medical organisations to do what is right?”. To answer, a four-point scale ranged from Never (1) to Always (4), M = 3.05, SD = 0.58. Lastly, media literacy skills were assessed using the validated scale from Vraga et al. [ 75 ]. This scale is comprised of six items on a seven-point scale ranging from Strongly disagree (1) to Strongly agree (7) [ 75 ], M = 5.51, SD = 0.84, α = .78. Example items are “I have the skills to interpret news messages” and “I’m often confused about the quality of news and information”.

Three dependent variables were measured: sharing intentions, message credibility, and source credibility. We used a five-point Likert-scale ranging from Very unlikely (1) to Very likely (5) from Vaidya et al. [ 42 ], to measure the likelihood that participants would share the information provided in the Tweet. Though self-reported sharing intentions conceptually differs from actual social media sharing behaviour, they are correlated [ 76 ]. Although sharing is a binary decision in practice, wider scales are used to measure this concept more sensitively.

Next, to measure how credible participants found the Twitter account holder, we used the five-point scale from Metzger et al. [ 77 ]. Participants had to report how biased, trustworthy, professional, and credible they found the author, with the answer options ranging from Not at all to Extremely (higher values indicate more credibility). The source credibility measure showed good internal consistency with a raw Cronbach’s α = .80. Dropping the item ‘biased’ would increase the overall α by .11. However, this is not advisable because the scale only consists of few questions, and internal consistency is good even without modifications.

To assess message credibility, participants rated how accurate, believable and authentic they found the content of the Tweet through a seven-point Likert-scale, ranging from Strongly disagree to Strongly agree (based on [ 64 ]), α = .90.

Lastly, we included some checks to assess whether participants paid sufficient attention. First, 8 participants were excluded from the analysis as they could not remember the content of the Tweet. Next, participant also were excluded from analysis if they thought they knew the fictional account, to prevent familiarity bias (only 1 out of 533 participants). Finally, participants were asked to report which badge the author of the Tweet had, where 40.5% reported they cannot remember, 38.5% remembered correctly, 21% did not remember correctly. Clearly, many participants guessed, supporting that source credibility cues are used as a heuristic rather than input for elaborate reasoning. Still, participants were not excluded from analysis based on their answer, as we are interested in both heuristic and more informed effects of source credibility cues. An exploratory analysis performed on the sub-sample that only considered the participants that answers the recall question correctly produced the same general pattern of results compared to the main analysis.

In the main analysis, we measured the main and interaction effects of source credibility cue and context on sharing intentions, message credibility, and source credibility. The model controlled for the participants’ Twitter use and media literacy. Trust in medical organisations was excluded for robustness and reliability, i.e., because this factor was not measured using a validated scale. Note that controlling for this variable yielded mostly similar outcomes to the main analysis.

The main analysis used the values of the participants’ intuitive response , i.e., the data obtained after participants had seen the Tweet for the first time, without any prior explanations about the meaning of the different badges. To explore the effects of an information intervention on verified source information, the main analysis also included the data of the participants’ informed response . This data was obtained after the meaning of the badges had been explained, and participants had seen the Tweet for the second time. For both responses, none of the results were heavily influenced by outliers or participants’ age. Note that both the intuitive and informed response were part of the same model, to circumvent an inflation of Type-1 error results.

The analysis was conducted using Stan [ 80 ] called via the package brms [ 81 ] within the R environment [ 82 ]. Furthermore, we used [ 83 – 93 ] for all analyses and reporting. We compared the 95% credible intervals (CrIs) of each estimate and checked whether the CrI fell into the ROPE range. Note: while credible intervals are different from frequentist confidence intervals, the latter often incorrectly get interpreted as the former [ 74 ]. If the full CrI fell into the ROPE range, we accepted the null value (there is no effect/difference). If the CrI fell entirely outside the range, we rejected the null value (there is an effect/difference). If it overlapped, we could not make a decision given our data. To give the data more weight than our own assumptions, we applied only weakly informative priors on our parameter estimates: all intercepts/cutoffs and all parameter slopes β used a Normal (0, 4) prior.

Results study 1

This section presents results for H1a/b/c and H2a/b/c, which are based on our main analysis of the participants’ intuitive response . Subsequently, we briefly report the results of our exploratory analysis, using the participants’ informed response .

Identity badge versus no badge (H1)

Our first hypotheses (H1a/b/c) claimed that Tweets with an identity verification badge would yield the same sharing intentions and perceived source and message credibility as Tweets without a badge. The output of the analyses can be found in Table 1 . Because interpreting main effects in the presence of an interaction can be misleading, we looked at both the main (averaged) effect and each context individually.

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Results are presented averaged over contexts and for both contexts individually.

https://doi.org/10.1371/journal.pone.0302323.t001

The intuitive viewing yielded inconclusive results regarding the effects of identity badges on sharing likelihood. Next, it remained inconclusive whether source credibility is affected by an identity badge in the household context. However, for the medical context and the average of these contexts, the identity badge substantially increased source credibility. Lastly, message credibility only conclusively increased in the medical context. The household context and the average of the contexts yielded no conclusive results on message credibility. None of these findings support H1a/b/c.

Next, we explored how information about badge interpretation affected user behaviour. Somewhat different results were obtained for this informed viewing, as now identity badges increased source and message credibility for both contexts as well as their averages. Sharing intentions also increased, yet only in the medical context and for the average of the contexts.

Credential badge vs. no badge (H2).

The credential badges were expected to help people make better credibility judgements. Hence, our second set of hypotheses stated verified credential increases credibility and sharing intentions, but only if the verified credential is relevant to the context (H2a/b/c). We thus compare the effects of a medical credential badge in the relevant (medical) against the irrelevant (household) context. Like the identity badges, the novel credential badges are evaluated with respect to sharing intentions and perceived source and message credibility. The results of the analysis are displayed in Table 2 .

https://doi.org/10.1371/journal.pone.0302323.t002

When the credential badge was context-relevant, the badge increased sharing intentions as well as source and message credibility in the intuitive viewing. Yet, when it was irrelevant to the context, the results show the presence of a virtual lab coat effect, as both source and message credibility was inflated by the medical credential badge regardless of the context. As a credential verification badge does not only increase source credibility when used in the relevant context, we cannot reject the null hypotheses of H2a/b. Whether this virtual lab coat effect applies to sharing likelihood remains uncertain, leaving us unable to reject the null hypothesis of H2c. Still, for the informed viewing, the credential badge increased all measurements. The exploratory analysis thus evidently shows a virtual lab coat effect.

Discussion study 1

Study 1 examined the impact of identity and credential verification badges on source credibility, message credibility, and sharing intentions. It was investigated whether identity badges affect user perceptions, expecting no effects (H1). Contrary to prior research [ 39 , 42 , 94 ], identity badges increased source and message credibility for medical posts in the initial viewing, suggesting a conflation of source authenticity and message credibility. These findings on identity verification are somewhat worrisome in the light of misinformation, especially given that identity verification is being made more accessible (e.g., through a subscription [ 1 , 41 ]). In the household context, however, the effects of identity badges were either inconclusive or much weaker. This may be explained by that household information could be considered as less exclusive compared to medical information. In that case, users rely less on source credibility heuristics [ 44 ].

Next, after explaining the interpretation of the badges, medical posts with identity badges yielded higher sharing intentions and perceived source and message credibility compared to posts without a badge. One explanation for the informed viewing findings is that the badges may have triggered users that saw no badge to become more suspicious of deceptive content or sources, leaving their initial assumption of truthful communication [ 95 ].

More conclusive findings were observed for credential badges, often larger in effect size compared to the effects of identity badges. Credential badges were expected to increase credibility perceptions and sharing intentions, but only if the verified credential was relevant to the message contents (H2). However, in the intuitive viewing, any posts by sources with verified medical credentials were perceived as more credible and more likely to be shared, even if the credential was irrelevant to the post. Therefore, we evidently show the presence of a “virtual lab coat effect”. This suggests that a medical credential lends general credibility, raising concerns regarding the potential of credential verification badges to boost misinformation. The same, even stronger effects were observed for the informed viewing.

Overall, the results show that source credibility increased when authors had identity or credential verification badges, regardless of the relevance of present verified credentials. This expands on research by Alhayan et al. [ 69 ], whose participants mentioned they found a source more credible if they had topic-relevant experience or a blue badge. Moreover, this confirms previous findings that any additional information about an online author affects source credibility, as previously researched for online reviews [ 71 – 73 ]. Moreover, we show that source credibility cues affect message credibility, contradicting previous research suggesting that source information has no relationship with the perceived accuracy of online news [ 96 ].

One limitation to this experiment is that the post in the medical context contained inaccurate information (see [ 97 ]). Though we do not expect participants to have been aware of this, this breaks the underlying assumption that experts generally communicate accurate information. Next, the source credibility ratings might have biased the message credibility ratings, as they were posed in this order in the survey. Similarly, posing the media literacy and trust questions prior to the intuitive viewing could have biased the participants, raising suspicion of possible deception (e.g., [ 95 ]). These limitations will be addressed in study 2.

The second study aimed to reproduce the results of study 1. Another goal of this second study was to verify whether the observed effects of source credibility cues on Twitter generalise to a more generic social media setting. Namely, many other social media platforms also use identity verification badge, e.g., Instagram [ 40 ], Facebook [ 41 ], and YouTube [ 98 ]. These platforms are also obliged to introduce tools that empower users to more accurately determine the credibility of content [ 32 ]. It is worth noting that this experiment took place in December 2022, after the upheaval regarding Twitter’s identity-based verification badges subscription policy (e.g., [ 1 ]).

Though study 2 aimed to test the robustness of the findings in study 1, the results of the first study imply that both badge designs can stimulate reasoning errors with possibly dangerous implications towards misinformation. Therefore, study 2 also introduced a new, different type of authenticity marker: the credential signature . This signature communicates the same information as credential verification badge, with one exception: the signature indicates expertise rather than employment. Hence, the author’s role within the organisation cannot be disputed, which was a limitation of study 1. An example of a generic social media post with a signature can be found in S2 Fig .

Though the information conveyed by the signature is fairly similar, the design of social media posts can affect user’s credibility perceptions (e.g., [ 12 , 37 ]). The credential signature is expected to reduce the emergence of virtual lab coat effects compared to its badge counterpart. Namely, the signature is placed below the message and therefore likely to be read after the message. This way, the signature information is more likely to be considered in the context of the message, as the context is now already apparent. Verified credentials irrelevant to the message content could thus trigger some form of expectancy violation heuristic [ 52 ], where messages with an irrelevant signature should not increase the source and content credibility.

In sum, study 2 investigated how identity and credential verification badges generalise to other platforms and compare to credential signatures. As with study 1, the designs are compared on their effects on credibility judgements and sharing intentions. Moreover, the experiment started with a round of intuitive evaluations, followed by explanation on how to interpret the badges and signatures. Consequently, we explored how this explanation affected the credibility and sharing judgements. Based on results of our previous experiment, we hypothesised the following:

• Hypotheses 3a/b/c : People are more inclined to find social media posts with an identity verification badge more credible (a: source credibility, b: message credibility) and to share these posts (c: likelihood of sharing), compared to posts without a badge.
• Hypotheses 4a/b/c : People are more inclined to find social media posts with a credential verification badge more credible (a: source credibility, b: message credibility) and to share these posts (c: likelihood of sharing), compared to posts without a badge, also if the credential is irrelevant to the context.
• Hypotheses 5a/b/c : People are more inclined to find social media posts with social media posts with a credential signature more credible (a: source credibility, b: message credibility) and to share these posts (c: likelihood of sharing), compared to posts without a badge, but only if the credential is relevant to the context.

Method study 2

The methodology used in our second study replicated exactly that of study 1, with exception for of the details listed below. Before running the experiment, we preregistered the sample size estimation, hypotheses, and planned statistical analyses. The preregistration and all used stimuli, the survey, data, and analysis scripts are available on the Open Science Framework ( https://osf.io/y2uew/ ).

The second study was also approved by the Ethics Committee of Social Sciences at Radboud University. The study was approved as part of the light track (i.e., involving minimal risk). The light track ethical approval used reference number ECSW-LT-2022–12-12-24077. Lastly, as with study 1, participants expressed informed consent through an electronic form prior to the experiment.

The study used a 2x5 between-subjects design. For the first independent variable (social media post context), the household context was replaced with a cybersecurity context, to represent a more exclusive topic and more clearly signal irrelevance of medical expertise. The second independent variable, source credibility cue, now contained five conditions: no badge or signature (control condition), an identity-based verification badge, an credential-based badge showcasing a medical credential, and a credential-based signature showcasing medical expertise. Finally, a credential-based signature showcasing cybersecurity expertise was included to check whether this yields similar effects compared to the medical signature. As this was indeed the case, it will not be reported any further.

As mentioned, the post used for the medical context in study 1 contained false information (see [ 97 ]). This was changed to accurate information: the medical context for study 2 thus read “Screening for asymptomatic atrial fibrillation increases the chance of preventing a stroke in elderly patients”, based on medical literature [ 99 ]. Next, the cybersecurity context media post used a similar framing, and said “The use of connected vehicular cloud computing increases the chance of successful cyber attacks in connected cars”, based on cybersecurity literature [ 100 ]. An overview of the social media posts in the medical context are displayed in S3 Fig (the other stimuli are available on Open Science Framework).

On 16 December 2022, we recruited a total of N = 590 participants (based on a G*power analysis) through Prolific, using identical sampling criteria to the first study (an age between 18 and 65; current living area in the UK). Participants were compensated with £1.2 for successfully completing the study, which was estimated to take around 8 minutes (£9.00/h). Similar to study 1, a pilot study with 26 people was conducted prior to the main data collection.

Due to sudden technical issues with the server hosting the survey, the survey took participants on average longer than expected ( M = 11.29, SD = 9.32 minutes). The participants received an additional £1.05 to compensate for the issues. We performed an exploratory analysis on the subset of participants who finished the survey within 10 minutes, i.e., likely without technical issues ( N = 297). In almost all cases, this analysis yielded similar results and effect sizes compared to our main analysis, suggesting the technical difficulties did not affect our results. We thus only report our main analysis.

The sample of 590 participants contained 34 participants with unusable data, 44 participants who did not pass the attention checks. Of these 44, 34 did not remember the contents of the social media post correctly. The remaining 10 thought they recognised the fictional author of the social media account. Hence, they were excluded from analysis. As stated in the pre-registration, we excluded all participants that took over 25 minutes to complete the survey (22 in total), leaving the data of 491 participants for analysis. This population had a mean age of 39.65 ( SD = 11.43).

In study 1, the background information questions also contained items on trust in medical organisations and media literacy. Yet, these items were postponed to the end of the survey to prevent accidental priming of expecting deception (e.g., [ 95 ]). Similarly, study 2 addressed message credibility prior to source credibility, to circumvent the participants considering the credibility of the message while judging the credibility of the author.

Next, most participants did not correctly remember which badge they had seen in study 1 (62.0%), which is subject to noise as many participants may have guessed. Hence, the answer options to this question were changed by visually supporting the participant, with the aim of reducing noise due to guessing. Namely, instead of displaying an example of the badge, we showed all possible social media posts (using the context the participant was assigned to). Also, the participants were asked to indicate whether they had guessed which post they saw. Now, most participants correctly recognised which post they had seen (72.9%), and the remaining group either guessed or incorrectly recalled. Moreover, this attention check was also included after the second time the participants saw the social media post. For both attention checks, we performed exploratory analyses including only the participants who correctly recalled the source credibility cue. These analyses yielded very similar results to the main analysis in almost all cases. The same holds for the exploratory analyses including the remaining participants. Therefore, they will not be discussed in more detail.

Lastly, the explanation on the designs tested in the survey and their meaning was revised. Specifically, it no longer referred to Twitter, and the text was supported with additional imagery including example posts rather than just badges. The full explanation can be found in S2 File .

Study 2 used the same three background information measures. However, instead of just Twitter use, social media use was assessed using two 10-point Likert-scales, where 1 means Never and 10 Very often (based on Kim et al. [ 101 ]). The two statements addressed how often the participant uses social networking sites (e.g., Facebook) and micro-blogging websites (e.g., Twitter) to get news. For the analyses, we used the average of these two measures ( r = .32, M = 6.30, SD = 2.61). For medical trust, we used the same statement and answer options, which yielded slightly lower results than study 1 ( M = 2.79, SD = 0.67). Media literacy was measured using the same scale [ 75 ], also yielding slightly lower results than in study 1 ( M = 5.29, SD = 0.85), α = .81.

The sharing likelihood scale was increased to a 7-point Likert-scale aiming to increase granularity and consistency with the other outcome levels. Moreover, the statement was reformulated to “ Imagine that you were with a couple of acquaintances last week. You had a conversation about the topic of the social media post you just saw. How likely are you to share the information in the social media post with them? ”, creating a more explicit context for sharing the post. This framing also includes in-person sharing of information, possibly yielding more granularity in results as people tend not to re-share posts on social media (e.g., [ 56 , 58 ]).

The message credibility scale was revised to resemble the scale by Appelman & Sundar [ 64 ] more accurately. Namely, participants now rated the message using the adverbs ‘accurate’, ‘authentic’ and ‘believable’, using a 7-point Likert scale ranging from Describes very poorly (1) to Describes very well (7). This scale showed very good internal consistency (raw α = .90).

Lastly, source credibility was also measured with a 7-point Likert-scale, both for survey consistency and to stick closer to the original source of the source credibility scale [ 102 ]. This scale scored good internal consistency (raw α = .82). As in study 1, though dropping the item ‘biased’ would increase α by .11, it was kept for the same reasons.

Results study 2

This section presents the results for H3 to H5. As with the first study, the main analysis was based on the participants’ intuitive response . The informed responses, i.e., ratings after the second viewing where the participant had information about the various badges, are reported as exploratory analysis.

Identity badge versus no badge (H3).

As we aimed to replicate the results of study 1 in a more general context, our third hypothesis claimed that people are more inclined to share social media posts with an identity verification badge, and to find these posts and their source more credible compared to posts without a badge. The posterior distributions with mean, standard-deviation and 95% CrI of the difference between the identity badge and no badge for the three outcome variables are listed in Table 3 .

https://doi.org/10.1371/journal.pone.0302323.t003

For the intuitive viewing, it remained inconclusive whether identity badges increase sharing intentions or credibility judgements. The null hypotheses of H3a/b/c can thus not be rejected, as no effects could be detected in both contexts. Additionally, we explored how sharing and credibility judgements were affected by an explanation on the interpretation of the badges and signature. For this informed viewing, it also remained inconclusive whether identity badges increase sharing intentions. In contrast, source and message credibility increased in both contexts as well as their average. The account holder and their message were thus thought to be more credible after the explanation, showing a conflation between source authenticity and message credibility.

Credential badge versus no badge (H4).

To investigate our fourth set of hypotheses, we compared social media posts with an credential verification badge to posts without a badge in terms of their effects on sharing intentions and source and message credibility. It was hypothesised that these measurements increase for posts with an credential verification badge, regardless of whether the credential is relevant to the context. For the analysis, we considered the medical credential verification badge. The results of our analysis are listed in Table 4 .

https://doi.org/10.1371/journal.pone.0302323.t004

For the intuitive viewing, a relevant credential badge increased the credibility of a source. However, it remains inconclusive how source credibility is affected when the badge is context irrelevant. Moreover, the effects of a credential badge on sharing likelihood and message credibility also remain inconclusive. Hence, the null hypotheses of H4a/b/c could not confidently be rejected, as the data does neither illustrate an increase in the relevant context nor the absence of a virtual lab coat effect. Next, for the informed ratings, a relevant credential badge yielded increased sharing intentions. However, it remains unclear whether this effect also occurs in the context irrelevant setting. Yet, the credential badge increased the informed source and message credibility ratings, regardless of its relevance to the message content.

Credential signature versus no signature (H5).

The final set of hypotheses claimed that posts with a signature increase sharing intentions and source and message credibility judgements compared to posts without a signature, but only if this credential information is relevant to the context. The parameters of the posterior distributions are listed in Table 5 .

https://doi.org/10.1371/journal.pone.0302323.t005

Similar to the credential badge, the credential signature yields an increase in source credibility when the verified credential is context relevant. Yet, it remains unclear whether this effect on source credibility also occurs when the credential is context irrelevant. Moreover, the data yields no definitive conclusions on the effects of credential signature on sharing likelihood and message credibility. In sum, none of null hypotheses of H5a/b/c can reliably be rejected. Lastly, for the informed ratings, a source with a credential signature was perceived as more credible regardless of the relevance of the credential within the context. Next, relevant credential signatures increased sharing intentions and message credibility. Yet, it remains inconclusive whether this also holds for credential signatures in irrelevant contexts.

Discussion study 2

The goal of study 2 was to test whether the results of study 1 generalise to a broader social media context. Moreover, it introduced a credential-based signature, as a potential solution to the virtual lab coat effects of the credential-based verification badge observed in study 1. In contrast to study 1, it remained inconclusive whether there exists an intuitive relationship between verified identity badges and source and message credibility, or sharing intentions. Therefore, H3 was not supported. However, the informed viewing data provides more support for the conflation of source authenticity and message credibility. Namely, after the explanation on how to interpret the badges and signature, participants rated posts by unknown authors with a verified identity as more credible, suggesting an incorrect reasoning shortcut. Note, however, that the difference in credibility and sharing intentions after explanation often stemmed from lower ratings for posts from authors without any verified information. This holds for all contrasts.

The hypotheses on credential-based badges (H4) were also not supported, contrary to results of study 1. It was expected that credential-based badges increased perceived source and message credibility as well as sharing intentions, regardless of the whether the credential information was context relevant. Yet, the credential-based verification badge only conclusively increased source credibility when relevant credential information was verified. It thus remains inconclusive whether a virtual lab coat effect occurs for the intuitive viewing. However, after explaining the interpretation of the badges and signature, the virtual lab coat effect was evident. Even if an unknown author’s verified credential information badge was irrelevant to the context, their message was perceived as more credible. Hence, although the effect size is much larger in the relevant context, a verified medical credential badge still lends credibility to irrelevant contexts.

The credential-based signatures were expected to increase perceived source and message credibility as well as sharing intentions. Yet, only when the credential information was context relevant (H5). The effects of the credential-based signature were very similar to its badge counterpart. However, there are two notable differences. First, the effect size for source credibility during the intuitive viewing was much higher for relevant signatures than for relevant badges. Second, it remains inconclusive whether the informed viewing yields a virtual lab coat effect. An explanation for this is the novelty of the design, which might have led participants to process the signature more elaborately (e.g., [ 103 ]).

The similarity between credential-based signatures and badges contradicts previous studies that suggest source cues are less impactful when they appear after the message [ 104 , 105 ]. Yet, those studies included participants motivated to think critically, which is not necessarily the case in this study. Moreover, the similarity in results between credential-based badges and signatures is particularly interesting, as the signatures conveyed more information than their badge counterpart (ensuring the author works as medical expert instead of, e.g., administrator). Hence, though this was listed as a limitation in study 1, it seems unlikely it affected participants’ reasoning. On the other hand, the more explicit medical expertise could explain the larger effect size of the signature compared to the badge variant in the intuitive viewing.

The results of study 2 provide less support for our previous finding that verified information about an unknown source increases their credibility. Namely, though this notion held for the informed viewing, the intuitive viewing only conclusively yielded higher author credibility in case of relevant verified credential information. For identity-based verification or irrelevant credential information, no definitive conclusions could be drawn about their relationship with source credibility.

Notably, study 1 and study 2 provide somewhat different results, especially for the intuitive viewing. This discrepancy can likely be attributed to the more generic style the posts were presented in. Alternative explanations are small changes in methodology, and possible associations with the turbulence regarding Twitter’s identity-based verification badges around the time the experiment was conducted (e.g., [ 1 ]).

General discussion

To counter online misinformation, this paper proposed to empower users through online platforms with tools to determine the credibility of social media posts more accurately. Specifically, we suggested to focus on source credibility cues, as users heavily assess the credibility of content through the lens of source credibility [ 35 ]. As source information, social media platforms commonly employ an identity verification badge, verifying an authors identity. In addition to such verification badges, this paper investigated the novel possibility of credential verification on social media. Though verifying credentials and identity are both technically viable [ 2 ], it was unclear how they affected credibility judgements and sharing behaviour. This was investigated through two experimental studies ( N = 525; N = 590), where participants rated a social media post with respect to credibility and sharing likelihood. Participants rated a post both before and after explanation of how to interpret the verified source information cues.

Before explanation, participant behaviour was unpredictable in a general social media setting. Namely, in most cases, both identity and credential verification methods did not show a clear absence or presence of effects on sharing intentions, and source or message credibility. Our results thus question the omnipresence of verified identity markers on social media platforms, as they do not seem to increase source credibility intuitively. However, specifically in an environment simulating Twitter, medical messages from unknown sources seemed more credible if the source had verified their identity or medical credential. Whereas a verified medical credential is a useful heuristic for judging the credibility of medical messages, a verified identity absolutely is not. Inflated medical message credibility in case of a verified identity is a worrisome finding, given that users increasingly use social media for medical information [ 7 , 8 ], and that verifying an identity is publicly available as a subscription [ 1 ]. This result likely applies to other messages of which the user has no intuition about its credibility [ 44 ].

However, most reasoning errors occurred after the participants were informed about how to interpret the verified source information cues. In both the Twitter setting as the general social media setting, participants often rated posts with verified source information cues as substantially more credible compared to posts without these cues after this explanation. The results surfaced two prominent reasoning errors in participants. First, participants conflated source authenticity and message credibility. Second, participants often found messages from sources with a verified credential more credible, even if this credential was irrelevant to the message. It thus seems that verifying information about an unknown source can increase the source’s credibility, as also suggested by previous studies [ 71 – 73 ]. Generally, verified source information is a good heuristic for source credibility. Yet, it becomes problematic when irrelevant verified source information (e.g., their identity, or irrelevant credential) inflates the credibility of the message. In its currently presented forms, verified source information thus seems to be more able to boost misinformation rather than to hinder it.

As most reasoning errors occurred after informing participants about the verified source information cues and what they mean, purely explaining how to interpret them seems insufficient to overcome the prevalence of these reasoning errors. In other words, this simplest form of a (news) media literacy intervention did not have the anticipated effect. This calls into question to what extent such low profile interventions are useful in combating misinformation, and subsequently how media literacy interventions should look like to be effective. Past research (e.g., [ 106 , 107 ]) indicates that more sophisticated interventions (e.g., integrating several strategies and/or featuring multiple messages) are promising. However, it is crucial to note that our theoretical suggestions are based on exploratory research, and we refrain from making definitive conclusions. Further investigation is required, particularly when it comes to the existence of negative side-effects of exposure to interventions [ 107 ], as also found in the current study.

Lastly, both studies are mostly inconclusive on the relationship between verified source information and intentions to share their posts. A likely explanation for this finding is that credibility and sharing are not necessarily related (e.g., [ 29 , 56 , 57 ]), and that sharing intentions have been found to depend on factors uncontrolled for, e.g., someone’s motivation to protect their self-image [ 60 ], or the novelty of the information [ 54 ]. Furthermore, it is hard to detect effects on sharing, as only few people tend to often re-share information by others on social media (e.g., [ 56 , 58 ]).

Limitations and future work

Some caveats to these results are to be noted. First, to minimise cultural noise, our participants were all based in the UK. However, cultural differences can also affect credibility processing (e.g., [ 38 ]). Moreover, some participants might have had prior knowledge about the social media posts contents. Though prior knowledge was assumed to be rare and distributed equally among conditions, it might still have affected their credibility judgements (e.g., [ 44 ]). Hence, future research could investigate how verified source information affects user behaviour for users from a wider variety of cultural and educational backgrounds.

This paper varied the presentation of (verified) source information and its effects on user behaviour, and the relevance of these cues to the message content (i.e. relevant or irrelevant expertise). However, another interesting experimental variation would be to vary information accuracy within the experiments. Using such a ground-truth is common practice in misinformation research. We purposely left this variation out considering that the ‘truth’ is often emergent and subjective, but future work could certainly experiment with more objective truths or falsehoods.

Furthermore, the stimuli contained rather neutral, scientific topics rather than polarising topics. This circumvents potential motivated reasoning where users pay less attention to source cues and more to message contents [ 108 ]. Still, sources affect message credibility as, e.g., messages from sources aligning with users’ political bias are perceived as more credible [ 109 ]. Yet, further research is needed to understand how verified source information of unknown sources affects content evaluation in polarising contexts. Additionally, it must be noted that scientific content can increase source credibility [ 69 ]. Therefore, another interesting angle for future research is how less scientific content (e.g., opinions, experiences) are evaluated in case verified source information is present.

Next, a potential downside of verifying credentials is its implication on anonymity. By verifying additional information, one’s personal data is shared on the internet. Users might be inclined to disclose more data (than they might have self-disclosed in their account biography) to gain credibility, without considering the impact on their privacy. Therefore, although verified credentials could improve credibility judgements in theory, the observed virtual lab coat effects and privacy risks associated with this technology underline it is inadequate to deploy it on social media in the form featured in this paper. Still, verified credentials could be employed in contexts less cognitively demanding than social media. An example of such a context where source credibility is important is Wikipedia (see, e.g., [ 110 ]).

Lastly, the experimental survey presented the sharing and credibility items all in the same fixed order. Though this order was fixed to circumvent specific priming effects (sharing intentions could be primed by credibility judgements), other priming effects may have occurred (e.g., sharing intentions priming credibility judgements for internal consistency). Therefore, the results of our study would be more robust if the survey included a randomised presentation order of these items instead.

With the introduction of social media, platforms hardly have any control over what users can or cannot say (e.g., [ 5 ]), making way for misinformation. Yet, determining the credibility of messages can be troublesome for users (e.g., [ 10 ]). Therefore, social media platforms should strive to make users smarter in what they believe. A good starting point is a more accurate perception of the credibility of the message’s source (e.g., [ 36 ]). We have investigated how verified source information influences credibility judgements and sharing intentions. We examined (1) an existing implementation, i.e., verified source identity, and (2) a potential new solution, i.e., verified credentials of the source.

Without providing users with knowledge on how to interpret the verified source information cues, the effects of these cues were mostly unpredictable. Yet, after explanation, users were prone to two reasoning errors. First, they conflated source authenticity and message credibility. Second, messages from sources with a verified credentials were more credible, regardless of whether this credentials was context relevant (i.e., virtual lab coat effect). The prevalence of these two reasoning errors seem especially harmful in the light of misinformation. Hence, future research should investigate how different solutions can be more effective in empowering users to more accurately determine the credibility of social media posts. Furthermore, alternative implementations or contexts to implement credentials verification should be explored, as it a promising development in the area of online credibility.

For full transparency, it must be noted that during revision of the paper, all hypotheses were slightly reworded to clarify the distinction between credibility judgements and sharing intentions, based on that these decisions are not necessarily related (e.g., [ 29 , 56 , 62 ]). This theoretical distinction did not affect how we conducted our analyses. One exception to this is the reformulation of hypothesis 4. Namely, the pre-registered hypothesis stated that credential-based verification badges do not affect the credibility judgements and sharing intentions with respect to posts without a badge. Yet, given the results from study 1, the hypothesis should have stated an increase of these factors.

Supporting information

S1 fig. medical context stimuli study 1..

An overview of the stimuli used in the medical context in study 1. Here, the medical signature (c) is considered a relevant attribute, as it is displayed in the medical context. Note that this figure is for illustrative purposes only for two reasons. First, the profile photo is similar but not identical to the one used in the experiment. While the original photo was obtained from Unsplash, this illustrative profile picture was AI-generated through https://thispersondoesnotexist.com . Second, this Figure differs from the original stimulus in that it features a self-designed version of a Tweet for legal reasons.

https://doi.org/10.1371/journal.pone.0302323.s001

S2 Fig. Credential signature on generic social media post.

Example social media post including a credential signature. Note that this image was used as support image in explaining the meaning of the various badge and signature designs. Note that, again, this figure is for illustrative purposes only, as the profile photo is similar but not identical to the one used in the experiment. While the original photo was obtained from Unsplash, this illustrative profile picture was AI-generated through https://thispersondoesnotexist.com .

https://doi.org/10.1371/journal.pone.0302323.s002

S3 Fig. Medical context stimuli study 2.

An overview of the stimuli used in the medical context in study 2. Here, the medical signature (d) is considered a relevant credential, whereas the cybersecurity signature (e) is considered irrelevant. Naturally, the opposite holds in case of the cybersecurity context (where only the message contents are replaced). Note that, again, this figure is for illustrative purposes only, as the profile photo is similar but not identical to the one used in the experiment. While the original photo was obtained from Unsplash, this illustrative profile picture was AI-generated through https://thispersondoesnotexist.com .

https://doi.org/10.1371/journal.pone.0302323.s003

S1 File. Explanation of the designs used in study 1.

This text was used to explain to the participants how to interpret the different possible badges included in the first experiment. It was explained that a source could have either no badge, an identity-based badge, or a credential-based badge. The text further explained how to interpret the badges, namely as verified identity and verified credential respectively. Lastly, this File differs from the original stimulus in that it features a self-designed version of the Twitter verification icon for legal reasons.

https://doi.org/10.1371/journal.pone.0302323.s004

S2 File. Explanation of the designs used in study 2.

This text was used to explain to the participants how to interpret the different possible badges included in the second experiment. It was explained that a source could have either no badge, an identity-based badge, a credential-based badge, or signed their message using a credential-based signature. The text further explained how to interpret the badges and signature, namely as verified identity and verified credential respectively. Note that, again, this figure is for illustrative purposes only, as the profile photo is similar but not identical to the one used in the experiment. While the original photo was obtained from Unsplash, this illustrative profile picture was AI-generated through https://thispersondoesnotexist.com .

https://doi.org/10.1371/journal.pone.0302323.s005

Acknowledgments

We would like to thank Lian for helping with creating the stimuli for study 2. Next, we thank Bernard van Gastel, Koen Verdenius, Marie-Sophie Simon, Emma Schipper, and Yelyzaveta Markova for their inspiring work and ideas. We thank Bart Jacobs for discussion and originally posing the idea of using verified credentials to guarantee authenticity of information in the context of misinformation. We thank our reviewers for their thoughtful remarks and suggestions.

Lastly, we note that we have used the Artficial Intelligence tool https://thispersondoesnotexist.com to generate profile pictures of non-existing people in S1 – S3 Figs, and S2 File . We regenerated portraits until the model yielded a portrait similar to the profile picture used in the study’s stimuli, which we could not include for legal reasons.

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Social Media Adoption, Usage And Impact In Business-To-Business (B2B) Context: A State-Of-The-Art Literature Review

• Open access
• Published: 02 February 2021
• Volume 25 , pages 971–993, ( 2023 )

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• Yogesh K. Dwivedi 1 ,
• Elvira Ismagilova 2 ,
• Nripendra P. Rana 2 &
• Ramakrishnan Raman 3  

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Social media plays an important part in the digital transformation of businesses. This research provides a comprehensive analysis of the use of social media by business-to-business (B2B) companies. The current study focuses on the number of aspects of social media such as the effect of social media, social media tools, social media use, adoption of social media use and its barriers, social media strategies, and measuring the effectiveness of use of social media. This research provides a valuable synthesis of the relevant literature on social media in B2B context by analysing, performing weight analysis and discussing the key findings from existing research on social media. The findings of this study can be used as an informative framework on social media for both, academic and practitioners.

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1 Introduction

The Internet has changed social communications and social behaviour, which lead to the development of new forms of communication channels and platforms (Ismagilova et al. 2017 ). Social media plays an important part in the digital transformation of businesses (Kunsman 2018 ). Digital transformation refers to the globally accelerated process of technical adaptation by companies and communities as a result of digitalisation (Sivarajah et al. 2019 ; Westerman et al. 2014 ). Web is developed from a tool used to provide passive information into the collaborative web, which allows and encourages active user engagement and contribution. If before social networks were used to provide the information about a company or brand, nowadays businesses use social media in their marketing aims and strategies to improve consumers’ involvement, relationship with customers and get useful consumers’ insights (Alalwan et al. 2017 ). Business-to-consumer (B2C) companies widely use social media as part of their digital transformation and enjoy its benefits such as an increase in sales, brand awareness, and customer engagement to name a few (Barreda et al. 2015 ; Chatterjee and Kar 2020 ; Harrigan et al. 2020 ; Kamboj et al. 2018 ; Kapoor et al. 2018 ).

From a marketing and sales research perspective, social media is defined as “the technological component of the communication, transaction and relationship building functions of a business which leverages the network of customers and prospects to promote value co-creation” (Andzulis et al. 2012 p.308). Industrial buyers use social media for their purchase as they compare products, research the market and build relationships with salesperson (Itani et al. 2017 ). Social media changed the way how buyers and sellers interact (Agnihotri et al. 2016 ) by enabling open and broad communications and cooperation between them (Rossmann and Stei 2015 ). Social media is an important facilitator of relationships between a company and customers (Agnihotri et al. 2012 ; Tedeschi 2006 ). Customers are more connected to companies, which make them more knowledgable about product selection and more powerful in buyer-seller relationships (Agnihotri et al. 2016 ). Social media also helps companies to increase business exposure, traffic and providing marketplace insight (Agnihotri et al. 2016 ; Stelzner 2011 ). As a result, the use of social media supports business decision processes and helps to improve companies’ performance (Rossmann and Stei 2015 ).

Due to digitalisation customers are becoming more informed and rely less on traditional selling initiatives (Ancillai et al. 2019 ). Buyers are relying more on digital resources and their buying process more often involves the use of social media. For example, in the research B2B buyer survey, 82% of buyers stated that social media content has a significant impact on the purchase decision (Ancillai et al. 2019 ; Minsky and Quesenberry 2016 ). As a result, these changes in consumer behaviour place high pressure on B2B salespeople and traditional sales companies (Ancillai et al. 2019 ). By using evidence from major B2B companies and consultancy report some studies claim that social media can be applied in sales to establish effective dialogues with buyers (Ancillai et al. 2019 ; Kovac 2016 ; McKinsey and Company 2015 ).

Now, business-to-business (B2B) companies started using social media as part of their digital transformation. 83% of B2B companies use social media, which makes it the most common marketing tactic (Pulizzi and Handley 2017 ; Sobal 2017 ). More than 70% of B2B companies use at least one of the “big 4” social media sites such as LinkedIn, Twitter, Facebook and YouTube. Additionally, 50% of the companies stated that social media has improved their marketing optimization and customer experience, while 25% stated that their revenue went up (Gregorio 2017 ; Sobal 2017 ). Even though B2B companies are benefitting from social media used by marketers, it is argued that research on that area is still in the embryonic stage and future research is needed (Salo 2017 ; Siamagka et al. 2015 ; Juntunen et al. 2020 ; Iannacci et al. 2020 ). There is a limited understanding of how B2B companies need to change to embrace recent technological innovations and how it can lead to business and societal transformation (Chen et al. 2012 ; Loebbecke and Picot 2015 ; Pappas et al. 2018 ).

The topic of social media in the context of B2B companies has started attracting attention from both academics and practitioners. This is evidenced by the growing number of research output within academic journals and conference proceedings. Some studies provided a comprehensive literature review on social media use by B2B companies (Pascucci et al. 2018 ; Salo 2017 ), but focused only on adoption of social media by B2B or social media influence, without providing the whole picture of the use of social media by B2B companies. Thus, this study aims to close this gap in the literature by conducting a comprehensive analysis of the use of social media by B2B companies and discuss its role in the digital transformation of B2B companies. The findings of this study can provide an informative framework for research on social media in the context of B2B companies for academics and practitioners.

The remaining sections of the study are organised as follows. Section 2 offers a brief overview of the methods used to identify relevant studies to be included in this review. Section 3 synthesises the studies identified in the previous section and provides a detailed overview. Section 4 presents weight analysis and its findings. Next section discusses the key aspects of the research, highlights any limitations within existing studies and explores the potential directions for future research. Finally, the paper is concluded in Section 6 .

2 Literature Search Method

The approach utilised in this study aligns with the recommendations in Webster and Watson ( 2002 ). This study used a keyword search-based approach for identifying relevant articles (Dwivedi et al. 2019b ; Ismagilova et al. 2020a ; Ismagilova et al. 2019 ; Jeyaraj and Dwivedi 2020 ; Williams et al. 2015 ). Keywords such as “Advertising” OR “Marketing” OR “Sales” AND TITLE (“Social Media” OR “Web 2.0” OR “Facebook” OR “LinkedIn” OR “Instagram” OR “Twitter” OR “Snapchat” OR “Pinterest” OR “WhatsApp” OR “Social Networking Sites”) AND TITLE-ABS-KEY (“B2B” OR “B to B” OR “Business to Business” OR “Business 2 Business”) were searched via the Scopus database. Scopus database was chosen to ensure the inclusion of only high quality studies. Use of online databases for conducting a systematic literature review became an emerging culture used by a number of information systems research studies (Dwivedi et al. 2019a ; Gupta et al. 2019 ; Ismagilova et al. 2020b ; Muhammad et al. 2018 ; Rana et al. 2019 ). The search resulted in 80 articles. All studies were processed by the authors in order to ensure relevance and that the research offered a contribution to the social media in the context B2B discussion. The search and review resulted in 70 articles and conference papers that formed the literature review for this study. The selected studies appeared in 33 separate journals and conference proceedings, including journals such as Industrial Marketing Management, Journal of Business and Industrial Marketing and Journal of Business Research.

3 Literature Synthesis

The studies on social media research in the context of B2B companies were divided into the following themes: effect of social media, adoption of social media, social media strategies, social media use, measuring the effectiveness of use of social media, and social media tools (see Table 1 ). The following subsections provide an overview of each theme.

3.1 Effect of Social Media

Some studies focus on the effect of social media for B2B companies, which include customer satisfaction, value creation, intention to buy and sales, building relationships with customers, brand awareness, knowledge creation, perceived corporate credibility, acquiring of new customers, salesperson performance, employee brand engagement, and sustainability (Table 2 ).

3.1.1 Customer Satisfaction

Some studies investigated how the use of social media affected customer satisfaction (Agnihotri et al. 2016 ; Ancillai et al. 2019 ; Rossmann and Stei 2015 ). For example, Agnihotri et al. ( 2016 ) investigated how the implementation of social media by B2B salesperson affects consumer satisfaction. Salesperson’s social media use is defined as a “salesperson’s utilization and integration of social media technology to perform his or her job” (Agnihotri et al. 2016 , p.2). The study used data from 111 sales professionals involved in B2B industrial selling to test the proposed hypotheses. It was found that a salesperson’s use of social media will have a positive effect on information communication, which will, in turn, lead to improved customer satisfaction with the salesperson. Also, it was investigated that information communication will be positively related to responsiveness, which impacts customer satisfaction.

Another study by Rossmann and Stei ( 2015 ) looked at the antecedents of social media use, social media use by B2B companies and their effect on customers. By using data from 362 chief information officers of B2B companies the study found the following. Social media usage of sales representative has a positive impact on customer satisfaction. Age has a negative effect on content generation. It seems that older salespeople use social media in passive ways or interacting with the customer rather than creating their own content. It was found that the quality of corporate social media strategy has a positive impact on social media usage in terms of the consumption of information, content generation, and active interaction with customers. Also, the expertise of a salesperson in the area of social media has a positive impact on social media usage.

3.1.2 Value Creation

Research in B2B found that social media can create value for customers and salesperson (Agnihotri et al. 2012 ; Agnihotri et al. 2017 ). Agnihotri et al. ( 2012 ) proposed a theoretical framework to explain the mechanisms through which salespeople’s use of social media operates to create value and propose a strategic approach to social media use to achieve competitive goals. The study draws on the existing literature on relationship marketing, task–technology fit theory, and sales service behavior to sketch a social media strategy for business-to-business sales organizations with relational selling objectives. The proposed framework describes how social media tools can help salespeople perform service behaviors (information sharing, customer service, and trust-building) leading to value creation.

Some researchers investigated the role of the salesperson in the value creation process after closing the sale. By employing salesperson-customer data within a business-to-business context, Agnihotri et al. ( 2017 ) analysed the direct effects of sales-based CRM technology on the post-sale service behaviors: diligence, information communication, inducements, empathy, and sportsmanship. Additionally, the study examines the interactive effects of sales-based CRM technology and social media on these behaviors. The results indicate that sales-based CRM technology has a positive influence on salesperson service behaviors and that salespeople using CRM technology in conjunction with social media are more likely to exhibit higher levels of SSBs than their counterparts with low social media technology use. Data were collected from 162 salespeople from India. SmartPLS was used to analyse the data.

3.1.3 Intention to Buy and Sales

Another group of studies investigated the effect of social media on the level of sales and consumer purchase intention (Ancillai et al. 2019 ; Itani et al. 2017 ; Salo 2017 ; Hsiao et al. 2020 ; Mahrous 2013 ). For example, Itani et al. ( 2017 ) used the theory of reasoned actions to develop a model that tests the factors affecting the use of social media by salesperson and its impact. By collecting data from 120 salespersons from different industries and using SmartPLS to analyse the data, it was found that attitude towards social media usefulness did not affect the use of social media. It was found that social media use positively affects competitive intelligence collection, adaptive selling behaviour, which in turn influenced sales performance. Another study by Ancillai et al. ( 2019 ) used in-depth interviews with social selling professionals. The findings suggest that the use of social media improves not only the level of sales but also affects relationship and customer performance (trust, customer satisfaction, customer referrals); and organisational performance (organisational selling performance and brand performance).

It was investigated that social media has a positive effect on the intention to purchase (Hsiao et al. 2020 ; Mahrous 2013 ). For instance, Mahrous ( 2013 ) by reviewing the literature on B2B and B2C companies concluded that social media has a significant influence on consumer buying behaviour.

3.1.4 Customer Relationships

Another group of studies focused on the effect of social media on customer relationships (Bhattacharjya and Ellison 2015 ; Gáti et al. 2018 ; Gruner and Power 2018 ; Hollebeek 2019 ; Iankova et al. 2018 ; Jussila et al. 2011 ; Kho 2008 ; Niedermeier et al. 2016 ; Ogilvie et al. 2018 ). For example, Bhattacharjya and Ellison ( 2015 ) investigated the way companies build relationships with customers by using responsive customer relationship management. The study analysed customer relationship management activities from Twitter account of a Canadian company Shopify (B2B service provider). The company uses Twitter to engage with small business customers, develops and consumers. Jussila et al. ( 2011 ), by reviewing the literature, found that social media leads to increased customer focus and understanding, increased level of customer service and decreased time-to-market.

Gáti et al. ( 2018 ) focused their research efforts on social media use in customer relationship performance, particularly in customer relations. The study investigated the adoption and impact of social media by salespeople of B2B companies. By using data of 112 salespeople from several industries the study found that the intensity of technology use positively affects attitude towards social media, which positively affects social media use. Intensive technology use in turn positively affects customer relationship performance (customer retention). PLS-SEM was applied for analysis.

Another study by Gruner and Power ( 2018 ) investigated the effectiveness of the use of multiple social media platforms in communications with customers. By using data from 208 large Australian organisations, the paper explores how companies’ investment in one form of social media impacts activity on another form of social media. A regression analysis was performed to analyse the data. It was found that widespread activities on LinkedIn, Twitter and YouTube have a negative effect on a company’s marketing activity on Facebook. Thus, having it is more effective for the company to focus on a specific social media platform in forming successful inter-organisational relationships with customers.

Hollebeek ( 2019 ) proposed an integrative S-D logic/resource-based view (RBV) model of customer engagement. The proposed model considers business customer actors and resources in driving business customer resource integration, business customer resource integration effectiveness and business customer resource integration efficiency, which are antecedents of business customer engagement. Business customer engagement, in turn, results in business customer co-creation and relationship productivity.

Niedermeier et al. ( 2016 ) investigated the use of social media among salespeople in the pharmaceutical industry in China. Also, the study investigated the impact of social media on building culturally specific Guanxi relationships-it involves the exchange of factors to build trust and connection for business purpose. By using in-depth interviews with 3 sales managers and a survey of 42 pharmaceutical sales representatives that study found that WeChat is the most common social media platform used by businesses. Also, it was found to be an important tool in building Guanxi. Future studies should focus on other industries and other types of cultural features in doing business.

Ogilvie et al. ( 2018 ) investigated the effect of social media technologies on customer relationship performance and objective sales performance by using two empirical studies conducted in the United States. The first study used 375 salespeople from 1200 B2B companies. The second study used 181 respondents from the energy solution company. It was found that social media significantly affects salesperson product information communication, diligence, product knowledge and adaptability, which in turn affect customer relationship performance. It was also found that the use of social media technologies without training on technology will not lead to good results. Thus, the results propose that companies should allocate the resources required for the proper implementation of social media strategies. Future research should examine how the personality traits of a salesperson can moderate the implementation of social media technologies.

While most of the studies focused on a single country, Iankova et al. ( 2018 ) investigated the perceived effectiveness of social media by different types of businesses in two countries. By using 449 respondents from the US and the UK businesses, it was found that social media is potentially less important, at the present time, for managing ongoing relationships in B2B organizations than for B2C, Mixed or B2B2C organizations. All types of businesses ascribe similar importance to social media for acquisition-related activities. Also it was found that B2B organizations see social media as a less effective communication channel, and to have less potential as a channel for the business.

3.1.5 Brand Awareness

Some researchers argued that social media can influence brand awareness (Ancillai et al. 2019 ; Hsiao et al. 2020 ). For instance, Hsiao et al. ( 2020 ) investigated the effect of social media in the fashion industry. By collecting 1395 posts from lookbook.nu and employing regression analysis it was found that the inclusion of national brand and private fashion brands in the post increased the level of popularity which leads to purchasing interest and brand awareness.

3.1.6 Knowledge Creation

Multiple types of collaborative web tools can help and significantly increase the collaboration and the use of the distributed knowledge inside and outside of the company (McAfee 2006 ). Kärkkäinen et al. ( 2011 ) by analysing previous literature on social media proposed that social media use has a positive effect on sharing and creation of customer information and knowledge in the case of B2B companies.

3.1.7 Corporate Credibility

Another study by Kho ( 2008 ) states the advantages of using social media by B2B companies, which include faster and more personalised communications between customer and vendor, which can improve corporate credibility and strengthen the relationships. Thanks to social media companies can provide more detailed information about their products and services. Kho ( 2008 ) also mentions that customer forums and blog comments in the B2B environment should be carefully monitored in order to make sure that inappropriate discussions are taken offline and negative eWOM communications should be addressed in a timely manner.

3.1.8 Acquiring New Customers

Meire et al. ( 2017 ) investigated the impact of social media on acquiring B2B customers. By using commercially purchased prospecting data, website data and Facebook data from beverage companies the study conducted an experiment and found that social media us an effective tool in acquiring B2B customers. Future work might assess the added value of social media pages for profitability prediction instead of prospect conversion. When a longer timeframe becomes available (e.g., after one year), the profitability of the converted prospects can be assessed.

3.1.9 Salesperson Performance

Moncrief et al. ( 2015 ) investigated the impact of social media technologies on the role of salesperson position. It was found that social media affects sales management functions (supervision, selection, training, compensation, and deployment) and salesperson performance (role, skill, and motivation). Another study by Rodriguez et al. ( 2012 ) examines the effect of social media on B2B sales performance by using social capital theory and collecting data from 1699 B2B salespeople from over 25 different industries. By employing SEM AMOS, the study found that social media usage has a positive significant relationship with selling companies’ ability to create opportunities and manage relationships. The study also found that social media usage has a positive and significant relationship with sales performance (based on relational measurers of sales that focus on behaviours that strengthen the relationship between buyers and sellers), but not with outcome-based sales performance (reflected by quota achievement, growth in average billing size, and overall revenue gain).

3.1.10 Employee Brand Management

The study by Pitt et al. ( 2018 ) focuses on employee engagement with B2B companies on social media. By using results from Glassdoor (2315 five-star and 1983 one-star reviews for the highest-ranked firms, and 1013 five star and 1025 one-star reviews for lowest ranked firms) on employee brand engagement on social media, two key drivers of employee brand engagement by using the content analysis tool DICTION were identified-optimism and commonality. Individuals working in top-ranked companies expressed a higher level of optimism and commonality in comparison with individuals working in low-ranked companies. As a result, a 2 × 2 matrix was constructed which can help managers to choose strategies in order to increase and improve employee brand engagement. Another study by Pitt et al. ( 2017 ) focused on employee engagement of B2B companies on social media. By using a conceptual framework based on a theory of word choice and verbal tone and 6300 reviews collected from Glassdoor and analysed using DICTION. The study found that employees of highly ranked B2B companies are more positive about their employer brand and talk more optimistically about these brands. For low ranked B2B companies it was found that employees express a greater level of activity, certainty, and realism. Also, it was found that they used more aggressive language.

3.1.11 Sustainability

Sustainability refers to the strategy that helps a business “to meet its current requirements without compromising its ability to meet future needs” (World Commission Report on Environment and Development 1987 , p 41). Two studies out of 70 focused on the role of social media for B2B sustainability (Sivarajah et al. 2019 ; Kasper et al. 2015 ). For example, Sivarajah et al. ( 2019 ) argued that big data and social media within a participatory web environment to enable B2B organisations to become profitable and remain sustainable through strategic operations and marketing related business activities.

Another study by Kasper et al. ( 2015 ) proposed the Social Media Matrix which helps companies to decide which social media activities to execute based on their corporate and communication goals. The matrix includes three parts. The first part is focusing on social media goals and task areas, which were identified and matched. The second part consists of five types of social media activities (content, interaction/dialog, listening and analysing, application and networking). The third part provides a structure to assess the suitability of each activity type on each social media platform for each goal. The matrix was successfully tested by assessing the German B2B sector by using expert interviews with practitioners.

Based on the reviewed studies, it can be seen that if used appropriately social media have positive effect on B2B companies before and after sales, such as customer satisfaction, value creation, intention to buy and sales, customer relationships, brand awareness, knowledge creation, corporate credibility, acquiring new customers, salesperson performance, employee brand management, and sustainability. However, limited research is done on the negative effect of social media on b2b companies.

3.2 Adoption of Social Media

Some scholars investigated factors affecting the adoption of social media by B2B companies (Buratti et al. 2018 ; Gáti et al. 2018 ; Gazal et al. 2016 ; Itani et al. 2017 ; Kumar and Möller 2018 ; Lacka and Chong 2016 ). For instance, Lacka and Chong ( 2016 ) investigated factors affecting the adoption of social media by B2B companies from different industries in China. The study collected the data from 181 respondents and used the technology acceptance model with Nielsen’s model of attributes of system acceptability as a theoretical framework. By using SEM AMOS for analysis the study found that perceived usability, perceived usefulness, and perceived utility positively affect adoption and use of social media by B2B marketing professionals. The usefulness is subject to the assessment of whether social media sites are suitable means through which marketing activities can be conducted. The ability to use social media sites for B2B marketing purposes, in turn, is due to those sites learnability and memorability attributes.

Another study by Müller et al. ( 2018 ) investigated factors affecting the usage of social media. By using survey data from 100 Polish and 39 German sensor suppliers, it was found that buying frequency, the function of a buyer, the industry sector and the country does not affect the usage of social media in the context of sensor technology from Poland and Germany. The study used correlation analysis and ANOVA.

Lashgari et al. ( 2018 ) studied the adoption and use of social media by using face-to-face interviews with key managers of four multinational corporations and observations from companies’ websites and social media platforms. It was found that that the elements essential in forming the B2B firm’s social media adoption strategies are content (depth and diversity), corresponding social media platform, the structure of social media channels, the role of moderators, information accessibility approaches (public vs. gated-content), and online communities. These elements are customized to the goals and target group the firm sets to pursue. Similarly, integration of social media into other promotional channels can fall under an ad-hoc or continuous approach depending on the scope and the breadth of the communication plan, derived from the goal.

Similar to Lashgari et al. ( 2018 ), Shaltoni ( 2017 ) used data from managers. The study applied technology organisational environmental framework and diffusion of innovations to investigate factors affecting the adoption of social media by B2B companies. By using data from marketing managers or business owners of 480 SMEs, the study found that perceived relative advance, perceive compatibility, organizational innovativeness, competitor pressure, and customer pressure influence the adoption of social media by B2B companies. The findings also suggest that many decision-makers in B2B companies think that Internet marketing is not beneficial, as it is not compatible with the nature of B2B markets.

Buratti et al. ( 2018 ) investigated the adoption of social media by tanker shipping companies and ocean carriers. By using data from 60 companies the following was found. LinkedIn is the most used tool, with a 93.3% adoption rate. Firm size emerges as a predictor of Twitter’s adoption: big companies unveil a higher attitude to use it. Finally, the country of origin is not a strong influential factor in the adoption rate. Nonetheless, Asian firms clearly show a lower attitude to join SM tools such as Facebook (70%) and LinkedIn (86.7%), probably also due to governmental web restrictions imposed in China. External dimensions such as the core business, the firm size, the geographic area of origin, etc., seem to affect network wideness. Firm size, also, discriminates the capacity of firms to build relational networks. Bigger firms create networks larger than small firms do. Looking at geographical dimensions, Asian firms confirm to be far less active on SM respect to European and North American firms. Finally, the study analyzed the format of the contents disclosed by sample firms, observing quite limited use of photos and videos: in the sample industries, informational contents seem more appropriate for activating a dialogue with stakeholders and communication still appears formulated in a very traditional manner. Preliminary findings suggest that companies operating in conservative B2B services pursue different strategic approaches toward SMM and develop ad hoc communication tactics. Nonetheless, to be successful in managing SM tools, a high degree of commitment and a clear vision concerning the role of SM within communication and marketing strategy is necessary.

Gazal et al. ( 2016 ) investigated the adoption and measuring of the effectiveness of social media in the context of the US forest industry by using organisational-level adoption framework and TAM. By using data from 166 companies and performing regression analysis, the following results were received. Years in business, new sales revenue, product type, amount of available information on a company website, perceived importance of e-commerce and perceived ease of use of social media significantly affected social media use. Also, it was found that companies’ strategies and internal resources and capabilities and influence a company’s decision to adopt social media. Also, it was found that 94 of respondents do not measure the ROI from social media use. The reason is that the use of social media in marketing is relatively new and companies do not possess the knowledge of measuring ROI from the use of social media. Companies mostly use quantitative metrics (number of site visits, number of social network friends, number of comments and profile views) and qualitative metrics (growth of relationships with the key audience, audience participation, moving from monologue to dialogue with consumers. Facebook was found to be the most effective social media platform reported by the US forest industry.

The study by Kumar and Möller ( 2018 ) investigated the role of social media for B2B companies in their recruitment practices. By using data from international B2B company with headquarter in Helsinki, Finland comprised of 139 respondents it was found that brand familiarity encourages them to adopt social media platforms for a job search; however, the effect of the persuasiveness of recruitment messages on users’ adoption of social media platforms for their job search behavior is negative. The study used correlation analysis and descriptive analysis to analyse the data.

Nunan et al. ( 2018 ) identified areas for future research such as patterns of social media adoption, the role of social media platforms within the sales process, B2B consumer engagement and social media, modeling the ROI of social media, and the risks of social media within B2B sales relationships.

The study by Pascucci et al. ( 2018 ) conducted a systematic literature review on antecedents affecting the adoption and use of social media by B2B companies. By reviewing 29 studies published in academic journal and conferences from 2001 to 2017, the study identified external (pressure from customers, competitors, availability of external information about social media) and internal factors (personal characteristics -managers age, individual commitment, perceptions of social media-perceived ease of use, perceived usefulness, perceived utility), which can affect adoption of social media.

The study by Siamagka et al. ( 2015 ) aims to investigate factors affecting the adoption of social media by B2B organisations. The conceptual model was based on the technology acceptance model and the resource-based theory. AMOS software and Structural equation modelling were employed to test the proposed hypotheses. By using a sample of 105 UK companies, the study found that perceived usefulness of social media is influenced by image, perceived ease of use and perceived barriers. Also, it was found that social media adoption is significantly determined by organisational innovativeness and perceived usefulness. Additionally, the study tested the moderating role of organisational innovativeness and found that it does not affect the adoption of social media by B2B organisations. The study also identified that perceived barriers to SNS (uncertainty about how to use SNS to achieve objectives, employee’s lack of knowledge about SNS, high cost of investment needed to adopt the technology) have a negative impact on perceived usefulness of social media by B2B organisations. The study also used nine in-depth interviews with B2B senior managers and social media specialists about adoption of social media by B2B. It was found that perceived pressure from stakeholders influences B2B organisations’ adoption intention of social media. Future research should test it by using quantitative methods.

While most of the studies focused on the antecedents of social media adoption by B2B companies, Michaelidou et al. ( 2011 ) investigated the usage, perceived barriers and measuring the effectiveness of social media. By using data from 92 SMEs the study found that over a quarter of B2B SMEs in the UK are currently using SNS to achieve brand objectives, the most popular of which is to attract new customers. The barriers that prevent SMEs from using social media to support their brands were lack of staff familiarity and technical skills. Innovativeness of a company determined the adoption of social media. It was found that most of the companies do not evaluate the effectiveness of their SNS in supporting their brand. The most popular measures were the number of users joining the groups/discussion and the number of comments made. The findings showed that the size of the company does not influence the usage of social media for small and medium-sized companies. Future research should investigate the usage of social media in large companies and determine if the size can have and influence on the use. The benefits of using social media include increasing awareness and communicating the brand online. B2B companies can employ social media to create customer value in the form of interacting with customers, as well as building and fostering customer relationships. Future research should investigate the reasons why most of the users do not assess the effectiveness of their SNS. Future research should also investigate how the attitude towards technology can influence the adoption of social media.

Based on the reviewed studies it can be seen that the main factors affecting the adoption of social media by B2B companies are perceived usability, technical skills of employees, pressure from stakeholders, perceived usefulness and innovativeness.

3.3 Social Media Strategies

Another group of studies investigated types of strategies B2B companies apply (Cawsey and Rowley 2016 ; Huotari et al. 2015 ; Kasper et al. 2015 ; McShane et al. 2019 ; Mudambi et al. 2019 ; Swani et al. 2013 ; Swani et al. 2014 ; Swani et al. 2017 ; Watt 2010 ). For example, Cawsey and Rowley ( 2016 ) focused on the social media strategies of B2B companies. By conducting semi-structured interviews with marketing professionals from France, Ireland, the UK and the USA it was found that enhancing brand image, extending brand awareness and facilitating customer engagement were considered the most common social media objective. The study proposed the B2B social media strategy framework, which includes six components of a social media strategy: 1) monitoring and listening 2) empowering and engaging employees 3) creating compelling content 4) stimulating eWOM 5) evaluating and selecting channels 6) enhancing brand presence through integrating social media.

Chirumalla et al. ( 2018 ) focused on the social media engagement strategies of manufacturing companies. By using semi-structured interviews (36), observations (4), focus group meetings (6), and documentation, the study developed the process of social media adoption through a three-phase engagement strategy which includes coordination, cooperation, and co-production.

McShane et al. ( 2019 ) proposed social media strategies to influence online users’ engagement with B2B companies. Taking into consideration fluency lens the study analysed Twitter feeds of top 50 social B2B brands to examine the influence of hashtags, text difficulty embedded media and message timing on user engagement, which was evaluated in terms of likes and retweets. It was found that hashtags and text difficulty are connected to lower levels of engagement while embedded media such as images and videos improve the level of engagement.

Swani et al. ( 2014 ) investigate the use of Twitter by B2B and B2C companies and predict factors that influence message strategies. The study conducted a longitudinal content analysis by collecting 7000 tweets from Fortune 500 companies. It was found that B2B and B2C companies used different message appeals, cues, links and hashtags. B2B companies tend to use more emotional than functional appeals. It was found that B2B and B2C companies do not use hard-sell message strategies.

Another study by Swani et al. ( 2013 ) aimed to investigate message strategies that can help in promoting eWOM activity for B2B companies. By applying content analysis and hierarchical linear modeling the study analysed 1143 wall post messages from 193 fortune 500 Facebook accounts. The study found that B2B account posts will be more effective if they include corporate brand names and avoid hard sell or explicitly commercial statement. Also, companies should use emotional sentiment in Facebook posts.

Huotari et al. ( 2015 ) aimed to investigate how B2B marketers can influence content creation in social media. By conducting four face-to-face interviews with B2B marketers, it was found that a B2B company can influence content creation in social media directly by adding new content, participating in a discussion and removing content through corporate user accounts and controlling employees social media behaviour. Also, it can influence it indirectly by training employees to create desired content and perfuming marketing activities that influence other users to create content that is favorable for the company.

Most of the studies investigated the strategies and content of social media communications of B2B companies. However, the limited number of studies investigated the importance of CEO engagement on social media in the company’s strategies. Mudambi et al. ( 2019 ) emphasise the importance of the CEO of B2B companies to be present and active on social media. The study discusses the advantages of social media presence for the CEO and how it will benefit the company. For example, one of the benefits for the CEO can be perceived as being more trustworthy and effective than non-social CEOs, which will benefit the company in increased customer trust. Mudambi et al. ( 2019 ) also discussed the platforms the CEO should use and posting frequencies depending on the content of the post.

From the above review of the studies, it can be seen that B2B companies social media strategies include enhancing brand image, extending brand awareness and facilitating customer engagement. Companies use various message strategies, such as using emotional appeal, use of brand names, and use of hashtags. Majority of the companies avoid hard sell or explicitly commercial statement.

3.4 Social Media Use

Studies investigated the way how companies used social media and factors affecting the use of social media by B2B (Andersson et al. 2013 ; Bernard 2016 ; Bolat et al. 2016 ; Denktaş-Şakar and Sürücü 2018 ; Dyck 2010 ; Guesalaga 2016 ; Habibi et al. 2015 ). For example, Vasudevan and Kumar ( 2018 ) investigated how B2B companies use social media by analysing 325 brand posts of Canon India, Epson India, and HP India on Linkedin, Facebook, and Twitter. By employing content analysis the study found that most of the posts had a combination of text and message. More than 50% of the posts were about product or brand-centric. The study argued that likes proved to be an unreliable measure of engagement, while shares were considered a more reliable metric. The reason was that likes had high spikes when brand posts were boosted during promotional activities.

Andersson and Wikström ( 2017 ) used case studies of three B2B companies to investigate reasons for using social media. It was found that companies use social media to enhance customer relationships, support sales and build their brands. Also, social media is used as a recruiting tool, a seeking tool, and a product information and service tool.

Bell and Shirzad ( 2013 ) aimed to conduct social media use analysis in the context of pharmaceutical companies. The study analysed 54,365 tweets from the top five pharmaceutical companies. The study analysed the popular time slots, the average number of positive and negative tweets and its content by using Nvivo9.

Bernard ( 2016 ) aims to examine how chief marketing officers use social media. By using case studies from IBM experience with social media it was found that B2B CMO’s are not ready to make use of social media. It was proposed that social media can be used for after-sales service, getting sales leads, engaging with key influencers, building the company’s reputation and enhancing the industry status of key individuals. B2B firms need to exploit the capabilities of processing massive amounts of data to get the most from social media.

Bolat et al. ( 2016 ) explore how companies apply mobile social media. By employing a grounded theory approach to analyse interviews from 26 B2B company representatives from UK advertising and marketing sector companies. It was found that companies use social media for branding, sensing market, managing relationships, and developing content.

Denktaş-Şakar and Sürücü ( 2018 ) investigated how social media usage influence stakeholder engagement focusing on the corporate Facebook page of 30 3PLs companies. In total 1532 Facebook posts were analysed. It was found that the number of followers, post sharing frequency, negatively affect stakeholder engagement. It was found that content including photos facilitates more stakeholder engagement (likes, comment, share) in comparison with other forms. Vivid posts and special day celebration posts strengthen relationships with stakeholders.

Dyck ( 2010 ) discussed the advantages of using social media for the device industry. Social media can be used for product innovation and development, to build a team and collaborate globally. Also, there is an opportunity to connect with all of the stakeholders needed in order to deliver the device to the market. Additionally, it provides to receive feedback from customers (doctors, hospitals) in real-time.

The study by Guesalaga ( 2016 ) draws on interactional psychology theory to propose and test a model of usage of social media in sales, analysing individual, organizational, and customer-related factors. It was found that organizational competence and commitment to social media are key determinants of social media usage in sales, as well as individual commitment. Customer engagement with social media also predicts social media usage in sales, both directly and (mostly) through the individual and organizational factors analysed, especially organizational competence and commitment. Finally, the study found evidence of synergistic effects between individual competence and commitment, which is not found at the organizational level. The data obtained by surveying 220 sales executives in the United States were analysed using regression analysis.

Habibi et al. ( 2015 ) proposed a conceptual model for the implementation of social media by B2B companies. Based on existing B2B marketing, social media and organisational orientational literature the study proposed that four components of electronic market orientation (philosophical, initiation, implementation and adoption) address different implementation issues faced in implementing social media.

Katona and Sarvary ( 2014 ) presented a case of using social media by Maersk-the largest container shipping company in the world. The case provided details on the program launch and the integration strategy which focused on integrating the largest independent social media operation into the company’s broader marketing efforts.

Moore et al. ( 2013 ) provided insights into the understanding of the use of social media by salespersons. 395 salespeople in B2B and B2C markets, utilization of relationship-oriented social media applications are presented and examined. Overall, findings show that B2B practitioners tend to use media targeted at professionals whereas their B2C counterparts tend to utilize more sites targeted to the general public for engaging in one-on-one dialogue with their customers. Moreover, B2B professionals tend to use relationship-oriented social media technologies more than B2C professionals for the purpose of prospecting, handling objections, and after-sale follow-up.

Moore et al. ( 2015 ) investigated the use of social media between B2B and B2C salespeople. By using survey data from 395 sales professionals from different industries they found that B2B sales managers use social selling tools significantly more frequently than B2C managers and B2C sales representatives while conducting sales presentations. Also, it was found that B2B managers used social selling tools significantly more frequently than all sales representatives while closing sales.

Müller et al. ( 2013 ) investigated social media use in the German automotive market. By using online analysis of 10 most popular car manufacturers online social networks and surveys of six manufacturers, 42 car dealers, 199 buyers the study found that social media communication relations are widely established between manufacturers and (prospective) buyers and only partially established between car dealers and prospective buyers. In contrast to that, on the B2B side, social media communication is rarely used. Social Online Networks (SONs) are the most popular social media channels employed by businesses. Manufacturers and car dealers focus their social media engagement, especially on Facebook. From the perspective of prospective buyers, however, forums are the most important source of information.

Sułkowski and Kaczorowska-Spychalska ( 2016 ) investigated the adoption of social media by companies in the Polish textile-clothing industry. By interviewing seven companies representatives of small and medium-sized enterprises the study found that companies started implementing social media activities in their marketing activities.

Vukanovic ( 2013 ) by reviewing previous literature on social media outlined advantages of using social media for B2B companies, which include: increase customer loyalty and trust, building and improving corporate reputation, facilitating open communications, improvement in customer engagement to name a few.

Keinänen and Kuivalainen ( 2015 ) investigated factors affecting the use of social media by B2B customers by conducting an online survey among 82 key customer accounts of an information technology service company. Partial least squares path modelling was used to analysed the proposed hypotheses. It was found that social media private use, colleague support for using SM, age, job position affected the use of social media by B2B customers. The study also found that corporate culture, gender, easiness to use, and perception of usability did not affect the use of social media by B2B customers.

By using interviews and survey social media research found that mostly B2B companies use social media to enhance customer relationships, support sales, build their brands, sense market, manage relationships, and develop content. Additionally, some companies use it social media as a recruitment tool. The main difference between B2B and B2C was that B2B sales managers use social selling tools significantly more frequently than B2C managers.

3.5 Measuring the Effectiveness of Social Media

It is important for a business to be able to measure the effectiveness of social media by calculating return on investment (ROI). ROI is the relationship between profit and the investment that generate that profit. Some studies focused on the ways B2B companies can measure ROI and the challenges they face (Gazal et al. 2016 ; Michaelidou et al. 2011 ; Vasudevan and Kumar 2018 ). For example, Gazal et al. ( 2016 ) investigated the adoption and measuring of the effectiveness of social media in the context of the US forest industry by using organisational-level adoption framework and TAM. By using data from 166 companies it was found that 94% of respondents do not measure the ROI from social media use. The reason is that the use of social media in marketing is relatively new and companies do not possess the knowledge of measuring ROI from the use of social media. Companies mostly use quantitative metrics (number of site visits, number of social network friends, number of comments and profile views) and qualitative metrics (growth of relationships with the key audience, audience participation, moving from monologue to dialogue with consumers).

Another study by Michaelidou et al. ( 2011 ) found that most of the companies do not evaluate the effectiveness of their SNS in supporting their brand. The most popular measures were the number of users joining the groups/discussion and the number of comments made.

Vasudevan and Kumar ( 2018 ) investigated how B2B companies use social media and measure ROI from social media by analysing 325 brand posts of Canon India, Epson India, and HP India on Linkedin, Facebook, and Twitter. By employing content analysis the study found that most of the post has a combination of text and message. More than 50% of the posts were about product or brand-centric. The study argued that likes proved to be an unreliable measure of engagement, while shares were considered a more reliable metric. The reason was that likes had high spikes when brand posts were boosted during promotional activities. Future research should conduct longitudinal studies.

By reviewing the above studies, it can be concluded that companies still struggle to find ways of measuring ROI and applying correct metrics. By gaining knowledge in how to measure ROI from social media activities, B2B companies will be able to produce valuable insights leading to better marketing strategies (Lal et al. 2020 ).

3.6 Social Media Tools

Some studies proposed tools that could be employed by companies to advance their use of social media. For example, Mehmet and Clarke ( 2016 ) proposed a social semiotic multimodal (SSMM) framework that improved the analysis of social media communications. This framework employs multimodal extensions to systemic functional linguistics enabling it to be applying to analysing non-language as well as language constituents of social media messages. Furthermore, the framework also utilises expansion theory to identify, categorise and analyse various marketing communication resources associated with marketing messages and also to reveal how conversations are chained together to form extended online marketing conversations. This semantic approach is exemplified using a Fairtrade Australia B2B case study demonstrating how marketing conversations can be mapped and analysed. The framework emphasises the importance of acknowledging the impact of all stakeholders, particularly messages that may distract or confuse the original purpose of the conversation.

Yang et al. ( 2012 ) proposed the temporal analysis technique to identify user relationships on social media platforms. The experiment was conducted by using data from Digg.com . The results showed that the proposed techniques achieved substantially higher recall but not very good at precision. This technique will help companies to identify their future consumers based on their user relationships.

Based on the literature review, it can be seen that B2B companies can benefit by using the discussed tools. However, it is important to consider that employee should have some technical skills and knowledge to use these tools successfully. As a result, companies will need to invest some resources in staff training.

4 Weight Analysis

Weight analysis enables scrutiny of the predictive power of independent variables in studied relationships and the degree of effectiveness of the relationships (Jeyaraj et al. 2006 ; Rana et al. 2015 ; Ismagilova et al. 2020a ). The results of weight analysis are depicted in Table 3 providing information about an independent variable, dependent variable, number of significant relationships, number of non-significant relationships, the total number of relationships and weight. To perform weight analysis, the number of significant relationships was divided by the total number of analysed relationships between the independent variable and the dependent variable (Jeyaraj et al. 2006 ; Rana et al. 2015 ). For example, the weight for the relationship between attitude towards social media and social media is calculated by dividing ‘1’ (the number of significant relationships) by ‘2’ (the total number of relationships) which equals 0.5.

A predictor is defined as well-utilised if it was examined five or more times, otherwise, it is defined as experimental. It can be seen from Table 3 that all relationships were examined less than five times. Thus all studied predictors are experimental. The predictor is defined as promising when it has been examined less than five times by existing studies but has a weight equal to ‘1’ (Jeyaraj et al. 2006 ). From the predictors affecting the adoption of social media, it can be seen that two are promising, technical skills of employees and pressure from stakeholders. Social media usage is a promising predictor for acquiring new customers, sales, stakeholder engagement and customer satisfaction. Perceived ease of use and age of salesperson are promising predictors of social media usage. Even though this relationship was found to be significant every time it was examined, it is suggested that this variable, which can also be referred to as experimental, will need to be further tested in order to qualify as the best predictor. Another predictor, average rating of product/service, was examined less than five times with a weight equal to 0.75, thus it is considered as an experimental predictor.

Figure 1 shows the diagrammatic representation of the factors affecting different relationships in B2B social media with their corresponding weights, based on the results of weight analysis. The findings suggest that promising predictors should be included in further empirical studies to determine their overall performance.

Diagrammatic representation of results of weight analysis. Note: experimental predictors

It can be seen from Fig. 1 that social media usage is affected by internal (e.g. attitude towards social media, technical skills of employees) and external factors (e.g. pressure from stakeholders) of the company. Also, the figure depicts the effect of social media on the business (e.g. sales) and society (e.g. customer satisfaction).

5 Discussion

In reviewing the publications gathered for this paper, the following themes were identified. Some studies investigated the effect of social media use by B2B companies. By using mostly survey to collect the data from salespeople and managers, the studies found that social media has a positive effect on number of outcomes important for the business such as customer satisfaction, value creation, intention to buy and sales, customer relationships, brand awareness, knowledge creation, corporate credibility, acquiring new customers, salespersons performance, employee brand management, and sustainability. Most of the outcomes are similar to the research on social media in the context of B2C companies. However, some of the outcomes are unique for B2B context (e.g. employee brand management, company credibility). Just recently, studies started investigating the impact of the use of social media on sustainability.

Another group of studies looked at the adoption of social media by B2B companies (Buratti et al. 2018 ; Gáti et al. 2018 ; Gazal et al. 2016 ; Itani et al. 2017 ; Kumar and Möller 2018 ). The studies investigated it mostly from the perspectives of salespersons and identify some of the key factors which affect the adoption, such as innovativeness, technical skills of employees, pressure from stakeholders, perceived usefulness, and perceived usability. As these factors are derived mostly from surveys conducted with salespersons findings can be different for other individuals working in the organisation. This it is important to conduct studies that will examine factors affecting the adoption of social media across the entire organisation, in different departments. Using social media as part of the digital transformation is much bigger than sales and marketing, it encompasses the entire company. Additionally, most of the studies were cross-sectional, which limits the understanding of the adoption of social media by B2B over time depending on the outcomes and environment (e.g. competitors using social media).

Some studies looked at social media strategies of B2B companies (Cawsey and Rowley 2016 ; Huotari et al. 2015 ; Kasper et al. 2015 ; McShane et al. 2019 ; Mudambi et al. 2019 ). By employing interviews with companies’ managers and analysing its social media platforms (e.g. Twitter) it was found that most of the companies follow the following strategies: 1) monitoring and listening 2) empowering and engaging employees 3) creating compelling content 4) stimulating eWOM 5) evaluating and selecting channels 6) enhancing brand presence through integrating social media (Cawsey and Rowley 2016 ). Some studies investigated the difference between social media strategies of B2B and B2C companies. For example, a study by Swani et al. ( 2017 ) focused on effective social media strategies. By applying psychological motivation theory the study examined the key differences in B2B and B2C social media message strategies in terms of branding, message appeals, selling, and information search. The study used Facebook posts on brand pages of 280 Fortune companies. In total, 1467 posts were analysed. By using Bayesian models, the results showed that the inclusion of corporate brand names, functional and emotional appeals and information search cues increases the popularity of B2B messages in comparison with B2C messages. Also, it was found that readers of B2B content show a higher message liking rate and lower message commenting rate in comparison with readers of B2C messages.

The next group of studies looked at social media use by B2B companies (Andersson et al. 2013 ; Bernard 2016 ; Bolat et al. 2016 ; Denktaş-Şakar and Sürücü 2018 ; Dyck 2010 ; Guesalaga 2016 ; Habibi et al. 2015 ). B2B companies use social media for enhancing and managing customer relationships (Andersson and Wikström 2017 ; Bolat et al. ( 2016 ); branding (Andersson and Wikström 2017 ; Bolat et al. 2016 ), sensing market (Bolat et al. 2016 ) and co-production (Chirumalla et al. 2018 ). Additionally, it was mentioned that some of the B2B companies use social media as a recruiting tool, and tool which helps to collaborate globally (Andersson and Wikström 2017 ; Dyck 2010 ).

It is important for companies to not only use social media to achieve positive business outcomes but also it is important to measure their achievements. As a result, some of the studies focused on the measuring effectiveness of social media (Gazal et al. 2016 ; Michaelidou et al. 2011 ; Vasudevan and Kumar 2018 ). Surprisingly, it was found that not so many companies measure ROI from social media (Gazal et al. 2016 ; Michaelidou et al. 2011 ). The ones who do it mostly use quantitative metrics (number of site visits, number of social network friends, number of comments and profile views) and qualitative metrics (growth of relationships with key audience, audience participation, moving from monologue to dialogue with consumers) (Gazal et al. 2016 ). Some future studies should investigate how ROI influences the strategy of B2B companies over period of time.

The last group of studies focused on social media tools used by B2B companies (Keinänen and Kuivalainen 2015 ; Mehmet and Clarke 2016 ; Yang et al. 2012 ). By using number of social media tools (Social Semiotic Multimodal) companies are able to improve their analysis of social media communications and identify their future consumers based on their user relationships. Studies investigating barriers and factors adoption of various social media tools by B2B companies are needed.

After reviewing studies on b2B social media, weight analysis was performed. Based on the results of weight analysis the conceptual model for future studies was proposed (Fig.  2 ). It is important to note that a limited number of studies focused and empirically tested factors affecting the adoption, use, and effect of social media. As a result, identified factors were considered as experimental (examined less than five times). It is too early to label these experimental predictors as worst or best, thus their further investigation is encouraged.

Social media impact on digital transformation and sustainable societies

Additionally, our review of the literature on B2B social media identified dominant research methods used by scholars. Qualitative and quantitative techniques were used by most of these studies. Closer analysis of 70 publications reviewed in this study revealed the multiple techniques applied for gathering data. Quantitative methods used in the studies mostly used surveys (see Table 4 ).

The data was mostly gathered from salespersons, managers and data from social media platforms (e.g. Twitter, Facebook). Just a limited number of studies employed consumer reported data (see Table 5 ).

On the other hand, publications using qualitative methods mainly used interviews and web scraping for the collection of the required data. To analyse the data studies used a variety of techniques including SEM, regression analysis and content analysis being one of the most used (see Table 6 ).

5.1 Digital Transformation and Sustainability Model

Based on the conducted literature review and adapting the model by Pappas et al. ( 2018 ) Fig. 2 presents the digital transformation and sustainability model in the context of B2B companies, which conceptualise the social media ecosystems, and the factors that need to collaborate to enable the use of social media towards the achievement of digital transformation and the creation of sustainable societies. The model comprises of social media stakeholders, the use of social media by B2B companies, and effect of social media on business and society.

5.1.1 Social Media Stakeholders

Building on the discussion and model provided by Pappas et al. ( 2018 ), this paper posits that the social media ecosystem comprises of the data stakeholders (company, society), who engage on social media (posting, reading, using information from social media). The use of social media by different stakeholders will lead to different effects affecting companies, customers and society. This is an iterative process based on which the stakeholders use their experience to constantly improve and evolve their use of social media, which has impacts on both, business and society. The successful implementation of this process is key to digital transformation and the creation of sustainable societies. Most of the current studies (Andersson et al. 2013 ; Bernard 2016 ; Bolat et al. 2016 ; Denktaş-Şakar and Sürücü 2018 ; Dyck 2010 ; Guesalaga 2016 ) focus mostly on the company as a stakeholder. However, more research is needed on other types of stakeholders (e.g. society).

5.1.2 Use of Social Media by B2B Companies

Social media affects not only ways how companies connect with their clients, but it is also changing their business models, the way how the value is delivered and profit is made. To successfully implement and use social media, B2B companies need to consider various social media tools, antecedents/barriers of its adoption, identify suitable social media strategies which are in line with the company’s overall strategy, and measure effectiveness of the use of social media. There are various factors that affect the use of social media by B2B companies. The study found that social media usage is influenced by perceived ease of use, adoption of social media, attitude towards social media and age of salesperson.

The majority of the studies focus on the management of the marketing department. However, digital transformation is much bigger than just marketing as it encompasses the entire organisation. As a result, future studies should look like the entire organisation and investigate barriers and factors affecting the use of social media.

It is crucial for companies to design content which will be noticed on social media by their potential, actual and former customers. Social media content should be interesting and offer some beneficial information, rather than just focus on services the company provides. Companies could use fresh views on relevant industry news, provide information how they are contributing to society and environment, include humour in their posts, share information about the team, make it more personal. It is also useful to use images, infographics, and video content.

It is also important for companies to measure digital marketing actions. More studies are needed on how to isolate the impact of specific media marketing actions to demonstrate their impact on the desired business outcomes (Salo 2017 ). Thus, future studies can consider how particular social media channels (e.g. Facebook, LinkedIn) in a campaign of a new product/ service influence brand awareness and sales level. Also, a limited number of studies discussed the way B2B companies can measure ROI. Future research should investigate how companies can measure intangible ROI, such as eWOM, brand awareness, and customer engagement (Kumar and Mirchandani 2012 ). Also, future research should investigate the reasons why most of the users do not assess the effectiveness of their SNS. Furthermore, most of the studies focused on likes, shares, and comments to evaluate social media engagement. Future research should focus on other types of measures. More research needs considering the impact of legislation on the use of social media by companies. Recent B2B studies did not consider recent legislation (General Data Protection Regulation 2018 ) in the context B2B (Sivarajah et al. 2019 ).

5.1.3 Effect of Social Media on Business and Society

Social media plays an important part in the company’s decision-making process. Social media can bring positive changes into company, which will result in improving customer satisfaction, value creation, increase in sales, building relationships with customers, knowledge creation, improve the perception of corporate credibility, acquisition of new customers, and improve employment brand engagement. Using information collected from social media can help companies to have a set of reliable attributes that comprise social, economic and environmental aspects in their decision-making process (Tseng 2017 ). Additionally, by using social media B2B companies can provide information to other stakeholders on their sustainability activities. By using data from social media companies will be able to provide products and services which are demanded by society. It will improve the quality of life and result in less waste. Additionally, social media can be considered as a tool that helps managers to integrate business practices with sustainability (Sivarajah et al. 2019 ). As a result, social media use by B2B companies can lead to business and societal changes.

A limited number of studies investigated the effect of social media on word of mouth communications in the B2B context. Future research should investigate the differences and similarities between B2C and B2B eWOM communications. Also, studies should investigate how these types of communications can be improved and ways to deal with negative eWOM. It is important for companies to respond to comments on social media. Additionally, future research should investigate its perceived helpfulness by customers.

Majority of studies (Agnihotri et al. 2016 ; Ancillai et al. 2019 ; Rossmann and Stei 2015 ; Agnihotri et al. 2012 ; Agnihotri et al. 2017 ; Itani et al. 2017 ; Salo 2017 ; Bhattacharjya and Ellison 2015 ; Gáti et al. 2018 ; Gruner and Power 2018 ; Hollebeek 2019 ) investigated positive effect of social media such consumer satisfaction, consumer engagement, and brand awareness. However, it will be interesting to consider the dark side of social media use such as an excessive number of requests on social media to salespeople (Agnihotri et al. 2016 ), which can result in the reduction of the responsiveness; spread of misinformation which can damage the reputation of the company.

Studies were performed in China (Lacka and Chong 2016 ; Niedermeier et al. 2016 ), the USA (Guesalaga 2016 ; Iankova et al. 2018 ; Ogilvie et al. 2018 ), India (Agnihotri et al. 2017 ; Vasudevan and Kumar 2018 ), the UK (Bolat et al. 2016 ; Iankova et al. 2018 ; Michaelidou et al. 2011 ). It is strongly advised that future studies conduct research in other countries as findings can be different due to the culture and social media adoption rates. Future studies should pay particular attention to other emerging markets (such as Russia, Brazil, and South Africa) as they suffer from the slow adoption rate of social media marketing. Some companies in these countries still rely more on traditional media for advertising of their products and services, as they are more trusted in comparison with social media channels (Olotewo 2016 ). The majority of studies investigate the effect of social media in B2B or B2C context. Future studies should pay attention to other contexts (e.g. B2B2B, B2B2C). Another limitation of the current research on B2B companies is that most of the studies on social media in the context of B2B focus on the effect of social media use only on business outcomes. It is important for future research to focus on societal outcomes.

Lastly, most of the studies on social media in the context of B2B companies use a cross-sectional approach to collect the data. Future research can use the longitudinal approach in order to advance understanding of social media use and its impact over time.

5.2 Research Propositions

Based on the social media research in the context of B2B companies and the discussion above the following is proposed, which could serve as a foundation for future empirical work.

Social media is a powerful tool to deliver information to customers. However, social media can be used to get consumer and market insights (Kazienko et al. 2013 ). A number of studies highlighted how information obtained from a number of social media platforms could be used for various marketing purposes, such as understanding the needs and preferences of consumers, marketing potential for new products/services, and current market trends (Agnihotri et al. 2016 ; Constantinides et al. 2008 ). It is advised that future research employs a longitudinal approach to study the impact of social media use on understanding customers. Therefore, the following proposition can be formulated:

Proposition 1

Social media usage of B2B companies has a positive influence on understanding its customers.

By using social media companies can examiner valuable information on competitors. It can help to understand competitors’ habits and strategies, which can lead to the competitive advantage and help strategic planning (Dey et al. 2011 ; Eid et al. 2019 ; Teo and Choo 2001 ). It is advised that future research employs a longitudinal approach to study the impact of social media use on understanding its competitors. As a result, using social media to understand customers and competitors can create business value (Mikalef et al. 2020a ) for key stakeholders and lead to positive changes in the business and societies. The above discussion leads to the following proposition:

Proposition 2

Social media usage of B2B companies has a positive influence on understanding its competitors.

Proposition 3

Culture influences the adoption and use of social media by B2B companies.

Usage of social media can result in some positive marketing outcomes such as building new customer relationships, increasing brand awareness, and level of sales to name a few (Agnihotri et al. 2016 ; Ancillai et al. 2019 ; Dwivedi et al. 2020 ; Rossmann and Stei 2015 ). However, when social media is not used appropriately it can lead to negative consequences. If a company does not have enough resources to implement social media tools the burden usually comes on a salesperson. A high number of customer inquiries, the pressure to engage with customers on social media, and monitor communications happening on various social media platforms can result in the increased workload of a salesperson putting extra pressure (Agnihotri et al. 2016 ). As a result, a salesperson might not have enough time to engage with all the customers online promptly or engage in reactive and proactive web care. As a result, customer satisfaction can be affected as well as company reputation. To investigate the negative impact of social media research could apply novel methods for data collection and analysis such as fsQCA (Pappas et al. 2020 ), or implying eye-tracking (Mikalef et al. 2020b ). This leads to the following proposition:

Proposition 4

Inappropriate use of social media by B2B companies has a negative effect on a) customer satisfaction and b) company reputation.

According to Technology-Organisation-Environment (TOE) framework environmental context significantly affects a company’s use of innovations (Abed 2020 ; Oliveira and Martins 2011 ). Environment refers to the factors which affect companies from outside, including competitors and customers. Adopting innovation can help companies to change the rules of the competition and reach a competitive advantage (Porter and Millar 1985 ). In a competitive environment, companies have a tendency to adopt an innovation. AlSharji et al. ( 2018 ) argued that the adoption of innovation can be extended to social media use by companies. A study by AlSharji et al. ( 2018 ) by using data from 1700 SMEs operating in the United Arab Emirates found that competitive pressure significantly affects the use of social media by SMEs. It can be explained by the fact that companies could feel pressure when other companies in the industry start adopting a particular technology and as a result adopt it to remain competitive (Kuan and Chau 2001 ). Based on the above discussion, the following proposition can be formulated:

Proposition 5

Competitive pressure positively affects the adoption of social media by B2B companies.

Companies might feel that they are forced to adopt and use IT innovations because their customers would expect them to do so. Meeting customers’ expectations could result in adoption of new technologies by B2B companies. Some research studies investigated the impact of customer pressure on companies (AlSharji et al. 2018 ; Maduku et al. 2016 ). For example, a study by Maduku et al. ( 2016 ) found that customer pressure has a positive effect on SMEs adoption of mobile marketing in the context of South Africa. Future research could implement longitudinal approach to investigate how environment affects adoption of social media by B2B companies. This leads to the formulation of the following proposition:

Proposition 6

Customer pressure positively affects the adoption of social media by B2B companies.

6 Conclusion

The aim of this research was to provide a comprehensive systematic review of the literature on social media in the context of B2B companies and propose the framework outlining the role of social media in the digital transformation of B2B companies. It was found that B2B companies use social media, but not all companies consider it as part of their marketing strategies. The studies on social media in the B2B context focused on the effect of social media, antecedents, and barriers of adoption of social media, social media strategies, social media use, and measuring the effectiveness of social media. Academics and practitioners can employ the current study as an informative framework for research on the use of social media by B2B companies. The summary of the key observations provided from this literature review is the following: [i] Facebook, Twitter, and LinkedIn are the most famous social media platforms used by B2B companies, [ii] Social media has a positive effect on customer satisfaction, acquisition of new customers, sales, stakeholder engagement, and customer relationships, [iii] In systematically reviewing 70 publications on social media in the context of B2B companies it was observed that most of the studies use online surveys and online content analysis, [iv] Companies still look for ways to evaluate the effectiveness of social media, [v] Innovativeness, pressure from stakeholders, perceived usefulness, and perceived usability have a significant positive effect on companies’ adoption to use social media, [vi] Lack of staff familiarity and technical skills are the main barriers that affect the adoption of social media by B2B, [vii] Social media has an impact not only on business but also on society, [viii] There is a dark side of social media: fake online reviews, an excessive number of requests on social media to salespeople, distribution of misinformation, negative eWOM, [ix] Use of social media by companies has a positive effect on sustainability, and [x] For successful digital transformation social media should change not only the way how companies integrate it into their marketing strategies but the way how companies deliver values to their customers and conduct their business. This research has a number of limitations. First, only publications from the Scopus database were included in literature analysis and synthesis. Second, this research did not use meta-analysis. To provide a broader picture of the research on social media in the B2B context and reconcile conflicting findings of the existing studies future research should conduct a meta-analysis (Ismagilova et al. 2020c ). It will advance knowledge of the social media domain.

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Dwivedi, Y.K., Ismagilova, E., Rana, N.P. et al. Social Media Adoption, Usage And Impact In Business-To-Business (B2B) Context: A State-Of-The-Art Literature Review. Inf Syst Front 25 , 971–993 (2023). https://doi.org/10.1007/s10796-021-10106-y

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Study reveals inadequate levels of medical assistant staffing in US

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A new paper published in Annals of Family Medicine analyzed the current ratio of medical assistants to primary care physicians within medical practices, finding that health-system-owned practices were less likely to be adequately staffed than other practices.

According to the paper, medical assistants are among the fastest growing occupations within the US primary care workforce, and many medical practices have expanded the roles and caregiving responsibilities of primary care medical assistants.

But not much was previously known about medical assistant staffing ratios across the US. This study was the first to assess staffing ratios and to examine the factors associated with ratios consistent with the teamlet model of primary care. The teamlet model includes two medical assistant health coaches and one primary care clinician.

The study analyzed survey answers from 1,252 primary care practices and determined that more than half (56.6%) of the practices had ratios of one medical assistant to each primary care clinician. Slightly more than one in ten (11.4%) had ratios of two or more assistants per clinician while more than a quarter (27.6%) had less than a one-to-one ratio.

“Adequate medical assistant staffing is needed to support the delivery of patient-centered, high-quality primary care. Medical assistants increasingly provide direct patient support, including health coaching to help patients with managing their chronic conditions and conducting patient outreach activities to ensure the reliable provision of evidence-based and recommended care,” said lead author Hector P. Rodriguez.

“Past research indicates that a staffing ratio of 2-to-1 medical assistants to primary care clinicians is needed for ‘teamlets’ to effectively support the provision of preventive care and help manage chronic care, while continuing to do traditional medical assistant functions, such as taking medical histories and preparing patients for examinations. Our study indicates that few primary care practices (~11%) have the capacity to provide the recommended staffing ratios for the teamlet model.”

Independent practices, medical group–owned practices, and Federally Qualified Health Centers were more likely to have ratios of two or more assistants per clinicians than practices owned by health care systems. Low medical assistant staffing levels were not found to be associated with higher levels of staffing of nurses, physician assistants, and nurse practitioners.

“The current study’s results suggest that system-owned practices may be less able to use patient-centered innovations because they have less medical assistant staffing support compared to independent practices and medical group owned practices,” said Rodriguez. “Health policy advocates are increasingly concerned about the potential harms of physician practice consolidation under health care systems because systems may be less responsive to the local needs of vulnerable populations and inadequately resource primary care practices to effectively address patients’ self-management and navigation support needs. Our hope is that the study helps make the connection between medical assistant staffing and the provision of patient-centered care clear to policy makers and health care organizational decision-makers.”

Additional authors include: Dorothy Y. Hung and Stephen M. Shortell of UC Berkeley School of Public Health and Alena D. Berube and Elliott S. Fisher of the Dartmouth Center for Health Policy & Clinical Practice at Dartmouth College.

This research project was funded by the Robert Wood Johnson Foundation.

People of BPH found in this article include:

• Hector Rodriguez Professor, Health Policy and Management
• Stephen Shortell Professor Emeritus

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The Use of Social Media in Children and Adolescents: Scoping Review on the Potential Risks

Elena bozzola.

1 Pediatric Unit, IRCCS Bambino Gesù Children Hospital, 00100 Rome, Italy

2 The Italian Pediatric Society, 00100 Rome, Italy

Giulia Spina

Rino agostiniani.

3 Department of Pediatrics, San Jacopo Hospital, 51100 Pistoia, Italy

Sarah Barni

Rocco russo, elena scarpato.

4 Department of Translational Medical Sciences-Section of Pediatric, University Federico II, 80100 Naples, Italy

Antonio Di Mauro

Antonella vita di stefano, cinthia caruso, giovanni corsello.

5 Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties “G. D’Alessandro”, University of Palermo, 90100 Palermo, Italy

Annamaria Staiano

Associated data.

Data available at Dr Bozzola’s study.

In recent years, social media has become part of our lives, even among children. From the beginning of COVID-19 pandemic period, media device and Internet access rapidly increased. Adolescents connected Internet alone, consulting social media, mostly Instagram, TikTok, and YouTube. During “lockdown”, the Internet usage allowed communication with peers and the continuity activities such as school teaching. However, we have to keep in mind that media usage may be related to some adverse consequences especially in the most vulnerable people, such as the young. Aim of the review is to focus on risks correlated to social media use by children and adolescents, identifying spies of rising problems and engaging in preventive recommendations. The scoping review was performed according to PRISMA guidelines, searching on PubMed the terms “social media” or “social network”, “health”, and “pediatrics”. Excluding articles not pertinent, we found 68 reports. Out of them, 19 were dealing with depression, 15 with diet, and 15 with psychological problems, which appeared to be the most reported risk of social media use. Other identified associated problems were sleep, addiction, anxiety, sex related issues, behavioral problems, body image, physical activity, online grooming, sight, headache, and dental caries. Public and medical awareness must rise over this topic and new prevention measures must be found, starting with health practitioners, caregivers, and websites/application developers. Pediatricians should be aware of the risks associated to a problematic social media use for the young’s health and identify sentinel signs in children as well as prevent negative outcomes in accordance with the family.

1. Introduction

Media device use is increasing year by year in Italy as well as in many other countries. An ISTAT report referred that in 2019, 85.8% of Italian adolescents aged 11–17 years regularly used smartphones, and over 72% accessed Internet via smartphones [ 1 ]. Almost 95% of Italian families with a child had a broadband internet connection [ 2 ]. Internet connection was mostly used to communicate with friends and to use social networks [ 1 ]. In 2020, COVID-19 pandemic represented one of the greatest disruptions for everybody’s everyday life, in Italy as well as all around the world. From the beginning of the pandemic period, media device and Internet access rapidly increased. In line, a 2021 CENSIS report revealed an even progressive increment of smartphone use by adolescents, which reached 95% [ 3 ]. In particular, the majority of adolescents (59%) admitted they use smartphone even more frequently than in the past with a daily use of more than 3 h in 46% of cases. Adolescents connected Internet alone (59%), consulting social media, mostly Instagram (72%), TikTok (62%), and YouTube (58%) [ 4 ]. In this context, social interaction over the Internet or simply social network consulting may play an important part in the lives of many young people, influencing them and their relationship with self-esteem and well-being [ 5 ]. Not being guided and monitored in Internet fruition, the young may be exposed to several risks, including cyberbullying which affects 7% of children aged 11–13 years and 5.2% of 14–17 years old adolescents or stalking which affects more than 600 minors in Italy. On social media, the young are more vulnerable and may display risk behavior, including pertaining substance abuse, sexual behaviors, or violence [ 6 ].

On the other hand, media and social networks are, actually, present in almost any house and are considered a great resource for anybody, including children and adolescents. Especially during “lockdown”, the Internet usage allowed communication with peers and the continuity activities such as school teaching. Social media services enable various form of communication verbally or visually by internet-based networking, bringing people together, facilitating instant connection and interaction, such as a like or a comment on something [ 7 ]. There was also a “school” use of smartphones and social media during lockdown which represented a tool of information and education [ 8 ].

In line, websites and applications that enable users to create and share content or to participate in social networking may be currently use as a definition of a social media. Facebook launched in 2004 and Twitter in 2006 were the first social media introduced, rapidly followed by many others [ 9 ]. Actually, Facebook with 2.9 billion monthly active users, YouTube with 2 billion, Instagram with 1.5 billion, and TikTok with 1 billion are the most accessed social media in the world [ 10 ]. As social media are spreading in every day’s life, regulatory models are required to address a broad range of challenges social media pose to the community, including privacy and protection of sensitive data.

Media usage is related to some adverse consequences especially in the most vulnerable people. The health emergency had a strong impact on the mental and psychological health of adolescents causing changing in their routine and daily activities. Forced isolation increased anxiety and stress especially in the most fragile individuals, such as children and adolescents, leading to a change in habitual lifestyles. The greatest risk was that of taking refuge in excessive use of smartphones, electronic devices, and social networks, running into a “digital overdose” [ 11 ].

A recent survey conducted by the Italian Society of Pediatrics in collaboration with State Police and Skuola.net investigated the relationship with media devices in times of pandemic, investigating the habits of adolescents on the use of media and social networks, underlined that 15% of them declared they “cannot stay without” their own media device [ 1 ].

The aim of the review is to focus on risks correlated to social media use by the young, identifying spies of rising problems, and engaging in preventive recommendations.

2. Materials and Methods

This scoping review has been conducted by The Italian Pediatric Society Scientific Communication Group in order to provide an overview of a complex research area. The aim is reviewing international literature disguising about social media and their effect on the pediatric age, including minors less than 18 years, to underline possible risks found so far, identifying the signs of a dangerous use, and to eventually give new recommendation based on these findings.

We define a risk as the possibility of something unfavorable happens, as an effect or an implication of social media usage and which may potentially affect human health. This scoping review has been performed according to the PRISMA Extension guidelines for Scoping Reviews [ 12 ].

An electronic search was undertaken on PubMed database on 23 January 2022. To avoid missing results that may be of note for our revision study, constructing our search in PubMed, we used all of the important concepts from our basic clinical question, avoiding unnecessary filters.

So, the search terms “social media”, “health”, and “pediatrics” in text or title/abstract were used, with the time span set as “all years”. The search on the selected database has produced n 651 among articles and reviews. Another research was made using “social network”, “health” and “pediatrics” as search terms in text or title/abstract, with the time span always set as “all years”. It resulted in 354 articles/reviews.

The two research were downloaded from PubMed and then uploaded to the web application “Rayyan” [ 13 ], a website used to screen and analyze articles, specific for writing reviews. Additional articles for potential inclusion were identified in a second stage by hand searching the reference lists in relevant articles.

Studies were considered eligible for this scoping review if they met the following inclusion criteria:

• - Full-length articles or reviews.
• - Pertaining to children and adolescents up to 18 years old.
• - Negative impact on a pediatric population using social media.
• - Social media meant as forms of electronic communication.

The exclusion criteria were:

• - Reports not in English.
• - Duplications.
• - Not pertinent field of investigation (e.g., use of the social media to promote healthcare, benefits of social media, social media used to debate on health-related issues, and social network meant as real social interactions).
• - The population analyzed was adult (>18 years).
• - The population had previous pathologies.

To reduce errors and bias, two researchers independently, two researchers conducted the screening process to identify articles that met all inclusion criteria. Using the web application “Rayyan” [ 13 ], duplicates were removed, then titles and abstracts were analyzed to exclude distinctly irrelevant articles. Finally, the eligibility of the articles was confirmed by evaluating the full text. Disagreements regarding inclusion/exclusion were settled by discussion between the researchers.

Relevant articles were selected on the web application “Rayyan” and grouped together based on the issue they were dealing with. Afterwards, data were compiled in a Microsoft Excel spreadsheet to calculate frequencies and percentages of the problems related to social media use, found in the research.

All the 1005 documents have been reviewed for relevance and eligibility.

As shown in the Figure 1 , through the help of the web application “Rayyan” [ 13 ] we removed before screening 9 duplicates, 25 foreign language works, and 49 publications dated before 2004. We excluded paper published before 2004, the year of Facebook foundation, because before that year “social networks” was a term used to mean “social interactions in real life”, as they were not pertinent to our research.

Flow chart of the selection process. * automation tools were used: 6 records were excluded by automation tools and 3 were excluded by authors. Twenty-five records were excluded because they were not written in English, these were identified using automation tools, but then checked by authors. ** 49 records were removed because they were published before 2004, and no social network existed before that year.

According to PRISMA guidelines [ 12 ], of the 922 works identified, all abstracts were analyzed, and 832 records were excluded. Around 66% of the excluded records were dealing with other topics (e.g., vaccines, promoting health by social media, social networks meant as real social interactions, and social lockdown during SARS-CoV-2 period), a percentage of 28% of the records corresponded to a wrong population: mostly parents, pregnant women, young adults, or children with pathologies (e.g., ADHD). About 6% of the excluded studies used social media tools to recruit people in their studies or to deliver questionnaires.

In conclusion, 90 were the records to be analyzed reading their full-length articles. The whole article of four of them has not been found (“reports not retrieved”), arriving at 86 reports assessed for eligibility. Figure 1 presents the flow chart of the selection process, adapted from PRISMA guideline [ 14 ].

Of the 86 reports attained, we read the whole length articles and then excluded 20 studies.

Of these twenty, 6 were excluded because not leading to any conclusion; 13 were dealing with wrong topics, such as: doctors’ social media knowledge; social lock down during the pandemic; social media marketing; underage and privacy; survey on how social media is perceived by adolescents; time consumed on social media; predictor factors of problematic social media use. Finally, one was not included because it focused on parents and families.

Searching through the cited studies in the included reports, two reviews which were not initially included in the research were added.

With 68 included reports analyzed, there were 15 reviews; of these two were systematic reviews, one validation study, and one editorial. Cross-sectional studies and longitudinal studies have been considered, eight and nine, respectively.

Many articles reported more than one issue correlated to social media use. The most frequent problems involved mental health, followed by diet and weight problems. Table 1 shows the problematic topics found to be related to social media use in children and adolescents and their prevalence, expressed as percentage, over the 68 reports analyzed.

Social media health related problems in a pediatric population. This table shows the issues found in this scoping review. Depression was argued in 19 reports, being the main topic found (27.9% of the whole study). Diet associated problems were discussed in 15 reports, cyberbullying in 15, psychological problems in 14, sleep related problems in 13, addiction in 10, anxiety in 10, sex related problems in 9, behavioral problems in 7, body images distortion in 6, reduced physical activity and related problems has been reported in 5 reports, online grooming in 3 reports, sight problems in 3, also headache in 3, and dental caries in total of 2 articles.

The most frequent problems found are related to mental health: depression, anxiety, and addiction.

Other problems are related to sleep, diet and nutrition, cyberbullying, psychological aspects, behavioral problems, sex, body image perception, physical activity, online grooming, sight, headache, and dental caries.

4. Discussion

4.1. social media and depression.

We identified 19 publications reporting a relationship between social media use and depression [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Table 2 summarized the main finding regarding each article. Out of them, four investigated the impact of COVID 19 pandemic on both social media use and depression ( Table 2 ).

Social media and depression.

4.1.1. Before COVID-19 Pandemic

Investigating the impact of social media on adolescents’ wellbeing is a priority due to a progressive increase in mental health problems or addiction and access to Emergency Department [ 15 ]. As Chiu and Rutter stated, there is a positive relationship between internalizing symptoms, such as depression and anxiety, and social media use [ 15 , 16 ]. Depression is connected to a rapidly increased of digital communication and virtual spaces, which substitute face-to-face contact by excessive smartphone use and online chatting. The more time adolescents spend on social device the higher levels of depression are found out. In this sense, social media are representing a risk factor for depression in the young. Depression, anxiety, and behavioral disorders are among the leading causes of illness and disability among adolescents [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. Key findings which correlate to depression regarding social media exposure are repeated activities such as checking messages, investment, and addition [ 23 ]. The findings were similar all over the world.

For example, in Sweden, spending more than 2 h on social media was associated with higher odds of feeling [ 20 ]. In Egypt, as well, students who have problematic Internet use, have higher psychiatric comorbidities, such as depression, anxiety, and suicidal tendency [ 24 ].

Social media addiction and more precisely Facebook addiction was linked not only to depression but even to dysthymia, so that the expression “Facebook depression” was coined to identify a relationship between depression and social networking activity [ 15 , 25 , 26 ]. Individuals suffering from Facebook depression may be at an increased risk of social isolation and may be more vulnerable to drugs or behavioral problems [ 26 ].

Internet penetrance and connectivity are also connected to cyberbullying which can lead to depression and suicidality [ 27 , 28 , 29 ].

On the other side, physical activity may decrease depression and anxiety, potentially protecting the young against the harmful effect of social media abuse [ 16 ].

At last, even if a positive correlation between internalizing symptoms and media use device is noted, Hoge states that there is also evidence that social media communication may improve mood and promote health strategies in some occasions [ 18 ].

Finally, even if evidence revealed that social media use is linked to poor mental health, the relationship between social media and depression in adolescents is still to be completely understood. It is still unclear whether social media use leads to more depression or if these depressive symptoms cause individuals to seek out more social media, which could feed into a vicious cycle [ 16 ]. Keles’s conclusion as well suggest defining the relationship between internalizing symptoms and social media use as an association and not a causative effect [ 23 ].

4.1.2. After COVID 19 Pandemic

During COVID-19 pandemic, the state of emergency and social isolation determined an increase in time on screen not only as a source of online education, but to continuously access social media. According to recent data, a percentage of 48% of adolescents spent a mean of 5 h per day on social media and 12% spent more than 10 h. Moreover, with that increase in virtual time depression arose [ 30 ].

The degree of social media usage in children is a significant predictor of depression, which increases with each additional hour of social media use [ 31 ].

During the pandemic, depressive symptoms may have been reactive to the context of being afraid of the virus and necessitating social isolation [ 32 ].

However, in this peculiar period, schoolchildren who increased time spent on either smartphones, social media, or gaming had significantly elevated psychological distress, such as depressive symptoms, than those with decreased time spent on these internet-related activities [ 33 ].

4.2. Social Media and Diet

Out of the reports, 15 dealt with the association of social media use and diet [ 21 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ]. The problems were related to junk food marketing (9 reports) [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ] obesity (4 reports) [ 21 , 41 , 42 , 43 ], unhealthy eating behaviors (3 reports) [ 44 , 45 , 46 ], and alcohol marketing (2 reports) [ 21 , 47 ]. In Table 3 the retrieved articles dealing with social media and diet, and their major findings are presented ( Table 3 ).

Social media and diet.

4.2.1. Before COVID-19 Pandemic

Junk food marketing.

Reports found that children are exposed to the marketing of unhealthy foods on social media and to their persuasive techniques. Digital marketing represents a major threat for children and adolescents in Mexico, because of its persuasive techniques. Cola and soft drinks, sweetened juices and in general the so-called junk food have high followers on Facebook and Twitter. [ 34 ]. This may cause an increase in children’s immediate consumption of the promoted product, unhealthy behaviors and may led to obesity, as confirmed by several studies [ 34 , 35 , 36 ]. Reports agree on the youth major vulnerability to unhealthy food advertisement, including digital marketing, sponsored content, influencers, and persuasive design [ 34 , 35 , 36 ]. This contributes to the obesity epidemic [ 36 ].

Major social media platforms do not have comprehensive policies in place to restrict the marketing of unhealthy foods on their platforms [ 36 , 37 ]. Therefore, exposure to the marketing of unhealthy products, on social media may be considered a risk factor for related unhealthy behaviors.

Analysis of the advertising policies of the 16 largest social media platforms proved them ineffective in protecting children and adolescents from exposure to the digital marketing of unhealthy food [ 37 ].

Among social media, YouTube is particularly worrying considering the affinity of the young toward the platform. Unhealthy food advertisements predominate in YouTube content aimed towards children. In fact, analysis of advertisements encountered in YouTube videos targeted at children revealed that food and beverage ads appeared most frequently, with more than half of these promoting unhealthy foods [ 38 ].

As confirmed by an Irish study, adolescents are very attracted to junk food advertisements and are likely to share comments on their network: generalized linear mixed models showed that advertisements for unhealthy food evoked significantly more positive responses, compared to non-food and healthy food. Of all the advertising, they see in social media, they view unhealthy food advertising posts for longer [ 39 ]. This confirms the vulnerability of children towards ad and digital marketing.

Moreover, it has been demonstrated that adolescent heavy social media users (>3 h/day) are more willing to engage with food ads compared to light social media users, and are more willing to “like” Instagram food ads featuring many “likes” versus few “likes”, demonstrating the power of social norms in shaping behaviors. Adolescents interact with brands in ways that mimic interactions with friends on social media, which is concerning when brands promote unhealthy product. [ 40 ]. There is a need of more strict policies to limit digital marketing, which is becoming more and more intense, especially towards children and adolescents.

4.2.2. After COVID-19 Pandemic

During the COVID-19 pandemic, this phenomenon even increased. In fact, the combination of staying at home, online education and social media usage have all caused screen time to surge and the food industry has been quick to identify this change in their target audience and has intensified online advertising and focused on children. The COVID-19 experience led to an increase in risk and severity of inappropriate behavioral eating habits, affecting the health and weight [ 41 ].

4.2.3. Before COVID-19 Pandemic

Social media is the first independent risk factor for obesity in primary school children and the second for high school students. In both primary school and high school models, children’s social media use has the highest impact on child’s BMI [ 42 ]. In addition, heavy media use during preschool years is associated with small but significant increases in BMI, especially if used ≥ 2 h of media per day [ 21 ].

4.2.4. After COVID-19 Pandemic

Obesity and social media correlated through junk food advertisements [ 41 , 43 ]. During COVID 19 pandemic poor quality food, energy-dense, and nutrient-poor products consumption increased, leading to the risk of overweight and obesity. The phenomenon has been called “Covibesity” [ 41 ].

4.3. Unhealthy Eating Behavior

Some social media contents promote pro-anorexia messages [ 44 , 45 , 46 ]. These messages are no longer limited to websites that can be easily monitored, but instead have been transferred to constantly changing media such as Snapchat, Twitter, Facebook, Pinterest, and Tumblr. Consequently, pro-eating disorder content has become more easily accessible by the users. Pro-anorexia website use is correlated with a higher drive for thinness, lower evaluations of their appearance, and higher levels of perfectionism, and all correlates with eating disturbances [ 44 , 46 ].

In detail, there is a real bombardment of unhealthy messages on media promoting low-nutrition aliments and sugar-sweetened drinks [ 45 ].

It is likely that the suboptimal quality of online information on social media platform contributes to the development of unhealthy eating attitudes and behaviors in young adolescent internet users seeking nutritional information. They look for nutritional information on internet sources such as commercial websites or social media in order to lose weight. In this occasion, they may be exposed to higher risk of eating disorders due to the high quantity of misinformation. Moreover, they may find dangerous methods to rapidly lose weight with possible harm for their health [ 46 ].

Literature agrees on the risk of time spent on social media as well as on the poor quality and reliability of weight loss information on media [ 44 , 45 , 46 ].

4.4. Alcohol Marketing

Adolescents identify drinking brands to peculiar images of ideal adults. Brands know well this underlying psychological mechanism and promote that identity adolescents seek, with specific advertisement on social media [ 47 ].

Studies have shown that exposure to alcohol in TV or movies is associated with initiation of this behavior. The major alcohol brands have a strong advertising presence on social media, including Facebook, Twitter, and YouTube. Several studies underlined risky health behaviors, such as illegal alcohol use or overuse. Evidence suggests that peer viewers of this content are likely to consider these behaviors as normative and desirable. Therefore, targeted advertising via social media has a significant effect on adolescent behavior [ 21 ].

4.5. Social Media and Cyberbullying

We identified 15 publications reporting a relationship between social media use and cyberbullying [ 21 , 22 , 25 , 26 , 27 , 28 , 29 , 45 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ]. Table 4 summarized the main finding regarding each article ( Table 4 ).

Social media and cyberbullying.

Cyberbullying may be defined as any behavior performed through electronic or digital media by individuals or groups that repeatedly communicate hostile or aggressive messages intended to inflict harm or discomfort on others. Compared to bullying, cyberbullying may be even more dangerous as victims can be reached anytime and in any place. Moreover, anonymity amplifies aggression as the perpetrator feels out of reach.

Moreover, the ability to hide behind fake names provides bullies the opportunity to communicate in content and language they would not use in front of people [ 26 , 48 , 49 ]. As confirmed by Shah et al., the anonymity of cyberbullying increases the risk for inappropriate behaviors among adolescents [ 50 ].

In literature, cyberbullying has been identified in phone calls, text messages, pictures/video clips, emails, and messaging apps. This is a great public health concern: in Italy, 2015 ISTAT data showed that 19.8% of 11–17 years old internet users report being cyberbullied [ 49 ].

This phenomenon is increasing. In fact, the number of adolescents being cyberbullied at least once in their life increased from 20.8% in 2010 to 33.8% in 2016 [ 50 ].

Victims of bullies exhibit increased depressive symptoms, anxiety, internalizing behaviors, externalizing behaviors, and greater academic distractions [ 21 , 22 , 25 , 27 , 28 , 29 , 51 ].

Cyberbullying has been associated with higher risks of depression, paranoia, anxiety, and suicide than the traditional form of bullying [ 21 , 22 ]. According to a metanalysis of 34 studies, traditional bullying increased suicide ideation by a factor of 2.16, whereas cyberbullying increased it by a factor of 3.12 [ 39 ].

In adolescence, social media intense or problematic use and frequent online contact with strangers are all independently associated with cyberbullying [ 45 , 52 , 53 ]. In this contest, social media represent a risk factor for cyberbullying and for inappropriate behavior related to it. In fact, problematic social media use is an important driver of cyberbullying victimization and perpetration, especially among girls [ 50 , 53 ]. The highest percentage is observed in adolescents, aged 13 to 15 years as suggested by literature reviews and, in particular, by Marengo and Uludasdemir [ 53 , 54 ]. However, Marengo also suggests that in presence of social support, the phenomenon is attenuated [ 53 ].

Moreover, having daily access to the Internet and the sharing of gender on social media increased the likelihood of cyber victimization among adolescents aged 12–17 years. Those who use Tumblr and Snapchat were found to become victims even more frequently [ 54 ].

4.6. Psychological Problems and Social Media

We identified 14 publications reporting a relationship between social media use and psychological problems [ 17 , 23 , 33 , 45 , 49 , 52 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 ]. Table 5 summarized the main finding regarding each article ( Table 5 ).

Social media and psychological problems.

4.6.1. Before COVID-19 Pandemic

A high use of screen device has been correlated to a low psychological well-being among children and adolescents, especially among females [ 17 ].

For examples, in Canadians adolescents, the prevalence of loneliness was higher for daily computer-mediated communication users than non-daily users [ 55 ]. As well as for cyberbullying, adolescents may benefit from social support, family communication, and interaction to ameliorate feelings of loneliness [ 53 , 55 ]. Boer et al. confirmed that intense user reported more frequent psychological complaints than non-intense user as well as less family and friend support [ 56 ]. In line with this finding, in Lithuania a problematic social media use has been associated with two times higher odds for lower life satisfaction [ 57 ].

Moreover, an intense social media use correlated to either low school well-being and reduced social well-being (decreased family and friends support and relations) [ 56 ].

A relationship between poor life satisfaction, problematic social media use, and lack of social support was found not only in adolescents, but also in children [ 52 , 57 , 58 , 59 , 60 ].

Social media use is also correlated with conduct and emotional problems, attention deficit, peer problems, school impairments, and psychological distress [ 23 , 45 , 61 , 62 ].

Social networks and media device use correlate to low academic outcomes, reduced concentration, and procrastination. In fact, problematic smartphone use correlates to a surface approach to learning rather than to a deep approach, leading to reduced creativity, organization skills, own thinking, and comprehension of information [ 49 ].

4.6.2. After COVID-19 Pandemic

During this COVID-19 pandemic, primary school children reported significantly higher psychological distress than the period prior to the COVID-19 outbreak. Studies showed that schoolchildren who increased time spent on either smartphones, social media, or gaming had significantly elevated psychological distress than those with decreased time spent on these internet-related activities [ 33 ].

4.7. Social Media and Sleep

Extended use of digital media screen time correlates with sleep impairment [ 18 , 21 , 22 , 26 , 31 , 43 , 47 , 49 , 57 , 61 , 63 , 64 , 65 ]. Table 6 summarizes the evidence in literature ( Table 6 ). Exposure to screen-based devices, online social networking sites, and video-sharing platforms is significantly associated with sleep-onset difficulties in adolescents [ 18 , 49 ]. Findings from a meta-analysis of 20 cross-sectional studies show 53% higher odds of poor sleep quality among adolescents with consistent bedtime media use [ 63 ]. Moreover, the use of computers and smartphones among adolescents is associated with daytime sleepiness and fatigue, shorter sleep duration, later bedtime, and unfavorable changes in sleep habits over time [ 22 ]. Smartphones may be easily carried around and even taken to bed. Several sleep disorders correlate to both overall and night phone use among adolescents. It has been demonstrated that social media addiction in school students decreases students’ sleep efficiency [ 61 ]. Use of cellphones, particularly for nighttime texting, and consulting social media were associated with insufficient sleep [ 63 ]. A 5 or more hours daily of media devices use has been related to a higher risk of sleep problems when compared to a 1 h use daily [ 49 ]. This finding is confirmed by Buda who correlates problematic social media with about two times higher odds for a bad sleep quality [ 57 ]. Varghese as well associated social media use with sleep difficulties. Furthermore, YouTube user had two-times higher odds for sleep-onset difficulties [ 63 ].

Social media and sleep.

In addition, it seems that girls suffer more than boys from these sleep problems [ 57 ].

Sleeping problems, especially sleep duration, have been then associated with time spent on screen, problematic behaviors, and higher internalizing and externalizing symptoms [ 64 ].

Even among children, there is a problem with extended use of social media sites, which result in sleep deprivation due to delayed bedtimes and reduced total sleep duration and quality of rest [ 31 , 65 ]. The report by Hadjipanayis as well confirms that sleeping disturbances may be associated with the disruption of circadian rhythms due to the blue light emission from the electronic screen-based media devices [ 26 ]. Negative outcomes including poor school performance, childhood overweight and obesity, and emotional issues have all been associated with sleep deprivation [ 21 , 26 , 43 , 47 ]. Inadequate sleep quality or quantity associated to social media use represents a risk factor for metabolic conditions such as for diabetes, cardiovascular disease and for mental problem, such as depression or substance abuse [ 49 ].

4.8. Social Media and Addiction

Ten reports found correlations between social media use and risk of different types of addictions: with internet [ 17 , 24 , 49 , 51 , 52 , 66 ], with substance abuse [ 15 , 67 ], with alcohol addiction and gaming [ 67 ], with gambling [ 68 ], and with tobacco use [ 69 ]. In Table 7 , the major findings of the related reports are presented ( Table 7 ).

Social media and addiction.

Investigating the impact of social media on adolescents’ wellbeing is a priority due to a progressive increase in mental health problems and access to Emergency Department [ 15 ]. Chiu reported that mental health or addiction related emergency department access increased by almost 90% in ten years mainly among adolescents aged 14–21 years. The increment well correlates to an increase availability of social media [ 15 ].

High screen use associated with internet addiction is also confirmed by O’Keeffe who states that technology is influencing children’s lives from a very young age [ 51 ].

More than 7% of youth have problematic social media use, indicated by symptoms of addiction to social media [ 52 ]. Warning signs of internet addiction can be skipping activities, meals, and homework for social media; weight loss or gain; a reduction in school grades [ 41 ]. In detail: concern, loss of controlling tolerance, withdrawal, instability and impulsiveness, mood modification, lies, and loss of interest have been identified as risk factors for smartphone addiction. Females have almost three times more risk for smartphone addiction than males and it may be related to a stronger desire for social relationships [ 66 ]. Main problems correlated to addiction are low self-esteem, stress, anxiety, depression, insecurity, solitude, and poor scholastic outcomes. Smartphone addiction correlates to both fear of missing out (FOMO) and boredom. FOMO is the apprehension of losing experiences and the consequent wish to remain constantly connected with others, continuously checking social applications. Boredom is defined as an unpleasant emotional state, related to lack of psychological involvement and interest associated with dissatisfaction, to cope with boredom adolescents may seek additional stimulation and compulsively use smartphones [ 49 ].

As well as O’Keeffe, Hawi found out that children are starting to use digital devices at a very young age, and so should be screened for the risk of digital addiction. New scales of early identifications have been developed such as the Digital Addiction Scale for Children, validated to assess the behavior of children 9 to 12 years old in association with digital devices usage. Out of the sample size, 12.4% were identified as at risk of addiction and most of them (62.4%) were male. Nevertheless, results demonstrated that weekday device use among females causes more conflicts [ 66 ].

Different grading scales can test addictions. A study assessed 700 adolescents aged from 14 to 18 years and found out that 65.6% were having internet addiction, 61.3% were gaming addicts, and 92.8% Facebook addicts. Internet addict students had statistically significant higher age, higher socioeconomic scale score, male gender, and lower last year grades in comparison to non-addicts. Depression, dysthymia, suicide, social anxiety, and phobias were common comorbidities in addicted adolescents [ 24 ].

In undergraduate students, disordered online social networking use is associated with higher levels of alcohol craving and in pupils aged from 11 to 13, it is associated with a higher likelihood of being substance users [ 67 ]. In addition, excessive video gaming is associated with increased substance use [ 15 , 67 ].

One report showed greater risk for children and adolescents to develop gambling problems. In fact, the prevalence of adolescent gambling has increased in recent years. Across Europe, self-reported rates of adolescent gambling in 2019 ranged from 36% in Italy to 78% in Iceland. Adolescent problem gambling prevalence ranges from 1.6 to 5.6%. Not only adolescents but also children are widely exposed to gambling advertisements on television and via social media. In recent years, there has been an expansion in sports betting online, and this has been heavily promoted by advertising and marketing attractive to adolescents. Gambling is also promoted to children via social media: children are sharing and re-tweeting messages from gambling companies, they are active in conversations around gambling, and regularly consume and share visual gambling adverts. Lastly, there is also a strong relationship between gaming and gambling: in video games, children pretend to gamble and some video games would ask real money to play [ 68 ].

Finally, there might be a relationship between youth using tobacco and tobacco social media posts. It is not clear if the relationship can be cause-effect or only a correlation. Adolescents who participate in conversations about tobacco in social media by posting positive messages about tobacco are more likely to be past-month tobacco users. Posting even only one positive tobacco-related tweet was associated with greater odds of using cigarettes, e-cigarettes, or any tobacco product, compared to those who did not post positive messages about tobacco [ 69 ].

Finally, social media has been associated to social media use and may represent a risk factor for the young as it interferes with dailies activities leading to unhealthy habits. The easy access to social media by smartphone undoubtedly facilitates addiction.

4.9. Social Media and Anxiety

We identified 10 publications reporting a relationship between social media use and anxiety. Out of them, three investigated the impact of COVID 19 pandemic on social media use and anxiety [ 15 , 16 , 17 , 18 , 22 , 23 , 31 , 32 , 33 , 70 ]. Table 8 summarized the main findings ( Table 8 ).

Social media and anxiety.

4.9.1. Before COVID-19 Pandemic

Evidence agrees that the degree of social media usage in children is a significant predictor of anxiety and perceived stress levels and that it increases with each additional hour of social media use [ 17 , 23 , 31 ]. Anxiety may represent a risk factor for children and adolescents’ health as it influences the way they see their body, the way they feel, and it may impact on social acceptance and relations with peers.

The excessive use of at least one type of screen, including television, computer, social media, and video gaming, has been connected with anxiety symptoms in the pediatric age [ 22 , 23 , 31 ]. Furthermore, in Rutter’s study a significant association between depression and anxiety with social media use has been detached [ 16 ]. Nevertheless, it is still unclear if social media use provoke anxiety or if anxiety is the cause of excessive use of social media [ 16 ]. Emergency department visits for mental health, including anxiety problems, has arisen since 2009, likely linked to the increased use and the harmful effect of social media [ 15 ]. On the contrary, physical activity may protect the young against the harmful effect of social media, preventing depression and anxiety [ 16 ].

In a scientific report, Muzaffar confirmed that an association between anxiety and social media is of note. In detail, increased adolescent generalized anxiety symptoms were associated with increased Facebook use and repetitive Facebook habits. Anxious adolescents may not be able to control their discomfort to the point that they need to regularly go back to check their previous posting on Facebook [ 70 ].

The constant connection to social networks through digital devices, on its side, potentially contributes to feelings of anxiety. Adolescents and children suffering from social anxiety may prefer to interact with texting, instant messaging, and emailing than over face-to-face interactions. However, the behavior may increase risk in individuals vulnerable to social anxiety disorder because substituting digital media for interpersonal communication to avoid feared situations may be reinforced over time, making the person even more avoidant and worsening the symptoms and severity of social anxiety disorder [ 18 ].

However, in some studies, not just overexposure but also underexposure to social media was associated with adolescent anxiety, depression, and suicidal ideation [ 22 ].

4.9.2. After COVID-19 Pandemic

Screen time and social media use have increased during the pandemic. Social media has been helpful during lockdown to keep social relationships and not to discontinuate school activities. However, an excessive Internet use may negatively affect children and adolescents’ well being. So, during social lockdown, an elevated psychological distress and anxious symptoms have been described in schoolchildren who increased time spent on screen [ 32 , 33 ]. Children who increased by 15 or 30 min daily the time spent on internet presented a high level of psychological distress.

4.10. Social Media and Sex Related Problems

Studies have found social media use related to sexual problematic behaviors such as early sexual activity, exposure to pornography, and sexting. [ 21 , 22 , 26 , 50 , 51 , 71 , 72 , 73 , 74 ]. Table 9 summarizes the results ( Table 9 ).

Social media and sex related problems.

The prevalence of sex related problems cannot be accurately recorded as for a wide range of definition and sampling methods and the comparison among reports is difficult.

Especially for girls, higher social media use, associated with lower family affluence and poorer body image, are key to early sexual activity [ 71 ].

Social media use was found to be significantly associated with risky sexual behavior among pre-college students in Ethiopia. Facebook, Instagram, YouTube, and other platforms have been identified as a factor that alters adolescent’s perception and influences them to engage in risky sexual behavior. Those who view sexually suggestive Facebook photos have a higher chance of having unprotected sexual intercourse and sex with strangers [ 72 ].

Moreover, youth can be exposed to unwanted sexual material online, including unwanted nude pictures or sexually explicit videos through means such as pop-up windows or spam e-mails [ 73 ].

Children exposed to inappropriate sexual content are prone to high-risk behaviors in subsequent sexual encounters. [ 22 ] Sexting activities may also affect emotional and social wellbeing of adolescents; it is correlated to depression and risky health behaviors, such as substance use, alcohol consumption, and suicide [ 26 , 50 ]. The odds of risky sexual behavior were 1.23 higher in social media user than in other students [ 72 ]. Furthermore, on the internet, pornography is readily accessible by media device, so that Wana found out that 7% of students use social media for pornography. In most cases, adolescents admit they intentionally viewed materials [ 74 ]. Pornographic media depict a fantasy world in which unrealistic encounters result in immediate sexual gratification, and intimate relationships are nonexistent. Repeated exposure of the adolescent brain to the world of online pornography can make it difficult for adolescents to develop mature healthy sexual relationships [ 22 ].

Internet pornography usage has been documented in adolescents before the age of 18. Online pornography is often the first source of sex education for many adolescents, and exposure to violent pornography increases the odds of sexually aggressive behavior [ 50 ]. Peer advice as well as substance abuse are significant predictor for risky sexual behavior [ 72 ].

Finally, among adolescents 10–19 years of age, the rate of sexting ranges from 5 to 22% [ 50 , 72 , 74 ].

Sexting is the use of media to send nude or sexualized contents such as texts, photos, or videos. An extensive sharing of these contents through technology has been connected with a negative impact on the emotional and social wellbeing of adolescents involved. An earlier sexual debut such as the use of drugs and promiscuity have been all associated to the excessive use of sexting. It can also cause spreading of sexual content material without consent, to a third party as a method of bullying or revenge [ 21 , 26 , 51 , 74 ].

4.11. Social Media and Behavioral Problems

Out of the reports, seven explored the influence of social media and behavioral problems [ 22 , 49 , 64 , 75 , 76 , 77 , 78 ]. Table 10 outlines the highlighted findings ( Table 10 ). Behavioral outcomes usually cover five areas, including hyperactivity/inattention, emotional symptoms, conduct problems, peer relationship, and pro-social behavior.

Social media and behavioral problems.

For children aged 10–15 years old, limited time on social media has no effect on most emotional and behavioral outcomes (and can even positively impact social relationships), while there are strong negative associations between very long hours on social media and increased emotional distress and worse behavioral outcomes, which continue for several years [ 75 ].

In accordance to McNamee, the study by Okada conducted in Japan [ 76 ] among children aged 9–10 years old highlighted that mobile devices usage time of less than 1 h was a protective factor for behavior problems in boys. Instead, the usage time of 1 h or more was a risk factor in girls. Among girls, a dose–response positive association was found between duration of mobile devices usage and total difficulty score. A U-shaped association was found between duration of mobile devices usage and behavioral problems in boys: moderate use of mobile devices might be a tool for relaxation or alleviating distress through interactions with peers. However, in the subscale analysis, boys who use two or more hours of mobile devices showed higher risk of emotional problems and peer problems [ 76 ].

Moreover, the social media violent content exposure may be a risk factor for violent and aggressive behaviors. In this context, levels of aggression are directly proportional to exposure of types of violent media content. Electronic and social media showing contents with fights, stealing, dead bodies, and people’s belongings being destroyed influence young viewers, as per observational-learning theory, making them believe that reacting aggressively in response to perception of any offense is acceptable [ 77 ].

In line with Tahir’s report, Maurer underlined a significant association between exposure to media violence and aggressive behavior, aggressive thoughts, angry feelings, and physiologic arousal. Media exposure is also negatively related to personal adjustment and school performance and positively related to risk-taking behaviors [ 22 ].

Another study confirmed that longer the time spent on screens, higher the risk for behavioral problems among children 9–10 years old, and depending on the content type visualization, the risk for an aggressive and rule-breaking behavior. This association was mediated by sleep duration: longer sleep duration was associated with fewer problem behaviors [ 64 ].

Challenges and risk-taking attitudes are frequent in child and youth culture. However, online challenges take on new meanings when mediated by digital sociability; they appear as a powerful communicative resource to reaffirm belonging, recognition, and audience adherence. They are a media strategy adopted by youth in the construction of an internet-mediated identity in which risk and violence are crucial devices in building a self-image capable of maintaining an audience. Nevertheless, they can involve potential self-inflicted injuries to participants, with risks ranging from minor to even lethal [ 78 ].

Finally, an emerging problem is the social phenomenon called Shakaiteki Hikikomori (social withdrawal). Most of them are males and they usually experience a social reclusion range from 1 to 4 years. They refuse to communicate even with their own family and spend even more than 12 h a day in front of a screen [ 49 ].

4.12. Social Media and Body Image

On social media platforms such as Facebook, Snapchat, and Instagram, body image has become an important topic [ 17 , 25 , 45 , 46 , 50 , 73 ]. Table 11 summarized the evidence. ( Table 11 ). People post their most flattering photos and view those of others, creating an online environment that could be damaging to body image acceptance. Spending time on social media puts adolescents under a higher risk of comparing themselves to models that are more attractive. As a result, these unfavorable social comparisons of physical appearance may exacerbate body image apprehension [ 17 , 45 ].

Social media and body image.

Moreover, beauty trends are constantly reinforced through social media networks and image-editing tools are often used to alter images to fit beauty standards. Teenagers who, perhaps, are not aware of these digital changing made in commercial photos may become insecure of their image. This may reduce self-esteem and body satisfaction, mainly among adolescent girls, developing body image concerns, engaging in weight-modification behavior, and potentially developing eating disorders. Nowadays, adolescents, and, in particular, girls, need to fit “social media” standard for photo posting; they use to modify photos with specific programs in order to respect society beauty standard. In fact, 28% of girls aged 8–18 years admit to editing their photos to make themselves look more attractive prior to posting online [ 50 ].

In addition to social media causing body image problems, adolescents with body image misperception may look on the internet for advice on how to lose weight quickly. However, the suboptimal quality of online information contributes to the development of unhealthy eating attitudes and behaviors in young adolescents. It may be that the content of these sites promotes eating disorders by providing unhealthy weight loss advice [ 46 ].

Furthermore, the desire of perfection and selfie mania with repeated selfie can cause depression and self-harm. This is a typical symptom of body dysmorphic disorder [ 73 ].

Finally, this association between the use of social media, self-esteem and body image can be a correlation and not a cause-effect relation: girls with lower self-esteem and sensitive to body image complains may use social media more frequently than girls with a higher level of self-esteem. For example, users can make a “selective self-presentation” where they show themselves only in a positive way on their social media profiles [ 25 ].

4.13. Social Media and Physical Activity

Evidence supports a correlation between social media and physical activity [ 45 , 49 , 57 , 73 , 79 ]. Excessive use of smartphones and other digital devices can also cause physical problems, such as a more sedentary lifestyle [ 45 ], which is positively associated with childhood obesity. In addition, non-physiological postures assumed while using smartphones may lead to cervical rigidity and muscle pain resulting in neck strain or “Tech Neck”. Moreover, “texting thumb” is a form of tendinitis that comes from overusing the thumb from excessive texting, video gaming, and web browsing using a smartphone [ 49 , 73 ].

An Australian study found that non-organized physical activity declines between 11 and 13 years, especially in children with a large increase in activities of texting, emailing, social media, and other internet use [ 79 ].

Another study showed that problematic social media use is related to lower levels of vigorous physical activity, especially in girls [ 57 ].

In Table 12 are listed the reports related to this topic and their major content ( Table 12 ).

Social media and physical activity.

4.14. Online Grooming

Online grooming may be defined as a situation in which an adult builds a relationship with a minor finalized to a sexual abuse using social media. [ 47 , 80 ]. The risk of developing post-traumatic stress disorder in the victims is of note and may affect mental and well-being of children and adolescents [ 80 ].

Children are more vulnerable online as they often escape their parents’ control and may be more willing to share information or pictures about themselves than in real life.

Online grooming, differently to offline sexual abuse, is simpler to perpetrate, due to internet’s technology and accessibility. Furthermore, often the perpetrator misrepresents himself as another child or teenager, in order to establish a trusting relationship [ 21 ].

Teenage girls appear to be more at risk, even if the proportion of male victims is considerable too. In general, minors with problematic internet use are at greater risk of being groomed.

Sexual solicitation has been found to be more common in children spending longer time on internet on weekdays, being involved in sexting, having strangers in social networks friends list, playing online games, and chats. The risk is high even for adolescents whose curiosity and unconsciousness set them at risk of being deceived [ 80 ].

Table 13 presents the reports related to this topic and their major content ( Table 13 ).

Social media and online grooming.

4.15. Social Media and Sight

Studies have investigated the risk of social media on sight, in terms of visual imbalance [ 22 , 49 , 73 ]. Evidence underlines that children can develop ocular disorders from excessive screen time, including myopia, eye fatigue, dryness, blurry vision, irritation, burning sensation, conjunctival injection, ocular redness, dry eye disease, decreased visual acuity, strain, fatigue acute acquired concomitant esotropia, and macular degeneration. During smartphone use, there is a reduction of the blink rate to 5–6/min that promotes tear evaporation and accommodation, leading to dry eye disease [ 49 , 73 ].

In addition, excessive screen time and less time spent outdoors may lead to early development of myopia, particularly with smartphone and tablet use [ 22 ].

Table 14 presents the reports related to this topic and their major content ( Table 14 ).

Social media and sight.

4.16. Social Media and Headache

There are increased complaints of headaches related to staring at a screen for too long [ 62 , 73 , 81 ]. Reports dealing with social media and headache are listed in Table 15 ( Table 15 ).

Social Media and headache.

Headache is actually the most common neurologic disorder in the population, children and adolescents included [ 81 ]. It may negatively impact on children and adolescents’ well-being, leading to stress, tiredness, anxiety, and bad mood. Time of usage of media device has been directly connected to headache: in particular, adolescents using more than 3 h a screen have a significantly higher risk of headache compared with those using a device for less than 2 h ( p < 0.001). Spending even 2–3 h with a computer significantly increases the chance of suffering a headache in comparison with those using a computer for less than 2 h ( p < 0.01). Excessive use of electronic devices is considered a risk factor, especially for the development of migraine-type headache ( p < 0.05) [ 81 ].

According to recent studies, headache and somatic symptoms have been found mostly in patients with problematic social media usage, compared with non-problematic peers. There is a consistent association between the problematic use of social media and adolescent psychosomatic health [ 62 , 73 ].

4.17. Social Media and Dental Caries

The association between use of internet and social media has been studied in literature [ 35 , 82 ]. Table 16 summarizes the main findings ( Table 16 ).

Social media and dental caries.

The association between use of internet social media to obtain oral health information and dental caries has been highlighted in Almoddahi’s report [ 82 ]. In detail, problematic internet use has been associated with unhealthy lifestyles, poor oral health behaviors, and more oral symptoms such as toothache, bleeding gums, and poor self-perceived oral health. Caries and junk food have been both connected to excessive internet use and ads [ 82 ]. Therefore, social media may be a risk factor for caries, poor oral health, and dental outcomes.

In line with Almoddahi, Radesky underlines that advertisements on social media promote intake of foods that contribute to dental caries, such as fast food and sugar beverages [ 35 ]. Nevertheless, evidence suggests that smartphone applications may improve health and oral health when internet-based health interventions are in place. Delivering oral health information via social media may increase tooth brushing and dental outcome [ 82 ].

5. Limitations

From the literature, it is not possible to decide whether social media use causes internalizing symptoms and problematic behaviors examined in this manuscript or whether children and adolescents suffering from depression, anxiety, or other psychological distress are more likely to spend time on social media. We can just state that there is an association between social media use and health problems, but that is not necessarily cause-effect. Moreover, the articles included are different, ranging from reviewers to clinical studies to letters and to editors, so that it may be difficult to accurately compare them. Third, as specified in the materials and methods, we excluded reports not in English letter and not published in PubMed.

Nevertheless, through our manuscript we contribute to the existing literature to highlighting the impact of social media use on adolescents, providing advices to pediatricians in everyday practice.

6. Conclusions

Social media is increasingly being used by children and adolescents, especially during COVID-19 pandemic and the health emergency. Although social media use demonstrated to be of utility, an excessive or non-correct use may be a risk factor for mental health, including depression, anxiety, and addiction.

Social media use may also correlate to a non-adequate nutrition with consumption of junk food marketing leading to weight gain, obesity, dental caries, and unhealthy eating behaviors. Associations have been found also with increasing physical problems due to sedentary lifestyle, obesity, and non-physiological postures. On the other hand, social media can cause problems with body image visualization and acceptance, especially in young adolescent girls with lower self-esteem, who may look for contents for losing weight rapidly, and this can help the extension of anorexia disorders.

Children and adolescents who use social media for many hours a day, are also at higher risk for behavioral problems, cyberbullying, online grooming, sleep difficulties, eye problems, (such as myopia, eye fatigue, dryness, blurry vision, irritation, burning sensation, conjunctival injection, ocular redness, and dry eye disease), and headache. Moreover, uncontrolled social media use, can lead to sexting, exposure to pornography, exposed to unwanted sexual material online, and early sexual activity. Social media users meet more online risks than their peers do, with an increased risk for those who are more digitally competence.

Public and medical awareness must rise over this topic and new prevention measures must be found, starting with health practitioners, caregivers, and websites/application developers. Families should be educating on the dangers and concerns of having children and adolescence online. Prerequisite to inform families how to handle social media is to educate those responsible for training, including health practitioners. In detail, pediatricians should be reminded to screen for media exposure (amount and content) during periodic check-up visits. They need to keep in mind a potential correlation of problematic social media use with depression, obesity and unhealthy eating behavior, psychological problems, sleep disorder, addiction, anxiety, sex related problem, behavioral problem, body image, physical inactivity, online grooming, sight compromising, headache, and dental caries. Pediatricians can also counsel parents to guide children to appropriate content by consulting ratings, reviews, plot descriptions, and by a previous screening of the material. They should inform parents about the potential risk of digital commerce to facilitate junk food, poor nutrition and sweetened aliments, facilitating overweight and obesity. On the contrary, a healthy diet, adequate physical activity and sleep need to be recommended. Pediatricians may also play a role in preventing cyberbullying by educating both adolescent and families on appropriate online behaviors and on privacy respect. They should also promote a face-to-face communication and to limit online communication by social media. Pediatricians may encourage parents to develop rules and strategies about media device and social media use at home as well as in every day’s life.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization: E.B.; methodology: S.B.; formal analysis G.S. and A.D.M.; Resources R.A. and R.R.; writing E.S. and A.V.D.S.; visualization: C.C.; editing: A.S.; supervision G.C. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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• Government reform
• Civil service reform
• Election guidance for civil servants
• Cabinet Office
• Civil Service

General election guidance 2024: guidance for civil servants (HTML)

Updated 23 May 2024

© Crown copyright 2024

This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] .

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This publication is available at https://www.gov.uk/government/publications/election-guidance-for-civil-servants/general-election-guidance-2024-guidance-for-civil-servants-html

1. General elections have a number of implications for the work of departments and civil servants. These arise from the special character of government business during an election campaign, and from the need to maintain, and be seen to maintain, the impartiality of the Civil Service, and to avoid any criticism of an inappropriate use of official resources. This guidance takes effect from 00:01 on 25 May 2024 at which point the ‘election period’ begins. The Prime Minister will write separately to Ministers advising them of the need to adhere to this guidance and to uphold the impartiality of the Civil Service. 

2. This guidance applies to all UK civil servants, and the board members and staff of Non-Departmental Public Bodies (NDPBs) and other arms’ length bodies.  

General Principles 

3. During the election period, the Government retains its responsibility to govern, and Ministers remain in charge of their departments. Essential business (which includes routine business necessary to ensure the continued smooth functioning of government and public services) must be allowed to continue. However, it is customary for Ministers to observe discretion in initiating any new action of a continuing or long term character. Decisions on matters of policy on which a new government might be expected to want the opportunity to take a different view from the present government should be postponed until after the election, provided that such postponement would not be detrimental to the national interest or wasteful of public money.   

4. Advice on handling such issues is set out in this guidance. This guidance will not cover every eventuality, but the principles should be applied to the particular circumstances.  

5. The principles underlying the conduct of civil servants in a general election are an extension of those that apply at all times, as set out in the Civil Service Code

• The basic principle for civil servants is not to undertake any activity that could call into question their political impartiality or that could give rise to criticism that public resources are being used for party political purposes. This principle applies to all staff working in departments.  
• Departmental and NDPB activity should not be seen to compete with the election campaign for public attention. The principles and conventions set out in this guidance also apply to public bodies.  
• It is also a requirement of the Ministerial Code that Ministers must not use government resources for party political purposes and must uphold the political impartiality of the Civil Service.  

Election queries 

6. For any detailed queries on this guidance, or other questions, officials should in the first instance seek guidance from their line management chain, and, where necessary, escalate to their Permanent Secretary who may consult the Cabinet Secretary, or the Propriety and Ethics Team in the Cabinet Office. 

7. The Propriety and Ethics Team handle general queries relating to conduct during the election period, provide advice on the handling of enquiries and any necessary co-ordination where enquiries raise issues that affect a number of departments (through their Permanent Secretary). 

8. In dealing with queries, the Propriety and Ethics Team will function most effectively if it is in touch with relevant developments in departments. 

Departments should therefore: 

• draw to their attention, for advice or information, any approach or exchange that raises issues that are likely to be of interest to other departments; and 
• seek advice before a Minister makes a significant Ministerial statement during the election period. 

Section A: Enquiries, Briefing, Requests for Information and attending events 

1. This note gives guidance on: 

• the handling by departments and agencies of requests for information and other enquiries during a general election campaign; 
• briefing of Ministers during the election period;  
• the handling of constituency letters received from Members of Parliament before dissolution, and of similar letters from parliamentary candidates during the campaign; and 
• the handling of FOI requests. 

2. At a general election, the government of the day is expected to defend its policies to the electorate. By convention, the governing party is entitled to check with departments that statements made on its behalf are factually correct and consistent with government policy. As at all times, however, government departments and their staff must not engage in, or appear to engage in, party politics or be used for party ends. They should provide consistent factual information on request to candidates of all parties, as well as to organisations and members of the public, and should in all instances avoid becoming involved or appearing to become involved, in a partisan way, in election issues. 

Requests for Factual Information 

3. Departments and agencies should provide any parliamentary candidate, organisation or member of the public with information in accordance with the Freedom of Information Act 2000. Local and regional offices should deal similarly with straightforward enquiries, referring doubtful cases through their line management chain and, where necessary to their Permanent Secretary for decision. 

4. Other requests for information will range from enquiries about existing government policy that are essentially factual in nature, to requests for justification and comment on existing government policy. All requests for information held by departments must be dealt with in accordance with the requirements of the Freedom of Information Act 2000. The handling of press enquiries is covered in Section I.  

5. Where the enquiry concerns the day-to-day management of a non-ministerial department or executive agency and the chief executive would normally reply, he or she should do so in the usual way, taking special care to avoid becoming involved in any matters of political controversy. 

6. Enquiries concerning policies newly announced in a party manifesto or for a comparison of the policies of different parties are for the political party concerned. Civil servants should not provide any assistance on these matters. See also paragraph 14.  

7. Officials should draft replies, whether for official or Ministerial signature, with particular care to avoid party political controversy, especially criticism of the policies of other parties. Ministers may decide to amend draft replies to include a party political context. Where this is the case, Ministers should be advised to issue the letter on party notepaper. The guiding principle is whether the use of departmental resources, including headed paper, would be a proper use of public funds for governmental as opposed to party political purposes, and could be defended as such. 

Speed of Response 

8. The circumstances of a general election demand the greatest speed in dealing with enquiries. In particular, the aim should be to answer enquiries from parliamentary candidates or from any of the political parties’ headquarters within 24 hours. All candidates should be treated equally. 

9. Where a request will take longer to deal with, the requester should be advised of this as he/she may wish to submit a refined request. 

FOI requests 

10. Requests that would normally be covered by the Freedom of Information Act (FOIA) must be handled in accordance with the requirements of the Act and the deadlines set therein. Where the application of the public interest balance requires more time, that is permitted under the Act but there is no general power to defer a decision.   

11. Where a request needs to be considered under FOIA it will not normally be possible to get back to the parliamentary candidate, or others, within 24 hours and he or she should be advised of this as they may wish to submit a request more in line with paragraph 8 above. 

Role of Ministers in FOIA decisions 

12. Ministers have a number of statutory functions in relation to requests for information. They are the qualified person for the purpose of using section 36 of the FOI Act for their departments. During the general election period, Ministers will be expected to carry out these functions.  

13. Where there is any doubt, requests should be referred to the FOI Policy team in the Cabinet Office. 

Briefing and Support for Ministers 

14. Ministers continue to be in charge of departments. It is reasonable for departments to continue to provide support for any necessary governmental functions, and receive any policy advice or factual briefing necessary to resolve issues that cannot be deferred until after the election. 

15. Departments can check statements for factual accuracy and consistency with established government policy. Officials should not, however, be asked to devise new arguments or cost policies for use in the election campaign. Departments should not undertake costings or analysis of Opposition policies during the election period.  

Officials attending public or stakeholder events 

16. Officials should decline invitations to events where they may be asked to respond on questions about future government policy or on matters of public controversy. 

Constituency Correspondence 

17. During the election period, replies to constituency letters received from Members of Parliament before the dissolution, or to similar letters from parliamentary candidates, should take into account the fact that if they become public knowledge they will do so in the more politically-charged atmosphere of an election and are more likely to become the subject of political comment. Outstanding correspondence should be cleared quickly. Letters may be sent to former MPs at the House of Commons after dissolution, to be picked up or forwarded. Departments and agencies whose staff routinely deal directly with MPs’ enquiries should ensure that their regional and local offices get early guidance on dealing with questions from parliamentary candidates. Such guidance should reflect the following points: 

a. Once Parliament is dissolved, a Member of Parliament’s constitutional right to represent his or her constituents’ grievances to government disappears, and all candidates for the election are on an equal footing. This doctrine should be applied in a reasonable way. In general, replies should be sent by Ministers to constituency letters that were written by MPs before dissolution. Where there is a pressing need for Ministers to reply to letters on constituency matters written after the dissolution by former Members, this should be handled in a way that avoids any preferential treatment or the appearance of preferential treatment between letters from the governing party and those from other candidates. It will normally be appropriate to send a Private Secretary reply to letters on constituency matters from prospective parliamentary candidates who were not Members before the dissolution. 

b. The main consideration must be to ensure that the citizen’s interests are not prejudiced. But it is possible that a personal case may become politically controversial during the election period. Departments should therefore make particular efforts to ensure, so far as possible, that letters are factual, straightforward and give no room for misrepresentation. 

c. Replies to constituency correspondence to be sent after polling day should, where there has been a change of MP, normally be sent direct to the constituent concerned. It should be left to the constituent to decide whether or not to copy the letter to any new MP. Where there is no change in MP, correspondence should be returned to the MP in the normal way.

Section B: Special Advisers 

1. Special Advisers must agree with the Cabinet Office the termination of their contracts  on or before 30 May (except for a small number of Special Advisers who may remain in post, where the express agreement of their appointing Minister and the Prime Minister to continue in post has been given).     

2. An exception to this is where a Special Adviser has been publicly identified as a candidate or prospective candidate for election to the UK Parliament, in which case they must instead resign at the start of the short campaign period ahead of the election. 

3. Special Advisers who leave government for any reason will no longer have preferential access to papers and officials. Any request for advice from a former Special Adviser will be treated in the same way as requests from other members of the public.  

4. On leaving government, Special Advisers should return all departmental property e.g. mobile phones, remote access and other IT equipment. Special Advisers may leave a voicemail message or out of office reply on departmental IT with forwarding contact details.  

5. Special Advisers receive severance pay when their appointment is terminated, but not where they resign. Severance pay for Special Advisers is taxable as normal income and will be paid as a lump sum. The amount an individual is entitled to will be determined by their length of service as set out in the Model Contract for Special Advisers. Special Advisers are required to agree that if they are reappointed, they will repay any amount above that which they would have been paid in salary had they remained in post. Any excess severance will be reclaimed automatically through payroll on reappointment.  

6. If the Prime Minister agrees exceptionally that a Special Adviser should remain in post during the election period, their appointment will be automatically terminated the day after polling day. In those cases, Special Advisers may continue to give advice on government business to their Ministers as before. They must continue to adhere to the requirements of the Code of Conduct for Special Advisers and may not take any public part in the campaign. Section A is also relevant in relation to the commissioning of briefing. 

7. Different arrangements can be made for Special Advisers on, or about to begin, maternity leave when a UK general election is called. These arrangements are set out in the Maternity Policy for Special Advisers, and Special Adviser HR are best placed to advise on specific circumstances.

8. If there is no change of government following the election, a Special Adviser may be reappointed. The Prime Minister’s approval will be required before any commitments are made, and a new contract issued, including for any advisers who have stayed in post.

Section C: Contacts with the Opposition Party 

1. The Prime Minister has authorised pre-election contact between the main opposition parties and Permanent Secretaries from 11 January 2024. These contacts are strictly confidential and are designed to allow Opposition spokespeople to inform themselves of factual questions of departmental organisation and to inform civil servants of any organisational or policy changes likely in the event of a change of government.  

2. Separate guidance on handling such contacts is set out in the Cabinet Manual.

Section D: Contact with Select Committees 

1. House of Commons Select Committees set up by Standing Order continue in existence, technically, until that Standing Order is amended or rescinded. In practice, when Parliament is dissolved pending a general election, membership of committees lapses and work on their inquiries ceases.  

2. House of Lords Select Committees are not set up by Standing Orders and technically cease to exist at the end of each session. 

3. The point of contact for departments continues to be the Committee Clerk who remains in post to process the basic administrative work of the committee (and prepare for the re-establishment of the Committee in the next Parliament).  

4. Departments should continue to work, on a contingency basis, on any outstanding evidence requested by the outgoing committee and on any outstanding government responses to committee reports. It will be for any newly-appointed Ministers to approve the content of any response. It will be for the newly-appointed committee to decide whether to continue with its predecessor committee’s inquiries and for the incoming administration to review the terms of draft responses before submitting to the newly appointed committee. 

5. It is for the newly-appointed committee to decide whether to publish government responses to its predecessor reports. There may be some delay before the committee is reconstituted, and an incoming government may well wish to publish such responses itself by means of a Command Paper. In this event, the department should consult the Clerk of the Committee before publication of the report response.

Section E: Political Activities of Civil Servants 

1. Permanent Secretaries will wish to remind staff of the general rules governing national political activities. These are set out in the Civil Service Management Code and departmental staff handbooks. 

2. For this purpose, the Civil Service is divided into three groups: 

a. the “politically free” – industrial and non-office grades; 

b. the “politically restricted” – members of the Senior Civil Service, civil servants in Grades 6 and 7 (or equivalent) and members of the Fast Stream Development Programme; and

c. civil servants outside the “politically free” and “politically restricted” groups  

3. Civil servants on secondment to outside organisations (or who are on any form of paid or unpaid leave) remain civil servants and the rules relating to political activity continue to apply to them. Departments should seek to contact individuals on secondment outside the civil service to remind them of this. Individuals seconded into the Civil Service are also covered by these rules for the duration of their appointment. 

Civil Servants Standing for Parliament  

4. All civil servants are disqualified from election to Parliament (House of Commons Disqualification Act 1975) and must resign from the Civil Service before standing for election. Individuals must resign from the Civil Service on their formal adoption as a prospective parliamentary candidate, and must complete their last day of service before their adoption papers are completed. If the adoption process does not reasonably allow for the individual to give full notice, departments and agencies may at their discretion pay an amount equivalent to the period of notice that would normally be given. 

Other Political Activity 

5. “Politically restricted” civil servants are prohibited from any participation in national political activities.  

6. All other civil servants may engage in national political activities with the permission of the department, which may be subject to certain conditions.  

7. Where, on a case by case basis, permission is given by departments, civil servants must still act in accordance with the requirements of the Civil Service Code, including ensuring that they meet the Code’s values and standards of behaviour about impartiality and political impartiality. Notwithstanding any permission to engage in national political activities, they must ensure that their actions (and the perception of those actions) are compatible with the requirements to: 

• serve the government, whatever its political persuasion, to the best of their ability in a way which maintains political impartiality and is in line with the requirements of the Code, no matter what their own political beliefs are; and 
• act in a way which deserves and retains the confidence of ministers, while at the same time ensuring that they will be able to establish the same relationship with those whom they may be required to serve in some future government. 

Reinstatement 

8. Departments and agencies must reinstate former civil servants who have resigned from “politically free” posts to stand for election and whose candidature has proved unsuccessful, provided they apply within a week of declaration day.  

9. Departments and agencies have discretion to reinstate all other former civil servants who have resigned to stand for election and whose candidature has proved unsuccessful. Former civil servants in this category seeking reinstatement should apply within a week of declaration day if they are not elected. Departments are encouraged to consider all applications sympathetically and on their merits. For some individuals, it may not be possible to post them back to their former area of employment because, for instance, of the sensitivity of their work and/or because their previous job is no longer vacant. In these cases, every effort should be made to post these staff to other areas rather than reject their applications.

Section F: Cabinet and Official Documents 

1. In order to enable Ministers to fulfil their continuing responsibilities as members of the Government during the election period, departments should retain the Cabinet documents issued to them. Cabinet documents refers to all papers, minutes and supplementary materials relating to Cabinet and its committees. This is applicable to meetings of and correspondence to Cabinet and its committees. 

2. If there is no change of government after the election, Ministers who leave office or who move to another Ministerial position must surrender any Cabinet or Cabinet committee papers or minutes (including electronic copies) and they should be retained in the department in line with guidance issued by the Cabinet Office.  Ministers who leave office or move to another Ministerial position should also not remove or destroy papers that are the responsibility of their former department: that is, those papers that are not personal, party or constituency papers. 

3. If a new government is formed, all Cabinet and Cabinet committee documents issued to Ministers should be destroyed. Clearly no instructions can be given to this effect until the result of the election is known, but Permanent Secretaries may wish to alert the relevant Private Secretaries.  

4. The conventions regarding the access by Ministers and Special Advisers to papers of a previous Administration are explained in more detail in the Cabinet Manual. Further guidance to departments will be issued by the Cabinet Office once the outcome of the election is known.  

5. More detailed guidance on managing records in the event of a change of administration will be held by your Departmental Records Officer. The Head of Public Records and Archives in the Cabinet Office can also provide further advice and written guidance can be found here: 

Guidance management of private office information and records

Section G: Government Decisions 

1. During an election campaign the Government retains its responsibility to govern and Ministers remain in charge of their departments. Essential business (including routine business necessary to ensure the continued smooth functioning of government and public services) must be carried on. Cabinet committees are not expected to meet during the election period, nor are they expected to consider issues by correspondence. However there may be exceptional circumstances under which a collective decision of Ministers is required. If something requires collective agreement and cannot wait until after the General Election, the Cabinet Secretary should be consulted.  

2. However, it is customary for Ministers to observe discretion in initiating any action of a continuing or long term character. Decisions on matters of policy, and other issues such as large and/or contentious commercial contracts, on which a new government might be expected to want the opportunity to take a different view from the present government, should be postponed until after the election, provided that such postponement would not be detrimental to the national interest or wasteful of public money. 

Statutory Instruments 

3. The principles outlined above apply to making statutory instruments. 

Departmental lawyers can advise in more detail, in conjunction with the Statutory Instrument Hub.  

4. The general principle that Ministers should observe discretion in initiating any new action of a continuing or long-term character applies to the making of commencement orders, which during the election period should be exceptional.  As is usual practice, statutory instruments are required to go through the Parliamentary Business and Legislation Committee process before they can be laid.

Section H: Public and Senior Civil Service Appointments

1. All appointments requiring approval by the Prime Minister, and other Civil Service and public appointments likely to prove sensitive (including those where Ministers have delegated decisions to officials or other authorities) should be frozen until after the election, except in exceptional circumstances (further detail below). This includes appointments where a candidate has already accepted a written offer (and the appointment has been announced before the election period), but where the individual is not due to take up post until after the election. The individual concerned should be told that the appointment will be subject to confirmation by the new Administration after the election. 

2. It is recognised that this may result in the cancellation (or delay) of an appointment by the new Administration, and that the relevant department could be vulnerable to legal action by a disappointed candidate. To reduce the risk of this, departments might wish to: 

• recommend to their Secretary of State the advisability of bringing forward or delaying key stages in the process, where an appointment would otherwise likely take effect just before or after an election; 
• issue a conditional offer letter, making it clear that the formal offer of the appointment will need to be confirmed by a new Administration. 

3. In cases where an appointment is due to end between dissolution and election day, and no announcement has been made concerning the new appointment, it will normally be possible for the post to be left vacant or the current term extended until incoming Ministers have been able to take a decision either about reappointment of the existing appointee or the appointment of a new person. This situation is also likely to apply to any appointments made by Letters Patent, or otherwise requiring royal approval, since it would not be appropriate to invite His Majesty to make a conditional appointment. 

4. In exceptional cases where it is not possible to apply these temporary arrangements and there is an essential need to make an appointment during the election period, departments may wish to advise their Ministers about consulting the Opposition before a final decision is taken. Departments should consult the Public Appointments Policy Team in the Cabinet Office. 

5. In the case of public and Senior Civil Service appointments, departments should delay the launch of any open competition during an election period, to give any incoming Administration the option of deciding whether to follow the existing approach.  

6. In those cases where an appointment is required to be made, it is acceptable, in the case of sensitive Senior Civil Service positions, to allow temporary promotion.  

Section I: Communication Activities during a General Election

1. The general principle governing communication activities during a general election is to do everything possible to avoid competition with parliamentary candidates for the attention of the public, and not to undertake any activity that could call into question civil servants’ political impartiality or that could give rise to criticism that public resources are being used for party political purposes. Special care must be taken during the course of an election since material produced with complete impartiality, which would be accepted as objective in ordinary times, may generate criticism during an election period when feelings are running high. All communication activity should be conducted in line with Government Communication Service (GCS) guidance on propriety and propriety in digital and social media .  

2. Departmental communications staff may properly continue to discharge their normal function during the election period, to the extent of providing factual explanation of current government policy, statements and decisions. They must be particularly careful not to become involved in a partisan way in election issues.  

3. During the election period, access to departmental briefing systems will be restricted to permanent civil servants who will produce briefing, and answer requests for information, in line with the principles set out in Section A of the election guidance. Any updating of lines to take should be confined to matters of fact and explanations of existing government policy in order to avoid criticism of serving, or appearing to serve, a party political purpose.  

News Media  

4. In response to questions departments should, where possible, provide factual information by reference to published material, including that on websites. Specific requests for unpublished material should be handled in accordance with the requirements of the Freedom of Information Act. 

5. Routine factual press notices may continue to be issued – for example statistics that are issued on a regular basis or reports of publicly-owned bodies, independent committees etc., which a department is required to publish. 

6. There would normally be no objection to issuing routine factual publications, for example health and safety advice, but these should be decided on a case by case basis, in consultation with the Director or Head of Communications, who should take account of the subject matter and the intended audience. A similar approach should apply to blogs and social media. 

7. Press releases and other material normally sent to Members of Parliament should cease at the point at which this guidance comes into effect. 

8. Statements that refer to the future intentions of the Government should not be handled by a department and should be treated as party political statements. Where a Minister considers it necessary to hold a governmental press conference to make clear the Government’s existing policies on a particular subject prior to the election, then his or her department should provide facilities and give guidance. Ultimately, each case must be judged on its merits, including consideration of whether an announcement needs to be made, in consultation with the Director or Head of Communications.  

9. The Propriety and Ethics Team in the Cabinet Office must be consulted before a Minister makes an official Ministerial statement during the election period. 

10. Statements or comments referring to the policies, commitments or perceived intentions of Opposition parties should not be handled by departments. 

Press Articles, Interviews, and Broadcasts and Webcasts by Ministers  

11. During the election period, arrangements for newspaper articles, interviews and broadcasts by Ministers, including online, will normally be made on the political network. Care should be taken by communications staff in arranging any press interviews for Ministers during this period because of the possibility that such interviews would have a strong political content. They should not arrange broadcasts through official channels unless they are satisfied there is a need to do so and that the Minister is speaking in a government, not party, capacity. 

Paid Media 

12. Advertising, including partnership and influencer marketing. New campaigns will in general be postponed and live campaigns will be paused (across all advertising and marketing channels). A very small number of campaigns (for example, relating to essential recruitment, or public health, such as blood and organ donation or health and safety) may be approved by the Permanent Secretary, in consultation with GCS and the Propriety and Ethics Team.

a. International activity. Where marketing is delivered outside the UK and targeting non-UK citizens, the campaign can continue during the election period, subject to Permanent Secretary approval and as long as consideration has been given to the potential for the campaign to garner interest within the UK and to reach UK diaspora. If continuing the campaign is likely to generate domestic interest, it should be paused.

b. Official radio ‘fillers’ will be reviewed and withdrawn unless essential.

13. Films, videos and photographs from departmental libraries or sources should not be made available for use by political parties.  

14. Printed material should not normally be given any fresh distribution in the United Kingdom during the election period, in order to avoid any competition with the flow of election material. The effect on departments that distribute posters and leaflets to the public is as follows: 

a. Posters. The normal display of existing posters on official premises may continue but efforts should not be made to seek display elsewhere. Specific requests by employers, trade unions etc for particular posters may, however, be met in the ordinary way. 

b. Leaflets. Small numbers of copies of leaflets may be issued on request to members of the public and to parliamentary candidates, in consultation with the Director or Head of Communications, who should take account of the subject matter and the intended audience. Bulk supplies should not be issued to any individuals or organisations without appropriate approval. 

c. Export promotion stories and case studies for overseas use may continue to be sought  in the UK but it must be made clear on each occasion that this information is needed for use abroad, and permission must be sought from the Permanent Secretary before proceeding. 

d. The use of public buildings for communication purposes is covered in Section L. 

15. Exhibitions. Official exhibitions on a contentious policy or proposal should not be kept open or opened during the election period. Official exhibitions that form part of a privately sponsored exhibition do not have to be withdrawn unless they are contentious, in which case they should be withdrawn. 

Social Media and Digital Channels 

16. Official websites and social media channels will be scrutinised closely by news media and political parties during the election period. All content must be managed in accordance with GCS propriety guidance.

Publishing content online  

17. Content Design: planning, writing and managing content guidance   should be consulted when publishing any online content.

18. Material that has already been published in accordance with the rules on propriety and that is part of the public domain record can stand. It may also be updated for factual accuracy, for example a change of address. However, while it can be referred to in handling media enquiries and signposting in response to enquiries from the public, nothing should be done to draw further attention to it. 

19. Updating the public with essential factual information may continue (e.g. transport delays) but social media and blogs that comment on government policies and proposals should not be updated for the duration of the election period.  

20. Ministers’ biographies and details of their responsibilities can remain on sites, no additions should be made. Social media profiles should not be updated during this period. 

21. Site maintenance and planned functional and technical development for existing sites can continue, but this should not involve new campaigns or extending existing campaigns.  

22. News sections of websites and blogs must comply with the advice on press releases. News tickers and other mechanisms should be discontinued for the election period. 

23. In the event of an emergency, digital channels can be used as part of Crisis Communication  activity in the normal way. 

Further Guidance 

24. In any case of doubt about the application of this guidance in a particular case, communications staff should consult their Director or Head of Communications in the first instance, then, if necessary, the Chief Executive, Government Communication Service, Chief Operating Officer, Government Communication Service, or the departmental Permanent Secretary who will liaise with the Propriety and Ethics Team in the Cabinet Office.

Section J: Guidance on Consultations during an election period 

1. In general, new public consultations should not be launched during the election period. If there are exceptional circumstances where launching a consultation is considered essential (for example, safeguarding public health), permission should be sought from the Propriety and Ethics Team in the Cabinet Office. 

2. If a consultation is on-going at the time this guidance comes into effect, it should continue as normal. However, departments should not take any steps during an election period that will compete with parliamentary candidates for the public’s attention. This effectively means a ban on publicity for those consultations that are still in process. 

3. As these restrictions may be detrimental to a consultation, departments are advised to decide on steps to make up for that deficiency while strictly observing the guidance. That can be done, for example, by: 

a. prolonging the consultation period; and 

b. putting out extra publicity for the consultation after the election in order to revive interest (following consultation with any new Minister). 

4. Some consultations, for instance those aimed solely at professional groups, and that carry no publicity, will not have the impact of those where a very public and wide-ranging consultation is required. Departments need, therefore, to take into account the circumstances of each consultation. Some may need no remedial action – but this is a practical rather than propriety question so long as departments observe the broader guidance here. 

5. During the election period, departments may continue to receive and analyse responses with a view to putting proposals to the incoming government but they should not make any statement or generate publicity during this period.   

Section K: Statistical Activities during a General Election 

1. This note gives guidance on the conduct of statistical activities across government during a general election period.  [footnote 1]

2. The same principles apply to social research and other government analytical services.  

3. Under the terms of the Statistics and Registration Service Act 2007, the UK Statistics Authority, headed by the National Statistician, is responsible for promoting and safeguarding the integrity of official statistics. It should be consulted in any cases of doubt about the application of this guidance.  

Key Principles 

4. Statistical activities should continue to be conducted in accordance with the Code of Practice for Official Statistics and the UK Government’s Prerelease Access to Official Statistics Order 2008, taking great care, in each case, to avoid competition with parliamentary candidates for the attention of the public. 

Statistical publications, releases, etc. 

5. The greatest care must continue to be taken to ensure that information is presented impartially and objectively. 

6. Regular pre-announced statistical releases (e.g. press notices, bulletins, publications or electronic releases) will continue to be issued and published. Any other ad hoc statistical releases should be released only in exceptional circumstances and with the approval of the National Statistician, consulting with the Propriety and Ethics Team in the Cabinet Office where appropriate. Where a pre-announcement has specified that the information would be released during a specified period (e.g. a week, or longer time period), but did not specify a precise day, releases should not be published within the election period. The same applies to social research publications

Requests for information 

7. Any requests for unpublished statistics, including from election candidates, should be handled in an even-handed manner, in accordance with the Freedom of Information Act. Guidance on handling FOI requests can be found in Section A.  

Commentary and Briefing 

8. Special care must be taken in producing commentary for inclusion in announcements of statistical publications issued during the election period. Commentary that would be accepted as impartial and objective analysis or interpretation at ordinary times, may attract criticism during an election. Commentary by civil servants should be restricted to the most basic factual clarification during this period. Ultimately the content of the announcement is left to the discretion of the departmental Head of Profession, seeking advice from the National Statistician as appropriate. 

9. Pre-election arrangements for statistics, whereby pre-release access for briefing purposes is given to Ministers or chief executives (and their appropriate briefing officials) who have policy responsibility for a subject area covered by a particular release, should continue, in accordance with the principles embodied in the UK Government’s Pre-release Access to Official Statistics Order 2008.  

10. In general, during this period, civil servants involved in the production of official statistics will not provide face to face briefing to Ministers. Only if there is a vital operational need for information, (e.g. an out of the ordinary occurrence of market-sensitive results with significant implications for the economy, or some new management figures with major implications for the running of public services), should such briefing be provided. Any such briefing should be approved by the National Statistician.  

11. Requests for advice on the interpretation or analysis of statistics should be handled with care, and in accordance with the guidance in paragraphs 6 and 7.  

12. Requests for factual guidance on methodology should continue to be met. 

13. Requests for small numbers of copies of leaflets, background papers or free publications that were available before the election period may continue to be met but no bulk issues to individuals or organisations should be made without appropriate approval. Regular mailings of statistical bulletins to customers on existing mailing lists may continue. 

Censuses, Surveys and other forms of quantitative or qualitative research enquiry  

14. Regular, continuous and on-going censuses and surveys of individuals, households, businesses or other organisations may continue. Ad hoc surveys and other forms of research that are directly related to and in support of a continuing statistical series may also continue. Ad hoc surveys and other forms of research that may give rise to controversy or be related to an election issue should be postponed or abandoned. 

Consultations 

15. Statistical consultations that are on-going at the point at which Parliament dissolves should continue as normal, but any publicity for such consultations should cease. New public consultations, even if preannounced, should not be launched but should be delayed until after the result of the election is officially declared.  

Further Advice 

16. If officials working on statistics in any area across government are unsure about any matters relating to their work during the election period, they should seek the advice of their Head of Profession in the first instance. Heads of Profession should consult the National Statistician in any cases of doubt. Queries relating to social research, or other analytical services should similarly be referred to the relevant Head of Profession or departmental lead and Permanent Secretary’s office in the first instance. Further advice can be sought from the Propriety and Ethics Team in the Cabinet Office.

Section L: Use of Government Property 

1. Neither Ministers, nor any other parliamentary candidates, should involve government establishments in the general election campaign by visiting them for electioneering purposes. 

2. In the case of NHS property, decisions are for the relevant NHS Trust but should visits be permitted to, for example, hospitals, the Department of Health and Social Care advise that there should be no disruption to services and the same facilities should be offered to other candidates. In any case, it is advised that election meetings should not be permitted on NHS premises. NHS England publishes its own information to NHS organisations about the pre-election period.

3. Decisions on the use of other public sector and related property must be taken by those legally responsible for the premises concerned – for example, for schools, the Governors or the Local Education Authority or Trust Board, and so on. If those concerned consult departments, they should be told that the decision is left to them but that they will be expected to treat the candidates of all parties in an even-handed way, and that there should be no disruption to services. The Department for Education will provide advice to schools on the use of school premises and resources.  

4. It is important that those legally responsible for spending public funds or the use of public property ensure that there is no misuse, or the perception of misuse, for party political purposes. Decision-makers must respect the Seven Principles of Public Life when considering the use of public funds or property during the election period. The principles include an expectation that public office holders take decisions impartially, fairly and on merit and maintain their accountability to the public for their decisions and actions.

Section M: International Business 

1. This guidance specifically addresses the principles that will apply to international business.  

2. International business will continue as normal during the period of the general election.  

International meetings 

3. Decisions on Ministerial attendance and representation at international meetings will continue to be taken on a case by case basis by the lead UK Minister. For example, Ministers will be entitled to attend international summits (such as meetings of the G20).  

4. When Ministers speak at international  meetings, they are fully entitled to pursue existing UK Government policies. All Ministers, whether from the UK Government or the Devolved Administrations, should avoid exploiting international engagements for electoral purposes. Ministers should observe discretion on new initiatives and before stating new positions or making new commitments (see Section G for further advice on Government decision-making).

5. Where a Minister is unable to attend an international meeting that has been assessed as of significant interest to the UK, the UK may be represented by a senior official. In this case, where an item is likely to be pressed to a decision (a legislative decision, or some other form of commitment, e.g. a resolution, conclusions), officials should engage in negotiations and vote in line with the cleared UK position and in line with a detailed brief cleared by the lead UK Minister. Officials should engage actively where there will be a general discussion or orientation debate, but should seek to avoid taking high profile decisions on issues of domestic political sensitivity. If decisions fall to be taken at an international summit that risk being controversial between the UK political parties, departments should consult their Permanent Secretary about the line to follow who may in turn wish to consult the Cabinet Secretary. 

Changes to International Negotiating Positions

6. There may be an unavoidable need for changes to a cleared UK position that require the collective agreement of Ministers. This may arise, for example, through the need for officials to have sufficiently clear negotiating instructions or as a result of the agreed UK position coming under pressure in the closing stages of negotiation. If collective agreement is required, the Cabinet Secretary should be consulted (see Section G). The Cabinet Secretariat can advise departments where they are unsure whether an issue requires further collective agreement. 

7. Departments should note that the reduced availability of Ministers during the election period means that it will be necessary to allow as much time as possible for Ministers to consider an issue. 

Relations with the Press 

8. Departmental Communication staff may properly continue to discharge, during the election period, their normal function only to the extent of providing factual explanation of current government policy, statements and decisions. They must be particularly careful not to become involved in a partisan way in election issues. 

9. Ministers attending international meetings will no doubt wish to brief the press afterwards in the normal manner. But where officials attend meetings in place of Ministers, they should be particularly circumspect in responding to the press on any decision or discussion in the meeting that could be regarded as touching on matters of domestic political sensitivity. If departments wish to issue press notices following international meetings on the discussions or decisions that took place, they should be essentially factual. Any comment, especially on items of domestic sensitivity, should be made by Ministers. In doing so, consideration will need to be given as to whether such comment should be handled by the department or the party. This must be agreed in advance with the Permanent Secretary.  

International Appointments 

10. The UK should not normally make nominations or put forward candidates for senior international appointments until after the election. It remains possible to make nominations or put forward candidates for other positions. Departments should consult their Permanent Secretary and the Propriety and Ethics Team in Cabinet Office on appointments that risk being controversial between the UK political parties.

Section N: The Devolved Administrations

1. The general election does not affect the devolved administrations in the same way. The devolved legislatures are elected separately to the House of Commons. Devolved Ministers in Scotland, Wales and Northern Ireland will continue to carry out their devolved functions in those countries as usual.

2. Under the Civil Service Code, which also applies to all civil servants, civil servants in the devolved administrations serve Ministers elected through elections in Scotland, Wales and Northern Ireland and do not report to the UK Government. Accordingly, this guidance does not apply to them. They will continue to support their Ministers in their work. 

3. However, the devolved administrations acknowledge that their activities could have a bearing on the general election campaign. While the devolved administrations will continue largely as normal, they are aware of the need to avoid any action that is, or could be construed as being, party political or likely to have a direct bearing on the general election. Staff in the devolved administrations will continue to refer requests for information about reserved issues from MPs, parliamentary candidates and political parties to the relevant UK department. Requests for information about devolved issues will be handled in accordance with relevant FOI legislation, taking account of the need for prompt responses in the context of an election period. 

4. Officials in the devolved administrations are subject to the rules in Section E as regards their personal political activities, in the same way as UK Government officials. 

5. Discussions with the devolved administrations during the election period should be conducted in this context. For more general details on how best to work with the devolved administrations see the Cabinet Office guidance: Devolution guidance for civil servants

Section O: Public Bodies 

1. The general principles and conventions set out in this guidance apply to the board members and staff of all NDPBs and similar public bodies. Some NDPBs and ALBs employ civil servants.  

2. NDPBs and other public sector bodies must be, and be seen to be, politically impartial. They should avoid becoming involved in party political controversy. Decisions on individual matters are for the bodies concerned in consultation with their sponsor department who will wish to consider whether proposed activities could reflect adversely on the work or reputation of the NDPB or public body in question.

This includes departments and their agencies and other relevant public bodies including all public bodies deemed to be producers of official statistics by dint of an Order in Parliament.  ↩

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