18–99 years
The meta-analysis results were divided into several sections in the present study: first, the comparison of QOL of ordinary people with IA people based on overall scores of QOL and each of its dimensions; second, the analysis of the relationship between the severity of IA and QOL based on r index and calculated OR index.
Due to the high heterogeneity of the analysis, the relationship between the severity of Internet addiction and each dimension of the quality of life, a power analysis was performed. The high power of the analysis for each dimension of the quality of life showed that the results of the study were not affected by heterogeneity.
Four studies examined the overall scores of both groups. Based on the results, people with a high IA (779 participants) received lower scores of QOL than those with normal Internet use (2589 participants) (95% CI: 2.31–2.61; I 2 = 85.23%, p < 0.001).
Four studies examined other QOL dimensions. Based on the obtained results, people with severe IA received lower QOL scores than those with normal Internet use in terms of the environmental (95% CI: 1.65–2.08; I 2 = 22.45%, p =0.276), physical (95% CI: 2.44–2.93; I 2 = 0.0%, p =0.962), psychological (95% CI: 2.71–3.57; I 2 = 38.32%, p =0.182), and social dimensions (95% CI: 1.63–2.95; I 2 = 86.31%, p < 0.001). Figure 2 shows results of the Forest plot for comparison of the QOL of ordinary people with IA ( Figure 2 ).
Comparing the quality of life of ordinary people with that of internet addicts.
The research results indicated that IA is associated with a decrease in QOL. There was a negative significant relationship between the severity of IA and QOL in psychological (95% CI: 0.32–0.99; I 2 = 97.47%, p < 0.001) ( Figure 3 ), physical (95% CI: 0.39–0.86; I 2 = 95.29%, p =0.001) ( Figure 4 ), and overall QOL (95% CI: 0.27–0.55; I 2 = 92.7%, p < 0.001) ( Figure 5 ); however, no statistical significant reduction was observed in environmental (95% CI: 0.50–1.06; I 2 = 93.89%, p < 0.001) ( Figure 6 ) and social dimension (95% CI: 0.45–1.24; I 2 = 96.63%, p < 0.001) ( Figure 7 ).
The relationship between the severity of internet addiction and the quality of life in the psychological dimension.
The relationship between the severity of internet addiction and the quality of life in the physical dimension.
The relationship between the severity of internet addiction and the overall quality of life score.
The relationship between the severity of internet addiction and the quality of life in the environmental dimension.
The relationship between the severity of internet addiction and the quality of life in the social dimension.
Based on the results of the Egger ( p =(0/601)) and Begg test ( p =(0/945)), no publication bias was observed among studies due to the symmetry of the funnel plot ( Figure 8 ).
Funnel plot for assessing possible publication bias.
Despite the increasing volume of research on the relationship between IA and QOL, no systematic review or meta-analysis has been conducted to summarize the findings to the best of the authors' knowledge. More specifically, the first study assessing IA and QOL has been published in 2013 [ 34 ]. Accordingly, the association between IA and sleep has been studied over the last seven years, and the cumulative evidence requires to be summarized. The present review is the first meta-analysis that uses empirical evidence from the past seven years to understand the association between IA and QOL. By a rigorous selection method using PRISMA guidelines, 18 studies with 11,097 participants were included in the present meta-analysis.
The high power of analysis for each dimension of quality of life showed that the results of the study were not affected by heterogeneity; one of the reasons could be the high number of samples in the study.
Meta-analysis results show differences in QOL based on Internet usage. As the results of four studies show that people with a high IA receive lower scores of QOL than those with normal Internet use (OR: 2.45, p < 0.001). This result was consistent with those of other studies in the field [ 35 – 38 ]; these results suggest that, in comparative studies, even after controlling some background variables affecting QOL, there are still significant independent correlations between IA and all aspects of QOL.
According to the obtained results of the meta-analysis (11studies), IA is associated with a decline in overall QOL (OR: 0.39; p < 0.001). This result, except in one [ 39 ] case, is consistent with the results of other studies included in the analysis [ 36 , 40 – 48 ]. In these studies, an Indian study had the smallest sample size which was 60 [ 39 ], and a Filipino study had the largest sample size, which was 1447 [ 40 ]. The studies are also conducted across 11 countries mostly located in Asia ( n = 11), followed by Europe ( n = 5) and the USA ( n = 2). Although the meta-analysis results in the present review are primarily derived from Asian populations, based on the Egger ( t : 0.539, p : 0.601) and Begg test ( z : 0.137, p : 0.190), no publication bias is observed among them. Additionally, with moderate- and high-quality studies using the STROBE checklist and standard measurement tools, the methodological concerns might have minimal impacts on the present findings.
The research results indicate a significant negative relationship between IA and QOL in the psychological (OR = 0.56, p =0.04) and physical dimensions (OR = 0.58, p =0.007). Different and sometimes contradictory results are reported in studies on the impact of IA on the QOL dimensions. For instance, in two studies by Solati et al. in Iran [ 44 ] and Kelley and Gruber in USA [ 34 ], IA decreased the QOL physical effect. Further, in a study by Lu et al. in China, IA reduced QOL in terms of physical, psychological, and environmental aspects [ 35 ]. Fatehi et al. [ 36 ] in Iran showed that IA decreased the QOL in physical, psychological, and social dimensions [ 36 ]. The results of three studies in Taiwan [ 37 ], China [ 49 ], and the USA [ 38 ] indicated that IA decreased the QOL in physical, social, psychological, and environmental aspects. In addition to a small number of cross-sectional studies, which make the comparison and deduction of causal relationships difficult, differences in contexts and ignorance of the underlying factors affecting the QOL dimensions (such as unemployment, chronic diseases, mental/psychological disorders (depression, negative feelings, and stress)) can be considered as reasons for the contradiction between results on the Internet impact on QOL dimensions [ 45 , 50 , 51 ].
On the other hand, a study conducted in Taiwan shows three specific IA manifestations (compulsive, interpersonal, health, and time management problems) to reduce the physical dimensions of QOL among college students. A possible explanation is that participants with higher compulsivity may have impaired control over Internet use, thereby developing the other two types of IA problems manifested through unhealthy lifestyles, such as poor diet and sleep deprivation, leading to lower physical QOL. Also, compulsivity concerning Internet use may cause poor mental health (depression, loneliness, anxiety, and stress), harming psychological HRQOL [ 37 ].
A longitudinal study in Hong Kong show that time management problem (staying online longer than originally intended) is considered the most common among the participants during the study period [ 52 ]. Such findings show the need for the implementation of IA intervention programs (time management, self-regulation, and self-efficacy) to prevent the deterioration of IA-related physical HRQOL.
Despite the increasing influence of the Internet in daily life, in the last eight years, no meta-analysis study has been conducted to investigate the effect of IA on QOL, and this study is the first study in this period.
The quality of the studies has been determined according to the information in the articles, and it is possible that the studies were of higher quality but did not provide all the information and as a result were in the group of medium-quality articles.
The study protocol was not registered before the start for this review and is considered as one of the limitations of the study because there is a concern that it may add to the possible bias over time.
According to the present review results, the Internet negatively affects overall QOL, physically and psychologically. Since the Internet meets the needs of information, entertainment, and social interactions, its use is an integral part of everyday human life (both work and leisure). Internet use can also trigger a compulsive need in a minority of individuals. These findings show that IA should be regarded as a major health concern and incorporated into health education and intervention initiatives. Also, further studies are suggested, in particular with a cohort and empirical design in different societies, using standardized methodologies and analytical reports that facilitate the comparison.
The authors acknowledge all the participants who were involved directly and indirectly in the study and provided professional, technical, and nontechnical support.
IA: | Internet addiction |
QOL: | Quality of life |
OR: | Odds ratio |
HRQOL: | Health-related quality of life |
PRISMA: | Preferred reporting items for systematic reviews and meta-analysis |
WHO: | World Health Organization. |
Conflicts of interest.
There are no conflicts of interest regarding the publication of this study.
The complete search strategy of other databases is provided as Supplementary File 1.
BMC Psychiatry volume 24 , Article number: 565 ( 2024 ) Cite this article
Metrics details
Doomscrolling behavior is very common among college students. The purpose of this study was to evaluate the reliability and validity of the Chinese version of the Doomscrolling Scale, thus providing a scientific basis for its application among Chinese university students.
The Chinese version of Doomscrolling Scale was developed through translation and revision of the original scale, conducting item and factor analysis, and validating it with validation factor analysis. The psychometric properties of the Doomscrolling Scale were assessed in 2885 Chinese university students.
The internal consistency coefficients, two-month test-retest reliability, and split-half reliability of the Chinese version of the Doomscrolling Scale (including the 15-item and the 4-item short version) were high, and the mono-factorial scales fitted well to the theoretical model. Scores on the Chinese version of the Doomscrolling Scale were significantly associated with depression, anxiety, and smartphone addiction. The structural equation model indicates that doomscrolling can mediate the bidirectional relationship between insomnia disorder and depression.
The revised Chinese version of the Doomscrolling Scale is valid and reliable, which can facilitate research in this field. The association between doomscrolling and various mental disorders has been confirmed, and further research should be conducted to investigate its mechanisms of action.
Peer Review reports
The term “doomscrolling” first emerged in 2018 and was popularized by journalist Karen Ho [ 1 ]. It refers to a behavior observed in individuals who engage in continuous scrolling through social media news, fixating on distressing, depressing, or other negative information [ 2 ]. The act of consistently exposing oneself to negative news on social media and news feeds has been conceptualized as “doomscrolling”. This behavior is often defined as a habit, characterized by compulsively scrolling through social media and news updates, with users becoming obsessed with seeking out disheartening negative information [ 3 ]. Sharma et al. defined “doomscrolling” as the habitual and immersive scanning of timely negative information in social media news feeds [ 4 ]. From the aforementioned conceptualization, it is apparent that doomscrolling leads to a vicious cycle that drives individuals to compulsively consume negative information. Regardless of the severity of these negative stimuli, individuals eventually fall into an endless pattern of seeking negative information, consequently impacting their mental and physical health [ 5 , 6 ].
In an era where social media news is ubiquitous, excessive consumption of negative information can lead to psychological and behavioral issues such as depression, anxiety, and addiction. Prior research conducted on 747 social media users revealed that engaging in doomscrolling produces a sense of addictive excitement [ 7 ], which is posited to be a primary driver of doomscrolling behavior. In terms of negative consequences, studies have found that high frequency of doomscrolling is associated with greater severity of depression, increased anxiety about the future, reduced psychological well-being, and lower life satisfaction [ 7 ]. Research has shown that consuming only 15 min of a news program can increase state anxiety and mood dysregulation in college students [ 8 ]. Furthermore, individuals who engage with higher-intensity negative news are more likely to exhibit maladaptive behaviors [ 7 ]. Specifically, doomscrolling is associated with higher impulsivity, greater stimulus-seeking behavior, and lower motivation to avoid unhealthy behaviors. Additionally, consuming negative news similarly has an impact on individual behavior. Specifically, consuming negative news is linked to negative emotions, reduced prosocial behavior [ 9 ], decreased prosocial intentions [ 10 ], and lower self-control [ 4 ].
A significant external factor contributing to the development of doomscrolling is the personalized information delivery implemented by various news media and social platforms based on user preferences (i.e., The more negative information one reads, the more negative content related apps will push) [ 11 ]. This undoubtedly amplifies the exposure to negative information for individuals. Therefore, screening for negative information consumption holds critical significance in the prevention and intervention of adverse behaviors and psychological issues.
Sharma and colleagues developed a self-report measurement tool for doomscrolling [ 4 ], aiding researchers in exploring the relationships between doomscrolling and other psychological health variables. This unidimensional scale comprises 15 items (e.g., “I feel an impulse to seek bad news on social media, and it is becoming more frequent”), scored on a 7-point Likert scale, where 1 indicates “strongly disagree” and 7 indicates “strongly agree”. The sum of all items’ scores reflects the extent of an individual’s inclination toward consuming negative information, offering an accessible and comprehensible measurement approach.
Doomscrolling is a relatively novel concept that has been studied by only a few researchers. For instance, the reliability and validity of the Doomscrolling Scale were validated among individuals in Turkey [ 5 ]. However, there is currently a lack of research on negative information consumption and effective measurement tools in China. Compared to primary and secondary school students, college students in China have more leisure time and a higher level of autonomous consumption capability. Consequently, they tend to use smartphones more extensively [ 12 ], potentially increasing their exposure to negative information through social media feeds. Therefore, this study aims to revise the Doomscrolling Scale and examine its applicability among Chinese university students, thereby providing a reliable tool for investigating negative information consumption. In addition, because of the relationship between doomscrolling and insomnia and depression, we also explored the mediating role of doomscrolling in the bidirectional relationship between insomnia and depression through structural equation modeling.
The research focused on the validation of a doomscrolling questionnaire among the Chinese population. Based on the original scale, item analysis, exploratory and confirmatory factor analysis, and reliability analysis were conducted for both the 15-item and 4-item short versions of the questionnaire. Correlation analysis with the criterion-related questionnaire was also performed.
The study procedure was submitted to the Ethics Committee of the Chongqing Key Laboratory of Psychological Diagnosis and Educational Technology for Children with Special Needs for ethical approval. The submitted materials included the research design, questionnaire content, data collection methods, informed consent forms, participant recruitment procedures, and potential risk assessments. The Ethics Committee evaluated the ethicality, safety, and scientific validity of the study and eventually granted ethics approval (Ethics Number: CSTJ-RE-20230620004). Additionally, the study was conducted anonymously, and the data were securely stored by designated personnel to fully protect the privacy of the participants and enhance the reliability of the results. As a token of appreciation, participants were entered into a draw with a 1/10 chance of winning 1 RMB upon completing the questionnaire.
On June 26 and 27, 2023, an initial survey was conducted among college students from two tertiary institutions in Chongqing, China using a convenient sampling method. A total of 2938 college students participated in this survey. The survey questionnaire was presented and data were collected through quick response (QR) codes generated by the Wenjuanxing platform ( www.wjx.cn ). The survey was administered by the mental health centers of the university. The survey QR codes were distributed to class advisors by the research team, who then forwarded them to class WeChat groups. Participants scanned the QR codes to take part in the survey. Prior to beginning the survey, participants were presented with the purpose of the study and provided informed consent. Choosing to answer the questionnaire implied their consent to participate. The inclusion criteria were: (1) college or university students currently enrolled in a specialized or undergraduate program; (2) an age of 18 years or older; (3) being capable of using internet tools such as mobile phones or computers. The study did not set explicit exclusion criteria, but during data analysis, responses from participants who took too short a time to complete the questionnaire were excluded.
The survey was conducted online, and all questions were set as mandatory, minimizing the occurrence of missing data. For the sake of survey reliability, participants who completed the questionnaire in less than 120 s were excluded, given that completing the questionnaire within such a short timeframe might lead to careless responses. The time threshold was determined based on the number of items and the average fastest completion time by researchers familiar with the questionnaire content. Additionally, we ensured that the proportion of excluded data was less than 5% of the total data, which is considered not to affect the sample’s representativeness [ 13 ]. Additionally, since age was an open-ended question, participants who provided incorrect information were also excluded. Finally, 53 participants (1.80%) were excluded, resulting in a final analysis with data from 2885 college students, with 598 participants in Sample 1 and 2287 participants in Sample 2. The effective response rate was 98.2%. The participants ranged in age from 18 to 23 (M = 19.36, SD = 0.93), and 1726 of them (59.83%) were male.
On August 24, 2023, a retest was conducted using the same procedures and methods as the initial test, involving 1251 participants. A total of 1251 sets of data were collected in Sample 3. A total of 48 questionnaires (3.84%) were excluded from the analysis due to a low response time of less than 50 s for 24 items. The specific exclusion criteria were consistent with that of the initial test. Ultimately, 1203 questionnaires were included for analysis, with an effective response rate of 96.16%. The average age of the participants was 19.46 (SD = 0.88), and 607 of them were male.
Doomscrolling scale.
The Doomscrolling Scale, developed by Sharma et al. in 2022, was employed for assessment [ 4 ]. This scale comprises 15 items (e.g., “I feel an urge to seek bad news on social media, more and more often”), rated on a 7-point Likert scale, where 1 indicates “strongly disagree” and 7 indicates “strongly agree”. Higher scores on the questionnaire indicate a stronger inclination toward doomscrolling. The internal consistency coefficients for the original study and this study were 0.960 and 0.982, respectively. Two experts in psychology and English, and one expert in public management and English, were invited to translate the Doomscrolling Scale, producing the initial Chinese draft. Subsequently, the Chinese version was back-translated into English and checked by native English speakers, revealing no significant discrepancies. In this way, the Chinese version of Doomscrolling Scale was developed. For a more comprehensive understanding of the translation process, please refer to the supplementary materials.
The Patient Health Questionnaire (PHQ-9), based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) diagnostic criteria, consists of 9 items [ 14 ]. This self-report questionnaire employs a four-point Likert scale ranging from 0 to 3 for each item, with a total score between 0 and 27. A higher total score corresponds to a more severe level of depression. The internal consistency coefficients for the original study and this study were 0.890 and 0.904, respectively.
Generalized Anxiety Disorder (GAD-7) Scale for Measuring Anxiety Levels in university students [ 15 ]. The GAD-7 consists of 7 items and is a self-report questionnaire. Each item is rated on a Likert four-point scale ranging from 0 to 3, with a total score ranging from 0 to 21. A higher total score indicates a higher level of anxiety. The internal consistency coefficients for the original study and this study were 0.920 and 0.939, respectively.
A simplified version of the Smartphone Addiction Scale (SAS-SV) was employed for measuring smartphone usage [ 16 ]. The SAS-SV is a unidimensional self-report questionnaire comprising 10 items. It employs a 6-point Likert scale (1 indicating “strongly disagree” and 6 indicating “strongly agree”). The internal consistency coefficients for the original study and this study were 0.967 and 0.932, respectively.
We performed statistical analyses using SPSS version 26.0 and Amos version 21.0. We conducted a series of exploratory factor analyses (EFA), a multivariate statistical analysis method used to explore potential relationships between variables. Factor analysis reveals the intrinsic structure among variables and simplifies the data by reducing its dimensionality [ 17 ]. Confirmatory factor analysis (CFA) was used to test whether the current data fits the structural model from the EFA and the original scale. CFA assesses the reliability of the theoretical model by comparing the fit between the observed data and the theoretical model [ 18 ]. CFA was conducted using maximum likelihood estimation, and the dimensions were derived from EFA (with only one dimension) from AMOS Graphics. The structural validity of the Chinese version of Doomscrolling Scale was assessed. Indices such as Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Incremental Fit Index (IFI), and Standardized Root Mean Square Residual (SRMR) were used to assess model fit. Fit standards were adopted as follows: RMSEA ≤ 0.08, SRMR ≤ 0.08, CFI ≥ 0.90, TLI ≥ 0.90, and item loadings > 0.60, in accordance with criteria established by Bowman and Goodboy [ 19 ]. If the results of the CFA did not meet these fit standards, revisions were planned for items with substantial residual values. Finally, the revised Chinese version of the 15-item Doomscrolling Scale and the 4-item short version of the Doomscrolling Scale were subjected to correlation analysis with depression, anxiety, and smartphone addiction. The detailed steps of the analysis were as follows.
Initially, reliability testing and item analysis were conducted on the collected sample 1. The critical ratio method, total score correlation method, and reliability tests were employed for item selection. The unidimensional structure of the 15-item and 4-item Doomscrolling Scale were validated using exploratory and validation factor analyses. Then, convergent validity was established with reference to the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Smartphone Addiction Scale-Short Version (SAS-SV). The reliability of this questionnaire was assessed using Cronbach’s α, McDonald’s omega (ω), test-retest reliability, and split-half reliability.
Table 1 presents the demographic information of the participants. The majority of participants were freshmen and sophomores, accounting for 79.58% and 18.99% of the total, respectively. Over 70% of the participants were from rural areas, and only 15.08% reported urban household registration. The vast majority of participants reported a medium or low economic status, with 62.63% of participants indicating a medium economic status. More than 32.26% of participants used their smartphones for 2–4 h per day, and 58.75% used them for more than 4 h. Nearly half of the participants (45.93%) reported mild or higher levels of depressive symptoms.
Correlation analyses of Doomscrolling Scale scores for each item and the total scores showed correlation coefficients ranging from 0.793 to 0.936. Effective items were screened according to the critical ratio (CR). Participants with the top 27% of total scores were grouped as the high-score group, and those with the bottom 27% were grouped as the low-score group. An independent samples t-test was then conducted to identify items that could not effectively differentiate participant responses, and these items were removed to improve the reliability and validity of the scale [ 20 ]. Independent sample t-tests were conducted to compare the scores of these two groups on each item. The results revealed significant differences across all items between the high- and low-score groups ( p < 0.001), indicating good discriminant validity.
The EFA results showed a Kaiser-Meyer-Olkin (KMO) value of 0.964 and a significant Bartlett’s test of sphericity ( p < 0.05), suggesting the suitability of the data for factor analysis. Hence, employing maximum variance rotation, a single common factor was extracted based on eigenvalues > 1, contributing to a cumulative variance of 78.11%. Factor loadings ranged from 0.784 to 0.939, indicating a well-structured scale. Factor loadings, descriptive statistics, and item-total score correlations are presented in Table 2 . CFA was conducted to assess the model fit of the Chinese version of the 15-item Doomscrolling Scale. The items were fit into a single factor, with the model fit indices yielding χ ²/ df = 40.685, RMSEA = 0.132, SRMR = 0.034, CFI = 0.930, TLI = 0.918, and IFI = 0.930. Although there was substantial item intercorrelation, omitting items did not improve model fit. Consequently, modification indices were examined, and 13 residual covariances were added to the model (between items 1 and 2, 1 and 3, 2 and 3, 4 and 5, 5 and 6, 6 and 7, 8 and 9, 9 and 10, 12 and 13, 12 and 15, 13 and 14, 13 and 15, 14 and 15), resulting in improved fit indices: χ ²/ df = 14.911, RMSEA = 0.078, SRMR = 0.019, CFI = 0.979, TLI = 0.971, and IFI = 0.979. All these indices met acceptable model fit criteria.
We made adjustments to some of the paths, item 1: I feel an urge to seek bad news on social media, more and more often, item 2: I lose track of time when I read bad news on social media. Both items explore an individual’s behavioral tendencies and emotional responses on social media, as well as their perception of time spent on social media. However, the two differ in their temporal responses, with item 1 focusing on the frequency of social media use, whereas item 2 focusing on the duration of social media use. Items 1 and 3 exhibit significant covariation, as both pertain to the use of social media push notifications, with item 1 displaying particularly high covariation. But item 1 emphasizes an increase in usage frequency, while item 2 emphasizes the behavior of constantly refreshing; items 6 and 7 both pertain to negative emotions individuals experience online, such as feelings of anxiety and panic, but there are differences in the intensity of the reactions. The other revised paths also have high commonalities in some aspects between each other. Therefore, it is necessary to modify these paths to improve the fit and ensure they align with the data’s structure and relationships. Consistent with the original scale study, the corrected residuals were predominantly from adjacent items, possibly due to the presentation order rather than unincorporated multidimensionality [ 4 ].
The Chinese version of the 15-item Doomscrolling Scale exhibited significant positive correlations with the PHQ-9, GAD-7, and SAS-SV. The total score of the Chinese version of the 15-item Doomscrolling Scale was more strongly correlated with smartphone addiction scores than with depression and anxiety scores (Table 3 ). The revised Chinese version of the 15-item Doomscrolling Scale demonstrated internal consistency (Cronbach’s alpha) of 0.98, McDonald’s omega (ω) of 0.98, test-retest reliability of 0.98, and split-half reliability of 0.94.
The EFA results for the 4-item Brief Scale showed a KMO value of 0.736 and a significant Bartlett’s test of sphericity ( p < 0.05), confirming suitability for factor analysis. A single common factor was extracted in the factor analysis, contributing to a cumulative variance of 79.11%. All items had factor loadings > 0.6, indicating good structural validity.
CFA was conducted for the brief Doomscrolling Scale. The initial model fit indices did not meet the fit criteria, prompting model modification. The results of the revised model and related fit indices are presented in Table 4 . Given that each item loaded on a single factor, although with substantial contributions, and considering the strong intercorrelation between items, adjustments were made for large residual values between items 1 and 2. The modified model yielded primary fit indices of χ ²/ df = 5.204, RMSEA = 0.043, SRMR = 0.002, CFI = 0.999, TLI = 0.997, and IFI = 0.999, all meeting acceptable model fit criteria. The improved model fit indicated good structural validity.
The 4-item brief Doomscrolling Scale demonstrated significant positive correlations (Table 3 ) with PHQ-9, GAD-7, and SAS-SV. The internal consistency of the short version of the 4-item Doomscrolling Scale was 0.91, the McDonald’s omega (ω) was 0.95, test-retest reliability was 0.97, and split-half reliability was 0.83.
After confirming the validity of the Doomscrolling Scale among the Chinese population, we further explored the mediating role of doomscrolling behavior in the bidirectional relationship between insomnia disorder and depression. This aims to enhance our understanding of the relationship between insomnia disorder and depression.
Study 2 comprised 578 college students recruited following the same procedure as Study 1. The sample consisted of 361 male students and 217 female students, with a mean age of 19.52 (SD = 1.06) years, ranging from 18 to 23 years. The average score for depression was 4.89 (SD = 4.73), and the average score for insomnia disorder was 0.79 (SD = 0.83).
Insomnia disorder was assessed using sleep condition indicators [ 21 ], with the online version of the scale comprising 7 items. Each item is scored on a Likert scale of 0–4 points. Scores ranging from 0 to 2 indicate no clinical diagnosis of insomnia, while scores greater than 2 are considered indicative of clinical insomnia disorder. Higher total scores in this study indicate poorer sleep [ 21 ]. The internal consistency coefficients of the sleep condition indicators in the original study and this study were 0.857 and 0.889, respectively. Assessment of depressive symptoms was conducted using the PHQ-9, with relevant scale information referenced in Study 1.
First, Spearman correlation analysis was used to explore the correlation between insomnia disorder, depression, and doomscrolling. Subsequently, the Mplus 8.3 software was used for structural equation modeling (SEM) and analysis. SEM is a multivariate data analysis method used to explore complex relationships between hypothesized structures and indicators [ 22 ]. This method is typically used to explain hypothesized causal relationships between latent variables. In a structural model, the relationships between variables are usually represented by diagrams with arrows, which indicate the predictive and predicted relationships, and provide the magnitude of these hypothesized effects [ 23 ]. This method is suitable for exploring the bidirectional predictive relationship between depression and insomnia disorders, which may be mediated by doomscrolling behavior. Maximum likelihood estimation and 5000 bootstrap samples were employed for model estimation. Two mediation models were constructed separately with insomnia and depression as independent variables.
The distribution of participants’ demographic information was similar to that in Study 1 (Table 1 ). The correlation analysis revealed a significant positive correlation between doomscrolling and insomnia disorder ( r = − 0.47, p < 0.01), as well as a significant positive correlation with depression ( r = − 0.42, p < 0.01). The insomnia-depression mediation model showed that doomscrolling mediated the relationship between insomnia disorder and depression in a saturated model, with all path coefficients being significant (Fig. 1 a). In the insomnia-depression model, the total effect of insomnia disorder on depressive symptoms was 0.40, with a mediation effect of 0.25, accounting for 62.5% of the total effect. This indicated that 62.5% of the influence of insomnia disorder on depressive symptoms is mediated by doomscrolling (Table 5 ). The mediation model of depression and insomnia is also a saturated model, with all paths being significant (Fig. 1 b). The total effect value of the model was 0.40, with a direct effect from depression to insomnia of 0.21 and a mediation effect of 0.19. The mediation effect accounted for 47.5% of the total effect (Table 5 ).
Mediation models for insomnia disorder and depression indicators via doomscrolling ( a . doomscrolling mediates insomnia and depression; b . doomscrolling mediates depression and insomnia)
Self-reports from news and social media users indicated that doomscrolling was characterized by individuals compulsively showing interest in timely and negative information, often accompanied with anxiety, leading them to be immersed in large volumes of negative news for extended periods [ 3 , 24 ]. Consequently, we believe that excessive attention to and continued consumption of negative news may increase individuals’ fears and uncertainties about the future, exacerbating depression and anxiety among viewers [ 25 , 26 ]. Therefore, it is crucial to investigate populations inclined towards doomscrolling. This study involved the adaptation of the Doomscrolling Scale developed by Sharma et al. into a Chinese version, providing an effective measurement tool tailored to the doomscrolling behavior of Chinese university students, thereby facilitating research on doomscrolling behavior in China.
EFA revealed that the Chinese version of Doomscrolling Scale was unidimensional, consistent with the one-dimensional structure of the original scale [ 4 ]. CFA results indicated that the fit indices RMSEA for both the 15-item and the abbreviated 4-item Chinese versions of the scale were above the recommended standards before modification [ 27 ]. Therefore, a similar approach to previous research was adopted to modify the fit model of the scale, achieving acceptable standards [ 4 ]. One possible reason for the elevated RMSEA values could be that both the revised Chinese version and the original scale were unidimensional. Some studies argued that traditional cutoff values may not necessarily apply to fit standards for single-factor models, as fit indices have different sensitivities to missing cross-loadings and factor covariates in single-factor models. Thus, the appropriateness of using these cutoff values in single-factor models remains uncertain [ 28 ]. Based on other good model fit indices, such as SRMR and CFI, we considered the model fit in the current study to be acceptable, as the RMSEA index was also not considered in the Turkish revision of Doomscrolling Scale [ 5 ].
A comparative analysis with the original study showed that the internal consistency reliability of the Chinese version was 0.98, slightly higher than that of the original scale (0.96), with both versions’ internal consistency coefficients exceeding the preferably acceptable value of 0.8 [ 29 ]. Additionally, the test-retest reliability of the Chinese version was 0.98, which was not mentioned in the original scale but the reliability was similar. In terms of construct validity, the results for RMSEA, SRMR, and CFI indicators are consistent (supplementary material table S1 ), but the chi-square to degrees of freedom ratio (Chinese version: 14.911 vs. original version: 4.167) was higher than that of the original study, likely due to the large sample size in this study [ 30 ]. These findings support the reliability and validity of the Chinese version of Doomscrolling Scale, ensuring that the translated version is equivalent to the original English version and that the findings are reliable across different language contexts.
Correlation analysis revealed a significant correlation between Doomscrolling scores and depression, anxiety, and smartphone addiction. Research has unveiled a relationship between social media usage and increased depressive and anxious emotions [ 31 ], i.e., individuals engaging in more doomscrolling were more likely to experience psychological distress [ 5 ]. Negative news followers exhibited compulsive behavior in consuming adverse information, making them more prone to mental health issues such as depression and anxiety [ 32 ], and this browsing behavior may also be related to smartphone usage. Correlational validity analysis of the Chinese version of the 15-item Doomscrolling Scale and the abbreviated 4-item version showed that their total scores were higher in correlation with smartphone addiction scores than with depression and anxiety scores. This suggests that individuals addicted to smartphones may find it challenging to break free from the compulsion to browse negative information, as addiction can lead to problematic usage of social media platforms and the internet [ 5 ]. However, smartphone addiction is prevalent among Chinese university students [ 33 ], which may increase the risk of doomscrolling behavior among individuals. Research suggests that the widespread availability of highly functional modules in smartphones among Chinese university students is a significant factor contributing to smartphone addiction [ 34 ]. The powerful features of smartphones can inundate users with various types of information, and the push of negative news may be a critical contributing factor for the frequent co-occurrence of depression [ 35 ] and anxiety [ 36 ] among smartphone addicts. This important topic warrants further exploration in the future.
However, despite the potential risks associated with the doomscrolling behavior, there is currently little government attention given to this issue. In China, the use of social media among university students has become quite common [ 37 ], and there are instances of excessive usage of platforms such as Douyin [ 38 ], Weibo [ 39 ], WeChat [ 40 ], and Bilibili. Without exception, these platforms analyze individuals’ browsing preferences and habits to push targeted content [ 11 ], which is one of the external factors leading to their excessive use of media software. However, this has garnered little attention from relevant authorities. We believe that if individuals with doomscrolling behavior continue to be exposed to more negative news in the long term, their doomscrolling behavior may be further exacerbated, thereby causing or worsening mental health issues. Therefore, we urge stakeholders to prioritize this important issue.
Revising the Chinese version of Doomscrolling Scale holds significant practical importance. Firstly, this measurement scale empowers researchers to assess individuals’ engagement in doomscrolling. Research has convincingly established a strong link between social media addiction and generalized problematic internet use, suggesting that doomscrolling represents an excessive and potentially dysfunctional facet of social media behavior [ 4 ]. Consequently, quantifying the doomscrolling behavior enables researchers to investigate it alongside other problematic behaviors. Secondly, increased awareness of doomscrolling behaviors can be beneficial for users, as it encourages the adoption of self-regulation strategies and alternative approaches to curbing excessive exposure to negative media. For example, users may learn to consume mobile news in smaller, deliberate portions [ 41 ]. Lastly, concerning the management of the current Chinese university students, utilizing this scale for assessment can inform decision-makers about the prevalence of negative information consumption and excessive social media use. Armed with this knowledge, it can assist mental health professionals in better identifying high-risk groups and implementing personalized interventions, as well as more precisely identifying college students who exhibit excessive reactions or are filled with fear and negative expectations towards the future due to negative information [ 6 , 42 ]. Thus, targeted and constructive measures can be implemented to curb these behaviors. For example, different intervention plans are provided for different degrees of doomscrolling, including psychological counseling and cognitive-behavioral therapy [ 43 ]. Addressing insomnia and depression arising from negative information through timely intervention can further prevent more serious psychological problems among college students.
Finally, we investigated the mediating role of doomscrolling between insomnia and depression. The results indicated that doomscrolling mediated the bidirectional relationship between insomnia and depression, with approximately half of the effect being mediated by doomscrolling. This further supports insomnia as one of the factors leading to depression, and the behavior of doomscrolling during insomnia may further exacerbate and perpetuate depressive symptoms [ 44 ]. Similarly, engaging in doomscrolling may also increase insomnia among individuals with depression [ 45 ]. These findings suggest that when university students experience insomnia, they should avoid doomscrolling, particularly at night.
To complement the lack of effective measurement tools for doomscrolling behavior in the Chinese scale, our revised Chinese version of the 15-item Doomscrolling Scale and the 4-item short version have good reliability and validity and can be used as measurement tools in studies of Chinese college students. In addition, the short version of Doomscrolling Scale is easy to use in conjunction with other addiction scales and mental disorder scales, and is also suitable for the time-series assessment of individual behaviors. The revision of this scale can promote the development of relevant research in China. On one hand, with the reports of doomscrolling behavior, Chinese college students gradually increase their awareness of doomscrolling, and may be wary of news media and social media full of negative content, thus reducing their unreasonable behavior of doomscrolling; On the other hand, the reports of relevant studies may attract the attention of university management and urge the implementation of effective management measures. Finally, we also call on relevant news or social media companies to block or reduce relevant negative information push. For example, the “personalized recommendation” function in the mobile app can be turned off to reduce browsing opportunities. In addition, the government should enact corresponding policies to supervise and restrict the information push mechanism of media companies.
First, this study has certain limitations in terms of sample representativeness, mainly due to the uneven distribution of participant grades, small sample size, and the use of convenience sampling, which may result in a homogeneous sample and affect the reliability and generalizability of the results. Given that the participants in this study were primarily freshmen, the findings may not be representative of the overall university student population, especially considering that there may be differences across grades in dimensions such as depression, insomnia disorders, and mobile phone usage time. Similar influences may also arise from the age of the participants. Previous research has indicated that freshmen typically sleep less due to social media usage [ 46 ], and that the prevalence of depression is higher among seniors compared to freshmen [ 47 , 48 ]. These differences may affect university students’ doomscrolling behavior. Therefore, caution should be exercised when generalizing the findings of this study. Future studies should consider increasing the sample size and balancing the number of participants across different grades to enhance the representativeness and generalizability of the results.
Second, although we adopted an anonymous approach during the survey and used standardized scales, emphasizing that there were no right or wrong answers, the self-report method may still present response biases. For example, when answering the depression scale, individuals might respond in a socially desirable manner [ 49 ], often reporting fewer psychological issues. To address social desirability bias, future research could consider using diverse data collection methods for cross-validation or incorporating a social desirability scale to identify potentially biased responses [ 50 ]. Furthermore, some scales require participants to report their performance over a past period, which may be influenced by recall bias [ 51 ]. For instance, feelings of sadness experienced in the past two weeks might be forgotten at the time of response. Additionally, the Likert scale scoring method may lead to extreme response tendencies and fail to capture subtle changes. Future research could consider using scoring methods that can capture fine changes, such as the Visual Analog Scale [ 52 ].
Third, the use of a cross-sectional design in this study cannot capture the long-term effects of doomscrolling on mental health. This is particularly relevant as depressive symptoms and doomscrolling behavior are significantly influenced by time. Future research should consider adopting a longitudinal design to track individuals’ doomscrolling behavior and mental health over a period of time. This would help reveal the causal relationship between doomscrolling and mental health issues such as insomnia or depression, and provide valuable insights into the dynamic changes of related variables over time. Furthermore, a longitudinal design could serve as a basis for developing preventive interventions, especially in mitigating the negative impact of doomscrolling on mental health at an early stage.
Finally, in this study, we did not control confounding variables, which might affect the true relationship between the independent and dependent variables [ 53 ]. One potential confounding factor is the frequency of social media use. Studies have shown that excessive use of social media can lead to addiction [ 54 ], which is associated with severe depressive symptoms [ 55 ]. Similarly, prolonged social media use can delay sleep time, leading to insomnia [ 56 ]. Therefore, future research could consider how the social media use frequency or social media addiction influence the effects of doomscrolling on depression and insomnia. Another potential confounding factor is the type of negative news, which may include public health crises such as the COVID-19 pandemic in 2020 [ 57 ]; natural disasters such as the destruction caused by major earthquakes [ 58 ]; and crime and violence events. Exploring the role of news types in doomscrolling behavior will enhance our understanding of doomscrolling. In conclusion, controlling potential confounding variables is crucial for improving the internal validity of research when exploring the relationship between depression and insomnia disorders.
This study aimed to validate the Chinese version of Doomscrolling Scale among Chinese university students. The Chinese version demonstrated high reliability and validity, showing significant associations with depression, anxiety, and smartphone addiction. Additionally, it revealed that doomscrolling may mediate the relationship between insomnia disorder and depression. This validated measurement tool provides a foundation for further research on the mechanisms and impacts of doomscrolling on mental health.
Data is provided upon request to the corresponding author.
Quick response
Standard deviation
Patient health questionnaire
Diagnostic and statistical manual of mental disorders
Generalized anxiety disorder
Smartphone addiction scale short version
Exploratory factor analyses
Confirmatory factor analysis
Root mean square error of approximation
Comparative fit index
Tucker‒Lewis index
Incremental fit index
Standardized root mean square residual
Kaiser‒Meyer‒Olkin
Content validity index
Critical ratio
Garcia-Navarro L. Your Doomscrolling Breeds Anxiety. Here’s How To Stop The Cycle. Health News Florida. 2020. https://health.wusf.usf.edu/health-news-florida/2020-07-19/your-doomscrolling-breeds-anxiety-heres-how-to-stop-the-cycle . Accessed 23 Sep 2023.
Price M, Legrand AC, Brier ZMF, van Stolk-Cooke K, Peck K, Dodds PS, et al. Doomscrolling during COVID-19: the negative association between daily social and traditional media consumption and mental health symptoms during the COVID-19 pandemic. Psychol Trauma. 2022;14:1338–46.
Article PubMed PubMed Central Google Scholar
Salisbury L. On not being able to read: doomscrolling and anxiety in pandemic times. Textual Pract. 2023;37:887–918.
Article PubMed Google Scholar
Sharma B, Lee SS, Johnson BK. The dark at the end of the tunnel: Doomscrolling on social media newsfeeds. Technology, Mind, and Behavior. 2022;3.
Satici SA, Gocet Tekin E, Deniz ME, Satici B. Doomscrolling Scale: its Association with personality traits, psychological distress, Social Media Use, and Wellbeing. Appl Res Qual Life. 2023;18:833–47.
Anand N, Sharma MK, Thakur PC, Mondal I, Sahu M, Singh P, et al. Doomsurfing and doomscrolling mediate psychological distress in COVID-19 lockdown: implications for awareness of cognitive biases. Perspect Psychiatr Care. 2022;58:170–2.
Shabahang R, Kim S, Hosseinkhanzadeh AA, Aruguete MS, Kakabaraee K. Give your thumb a break from surfing tragic posts: potential corrosive consequences of social media users’ doomscrolling. Media Psychol. 2023;26:460–79.
Article Google Scholar
Szabo A, Hopkinson KL. Negative psychological effects of watching the news in the television: relaxation or another intervention may be needed to buffer them! Int J Behav Med. 2007;14:57–62.
Han L, Sun R, Gao F, Zhou Y, Jou M. The effect of negative energy news on social trust and helping behavior. Comput Hum Behav. 2019;92:128–38.
Baden D, McIntyre K, Homberg F. The impact of Constructive News on affective and behavioural responses. J Stud. 2019;20:1940–59.
Google Scholar
Thurman N. Making ‘The Daily Me’: Technology, economics and habit in the mainstream assimilation of personalized news. Journalism. 2011;12:395–415.
Liu M. College students’ social anxiety, mobile phone addiction and self conceptual relationship research. China West Normal University; 2019.
White IR, Higgins JPT, Wood AM. Allowing for uncertainty due to missing data in meta-analysis—part 1: two‐stage methods. Stat Med. 2008;27:711–27.
Kroenke K, Spitzer RL, Williams JBW. The PHQ-9. J Gen Intern Med. 2001;16:606–13.
Article CAS PubMed PubMed Central Google Scholar
Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder. Arch Intern Med. 2006;166:1092.
Kwon M, Kim D-J, Cho H, Yang S. The Smartphone Addiction Scale: Development and Validation of a short version for adolescents. PLoS ONE. 2013;8:e83558.
Watkins MW. Exploratory factor analysis: a guide to best practice. J Black Psychol. 2018;44:219–46.
Gallagher MW, Brown TA. Introduction to Confirmatory Factor Analysis and structural equation modeling. Handbook of quantitative methods for Educational Research. Rotterdam: Sense; 2013. pp. 289–314.
Chapter Google Scholar
Bowman ND, Goodboy AK. Evolving considerations and empirical approaches to construct validity in communication science. Ann Int Commun Assoc. 2020;44:219–34.
DeVellis RF. Scale Development Theory and Applications (Fourth Edition). SAGE Publication. 2017;4.
Espie CA, Kyle SD, Hames P, Gardani M, Fleming L, Cape J. The Sleep Condition Indicator: a clinical screening tool to evaluate insomnia disorder. BMJ Open. 2014;4:e004183.
Hair JF, Hult GTM, Ringle CM, Sarstedt M, Danks NP, Ray S. An Introduction to Structural Equation Modeling. 2021. pp. 1–29.
Neuberg LG. Causality: models, reasoning, and inference. Econ Theory. 2003;19:675–85.
Warzel C. I need to stop scrolling: The diminishing returns of constant COVID news. substack. 2021. https://warzel.substack.com/p/i-need-to-stop-scrolling . Accessed 23 Sep 2023.
Bhatt N, Bhatt B, Gurung S, Dahal S, Jaishi AR, Neupane B, et al. Perceptions and experiences of the public regarding the COVID-19 pandemic in Nepal: a qualitative study using phenomenological analysis. BMJ Open. 2020;10:e043312.
Kim J, Rim SJ, Jo M, Lee MG, Park S. The Trend of Psychiatric visits and Psychiatric Medication prescription among people tested for SARS-CoV-2 during the initial phase of COVID-19 pandemic in South Korea. Psychiatry Investig. 2022;19:61–71.
Fan X, Sivo SA. Sensitivity of fit indices to Model Misspecification and Model types. Multivar Behav Res. 2007;42:509–29.
McNeish D, Wolf MG. Dynamic fit index cutoffs for one-factor models. Behav Res Methods. 2022;55:1157–74.
Sousa VD, Rojjanasrirat W. Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: a clear and user-friendly guideline. J Eval Clin Pract. 2011;17:268–74.
Pan H, He W, Lin B, Zhong X. Factors influencing HPV vaccination willingness among men who have sex with men in China: a structural equation modeling analysis. Hum Vaccin Immunother. 2022;18:2038504.
Vannucci A, Flannery KM, Ohannessian CM. Social media use and anxiety in emerging adults. J Affect Disord. 2017;207:163–6.
Donahue RD. The structural relationships among generalized anxiety, obsessions-compulsions, and depression at the syndrome and sub-syndrome level. Behav Res Ther. 2005;43:1587–609.
Yang Y. Study on the influence of college students psychological craving for Smart-phone on Smart-phone addiction and its intervention. Jiangnan University; 2022.
Kong L. Research on the relationship between College Students’ Mobile phone addition tendency,negative life events and social support. J Pingdingshan Univ. 2023;38:123–8.
Zhang X, Gao F, Kang Z, Zhou H, Zhang J, Li J, et al. Perceived academic stress and depression: the mediation role of Mobile phone addiction and sleep quality. Front Public Health. 2022;10:760387.
De-Sola J, Talledo H, Rubio G, de Fonseca FR. Development of a mobile phone addiction craving scale and its validation in a Spanish Adult Population. Front Psychiatry. 2017;8:90.
Lei H, Huang Y, Chai Y, Zhang X. Social Media Disorder, Mental Health, and validation of the Chinese Version of 27-Item Social Media Disorder Scale in Chinese College Students. Front Public Health. 2022;10:942720.
Yang M. A study on the influencing factors and countermeasures of excessive use of TikTok APP by College Students. Southwest University; 2023.
Chen J. Relations between Narcissim and Excessive Use of Microblog of College students: the Mediating Effect of interpersonal relationship disorder and Microblog Use Motivation. Shaanxi Normal University; 2018.
Ma X, Huang H, Yao Z, Zhao S, Chen H. The relationship between sense of security of college students and their overuse of WeChat: mediating effect of loneliness. Psychologies. 2023;18:87–9.
Molyneux L. Mobile News Consumption. Digit Journalism. 2018;6:634–50.
Stupinski AM, Alshaabi T, Arnold MV, Adams JL, Minot JR, Price M, et al. Quantifying changes in the Language used around Mental Health on Twitter over 10 years: Observational Study. JMIR Ment Health. 2022;9:e33685.
Zargaran D, Walsh C, Koumpa FS, Ashraf MA, White AJ, Patel N et al. Comment on Internet-Based Cognitive Behavioral Therapy With Real-Time Therapist Support via Videoconference for Patients With Obsessive-Compulsive Disorder, Panic Disorder, and Social Anxiety Disorder: Pilot Single-Arm Trial. J Med Internet Res. 2020;22:e13234.
Li C-T, Bai Y-M, Lee Y-C, Mao W-C, Chen M-H, Tu P-C, et al. High dosage of hypnotics predicts subsequent sleep-related breathing disorders and is associated with worse outcomes for depression. Sleep. 2014;37:803–9. 809A-809B.
Sivertsen B, Salo P, Mykletun A, Hysing M, Pallesen S, Krokstad S, et al. The Bidirectional Association between Depression and Insomnia. Psychosom Med. 2012;74:758–65.
Xu X, Lin Q, Zhang Y, Zhu R, Sharma M, Zhao Y. Influence of WeChat on sleep quality among undergraduates in Chongqing, China: a cross-sectional study. Springerplus. 2016;5:2066.
Liu X, Ping S, Gao W. Changes in undergraduate students’ Psychological Well-Being as they experience University Life. Int J Environ Res Public Health. 2019;16.
Chen Y, Liu X, Chiu DT, Li Y, Mi B, Zhang Y et al. Problematic social media use and depressive outcomes among College students in China: observational and experimental findings. Int J Environ Res Public Health. 2022;19.
Miller PH, Baxter SD, Royer JA, Hitchcock DB, Smith AF, Collins KL, et al. Children’s social desirability: effects of test assessment mode. Pers Individ Dif. 2015;83:85–90.
McCrae RR, Costa PT. Social desirability scales: more substance than style. J Consult Clin Psychol. 1983;51:882–8.
Silberstein SD. Preventive treatment of headaches. Curr Opin Neurol. 2005;18:289–92.
Gallagher EJ, Bijur PE, Latimer C, Silver W. Reliability and validity of a visual analog scale for acute abdominal pain in the ED. Am J Emerg Med. 2002;20:287–90.
Greenland S, Pearl J, Robins JM. Confounding and collapsibility in causal inference. Stat Sci. 1999;14.
Chegeni M, Nakhaee N, Shahrbabaki ME, Mangolian Shahrbabaki P, Javadi S, Haghdoost A. Prevalence and motives of Social Media Use among the Iranian Population. J Environ Public Health. 2022;2022:1490227.
Punyanunt-Carter NM, Cruz JJD, La, Wrench JS. Analyzing College Students’ Social Media Communication Apprehension. Cyberpsychol Behav Soc Netw. 2018;21:511–5.
Shimoga SV, Erlyana E, Rebello V. Associations of Social Media Use with Physical Activity and Sleep Adequacy among Adolescents: cross-sectional survey. J Med Internet Res. 2019;21:e14290.
Karimi-Sari H, Sharafi H, Rezaee-Zavareh MS, Alavian SM. Harm reduction during the COVID-19 outbreak in Iran. Lancet Psychiatry. 2020;7:e57.
Nagamine M, Giltay EJ, Shigemura J, van der Wee NJ, Yamamoto T, Takahashi Y, et al. Assessment of factors Associated with Long-Term Posttraumatic stress symptoms among 56 388 first responders after the 2011 Great East Japan Earthquake. JAMA Netw Open. 2020;3:e2018339.
Download references
Not applicable.
Authors and affiliations.
School of Educational Sciences, Chongqing Normal University, Chongqing, 401331, China
Lu Yang & Tao Wang
Chongqing Key Laboratory of Psychological Diagnosis and Education Technology for Children with Special Needs, Chongqing, China
Department of Medical English, School of Basic Medicine, Army Medical University, Chongqing, 400038, China
Xuejiao Tan & Kuiliang Li
Chongqing Vocational Institute of Safety & Technology, Chongqing, China
School of Psychology, Shaanxi Normal University, Xi’an, China
Kuiliang Li
You can also search for this author in PubMed Google Scholar
T.W. and K.L. contributed to the conception and design of the study. L.Y., K.L., and X.T. wrote the main manuscript text, R.L. collected data and L.Y. prepared figures and tables. All authors reviewed the manuscript.
Correspondence to Tao Wang or Kuiliang Li .
Ethics approval and consent to participate.
All procedures were conducted in accordance with the ethical standards of the responsible committee on human experimentation (Chongqing Normal University, China) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all participants included in the study. This research received ethical approval from the Chongqing Key Laboratory of Psychological Diagnosis and Educational Technology for Children with Special Needs (Ethics Number: CSTJ-RE-20230620004).
Competing interests.
The authors declare no competing interests.
Publisher’s note.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Below is the link to the electronic supplementary material.
Rights and permissions.
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .
Reprints and permissions
Cite this article.
Yang, L., Tan, X., Lang, R. et al. Reliability and validity of the Chinese version of the doomscrolling scale and the mediating role of doomscrolling in the bidirectional relationship between insomnia and depression. BMC Psychiatry 24 , 565 (2024). https://doi.org/10.1186/s12888-024-06006-5
Download citation
Received : 25 March 2024
Accepted : 08 August 2024
Published : 19 August 2024
DOI : https://doi.org/10.1186/s12888-024-06006-5
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative
ISSN: 1471-244X
IMAGES
COMMENTS
INTRODUCTION. The idea that problematic computer use meets criteria for an addiction, ... Furthermore, the current work gives a good overview of the current state of research in the field of internet addiction treatment. Despite the limitations stated above this work gives a brief overview of the current state of research on IAD from a ...
INTRODUCTION: The Internet has drastically affected human behavior, and it has positive and negative effects; however, its excessive usage exposes users to internet addiction. ... and recent research conducted in Iran indicated that the young population makes up the majority of internet users. Previous research specified that the Iranian users ...
INTRODUCTION. Over the last 15 years, the number of Internet users has increased by 1000%[], and at the same time, research on addictive Internet use has proliferated.Internet addiction has not yet been understood very well, and research on its etiology and natural history is still in its infancy[].Currently, it is estimated that between 0.8% of young individuals in Italy[] and 8.8% of Chinese ...
Abstract. Problematic computer use is a growing social issue which is being debated worldwide. Internet Addiction Disorder (IAD) ruins lives by causing neurological complications, psychological disturbances, and social problems. Surveys in the United States and Europe have indicated alarming prevalence rates between 1.5 and 8.2% [1]. There are ...
In recent years (2017-2020) there has been an explosion of research on Internet addiction in young adults. In total, the meta-analysis consists of 30 studies with k = 37 samples from Europe, Asia, America and Oceania. The total sample of participants is 21,378, with 51.22% being male, 48.78% female (three studies do not provide data on the ...
Introduction. Internet addiction (IA), also referred to as problematic, pathological, or compulsive Internet use, is a controversial concept in the research field.The frequent use of different terms to describe this new phenomenon, linked to the advent and growth of the Internet, leads to confusion over what it really consists of Tereshchenko and Kasparov (2019).
In a previous meta-analysis, Cheng and Li (2014) found that the pooled prevalence of Internet addiction was 6.0 % in general population. Another recent meta-analysis investigated prevalence of IGD in adolescents and found the pooled prevalence of IGD is 4.1 % ( Fam, 2018 ). Previous empirical research found that IGD was much more strongly ...
About this book. This book combines a scholarly introduction with state-of-the-art research in the characterization of Internet addiction. It is intended for a broad audience including scientists, students and practitioners. The first part of the book contains an introduction to Internet addiction and their pathogenesis.
Introduction. Given the ubiquity of the Internet, its evolving nature as a modern tool of society, and issues surrounding its excessive use and abuse by a minority of people, Internet addiction (IA) has become an increasingly important topic for dedicated research agendas from several scientific fields including psychology, psychiatry, and neuroscience.
AA Review of the Research on Internet Addiction. Chien Chou,1 4 Linda Condron,2 and John C. Belland3. Research indicates that maladaptive patterns of Internet use constitute be havioral addiction. This article explores the research on the social effects of Internet addiction. There are four major sections.
DOI: 10.2165/00023210-200822050-00001. Abstract. Internet addiction is characterized by excessive or poorly controlled preoccupations, urges or behaviours regarding computer use and internet access that lead to impairment or distress. The condition has attracted increasing attention in the popular media and among researchers, and this attention ...
Purpose of Review This review describes recent research findings and contemporary viewpoints regarding internet addiction in adolescents including its nomenclature, prevalence, potential determinants, comorbid disorders, and treatment. Recent Findings Prevalence studies show findings that are disparate by location and vary widely by definitions being used. Impulsivity, aggression, and ...
In this clincial study, patients with internet addiction and either panic disorder or generalized anxiety disorder received medication for their anxiety and 10 sessions of modified CBT. All 39 patients showed improved anxiety and internet addiction scores reduced on average. [ PMC free article] [ PubMed] 75.••.
Purpose. The purpose of this paper is to delineate the overall theoretical framework on the topic of internet addiction through the comprehensive narrative review to make readers aware of the conceptual growth and development in the respective field. The paper evolves theoretically from the historical foundation, phenomenology, clinical feature ...
Addiction. Internet addiction is defined as uncontrollable use of the internet that results in excessive time consumption or social dysfunction and may have a similar pathology to other addictions, which result in interpersonal, family, and social problems (Bailin et al., 2014 ). As many as 50% of adolescents feel addicted to social media, and ...
internet addiction in Korea found identity to be one factor associated with internet addiction (Koo & Kwon, 2014). While it could be hard now to treat internet addiction and its influence on identity, it is crucial to understand how identities are constructed within the growing complex nature of technology and communications.
oned findings, in our research, we focused on students of Czech universities. The purpose of the presented research is to detect the prevalence of Internet addiction among university students in the Czech Republic and its risk factors, including gender, age, the form of studies (full-. ime vs. part-time), the type of university studied and ...
Internet addiction disorder (IAD), also known as problematic internet use or pathological internet use, ... (2021) titled "Current Research and Viewpoints on Internet Addiction in Adolescents" found that internet addiction is a growing concern among adolescents, with many spending a significant amount of time online and exhibiting problematic ...
Introduction. Internet addiction can be defined as overuse of the Internet leading to impairment of an individual's psychological state (both mental and emotional), ... Addiction Research & Theory, 17 (3), 291-305. doi: 10.1080/16066350802435152 [Google Scholar]
If you or a loved one are struggling with an addiction, contact the Substance Abuse and Mental Health Services Administration (SAMHSA) National Helpline at 1-800-662-4357 for information on support and treatment facilities in your area. For more mental health resources, see our National Helpline Database.
Overview of Internet Addiction Internet addiction is defined as an unhealthy behavior that interferes with and causes stress in one's personal, school, and/or work life. Like other addictions, compulsive Internet usage completely dictates a person's life. Addicts struggle to control their behavior, causing a sense of despair, leading them to dive further in their addictive pattern.
This study is a preliminary investigation of the extent of internet addiction in a management institute in India, where sampled were 300 students (first, second and third years' students). This ...
1. Introduction. Among the different media types, the Internet is a recent achievement of mankind, a highly reachable global medium with an advanced modern communication technology capable of providing access to a wide range of information sources [1, 2].Although the Internet and its technologies have provided valuable opportunities in scientific, communicative, and economic aspects for human ...
Research has convincingly established a strong link between social media addiction and generalized problematic internet use, suggesting that doomscrolling represents an excessive and potentially dysfunctional facet of social media behavior . Consequently, quantifying the doomscrolling behavior enables researchers to investigate it alongside ...