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The Oxford Handbook of Quantitative Methods in Psychology, Vol. 1

Todd D. Little, Texas Tech University, Lubbock, Texas

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Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, this two-volume text provides the tool box to deliver the valid and generalizable answers to today's complex research questions. The Oxford Handbook of Quantitative Methods in Psychology aims to be a source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this text covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the book then segway into the realm of statistical inference and modeling with articles dedicated to classical approaches as well as modern latent variable approaches. Numerous articles associated with longitudinal data and more specialized techniques round out this broad selection of topics.

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Quantitative Research: A Successful Investigation in Natural and Social Sciences

• January 2021
• Journal of Economic Development Environment and People 9(4)
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Emotion Regulation and Academic Burnout Among Youth: a Quantitative Meta-analysis

• META-ANALYSIS
• Open access
• Published: 10 September 2024
• Volume 36 , article number  106 , ( 2024 )

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• Ioana Alexandra Iuga   ORCID: orcid.org/0000-0001-9152-2004 1 , 2 &
• Oana Alexandra David   ORCID: orcid.org/0000-0001-8706-1778 2 , 3  

Emotion regulation (ER) represents an important factor in youth’s academic wellbeing even in contexts that are not characterized by outstanding levels of academic stress. Effective ER not only enhances learning and, consequentially, improves youths’ academic achievement, but can also serve as a protective factor against academic burnout. The relationship between ER and academic burnout is complex and varies across studies. This meta-analysis examines the connection between ER strategies and student burnout, considering a series of influencing factors. Data analysis involved a random effects meta-analytic approach, assessing heterogeneity and employing multiple methods to address publication bias, along with meta-regression for continuous moderating variables (quality, female percentage and mean age) and subgroup analyses for categorical moderating variables (sample grade level). According to our findings, adaptive ER strategies are negatively associated with overall burnout scores, whereas ER difficulties are positively associated with burnout and its dimensions, comprising emotional exhaustion, cynicism, and lack of efficacy. These results suggest the nuanced role of ER in psychopathology and well-being. We also identified moderating factors such as mean age, grade level and gender composition of the sample in shaping these associations. This study highlights the need for the expansion of the body of literature concerning ER and academic burnout, that would allow for particularized analyses, along with context-specific ER research and consistent measurement approaches in understanding academic burnout. Despite methodological limitations, our findings contribute to a deeper understanding of ER's intricate relationship with student burnout, guiding future research in this field.

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Introduction

The transitional stages of late adolescence and early adulthood are characterized by significant physiological and psychological changes, including increased stress (Matud et al., 2020 ). Academic stress among students has long been studied in various samples, most of them focusing on university students (Bedewy & Gabriel, 2015 ; Córdova Olivera et al., 2023 ; Hystad et al., 2009 ) and, more recently, high school (Deb et al., 2015 ) and middle school students (Luo et al., 2020 ). Further, studies report an exacerbation of academic stress and mental health difficulties in response to the COVID-19 pandemic (Guessoum et al., 2020 ), with children facing additional challenges that affect their academic well-being, such as increasing workloads, influences from the family, and the issue of decreasing financial income (Ibda et al., 2023 ; Yang et al., 2021 ). For youth to maintain their well-being in stressful academic settings, emotion regulation (ER) has been identified as an important factor (Santos Alves Peixoto et al., 2022 ; Yildiz, 2017 ; Zahniser & Conley, 2018 ).

Emotion regulation, referring to”the process by which individuals influence which emotions they have, when they have them, and how they experience and express their emotions” (Gross, 1998b ), represents an important factor in youth’s academic well-being even in contexts that are not characterized by outstanding levels of stress. Emotion regulation strategies promote more efficient learning and, consequentially, improve youth’s academic achievement and motivation (Asareh et al., 2022 ; Davis & Levine, 2013 ), discourage academic procrastination (Mohammadi Bytamar et al., 2020 ), and decrease the chances of developing emotional problems such as burnout (Narimanj et al., 2021 ) and anxiety (Shahidi et al., 2017 ).

Approaches to Emotion Regulation

Numerous theories have been proposed to elucidate the process underlying the emergence and progression of emotional regulation (Gross, 1998a , 1998b ; Koole, 2009 ; Larsen, 2000 ; Parkinson & Totterdell, 1999 ). One prominent approach, developed by Gross ( 2015 ), refers to the process model of emotion regulation, which lays out the sequential actions people take to regulate their emotions during the emotion-generative process. These steps involve situation selection, situation modification, attentional deployment, cognitive change, and response modulation. The kind and timing of the emotion regulation strategies people use, according to this paradigm, influence the specific emotions people experience and express.

Recent theories of emotion regulation propose two separate, yet interconnected approaches: ER abilities and ER strategies. ER abilities are considered a higher-order process that guides the type of ER strategy an individual uses in the context of an emotion-generative circumstance. Further, ER strategies are considered factors that can also influence ER abilities, forming a bidirectional relationship (Tull & Aldao, 2015 ). Researchers use many definitions and classifications of emotion regulation, however, upon closer inspection, it becomes clear that there are notable similarities across these concepts. While there are many models of emotion regulation, it's important to keep from seeing them as competing or incompatible since each one represents a unique and important aspect of the multifaceted concept of emotion regulation.

Emotion Regulation and Emotional Problems

The connection between ER strategies and psychopathology is intricate and multifaceted. While some researchers propose that ER’s effectiveness is context-dependent (Kobylińska & Kusev, 2019 ; Troy et al., 2013 ), several ER strategies have long been attested as adaptive or maladaptive. This body of work suggests that certain emotion regulation strategies (such as avoidance and expressive suppression) demonstrate, based on findings from experimental studies, inefficacy in altering affect and appear to be linked to higher levels of psychological symptoms. These strategies have been categorized as ER difficulties. In contrast, alternative emotion regulation strategies (such as reappraisal and acceptance) have demonstrated effectiveness in modifying affect within controlled laboratory environments, exhibiting a negative association with clinical symptoms. As a result, these strategies have been characterized as potentially adaptive (Aldao & Nolen-Hoeksema, 2012a , 2012b ; Aldao et al., 2010 ; Gross, 2013 ; Webb et al., 2012 ).

A long line of research highlights the divergent impact of putatively maladaptive and adaptive ER strategies on psychopathology and overall well-being (Gross & Levenson, 1993 ; Gross, 1998a ). Increased negative affect, increased physiological reactivity, memory problems (Richards et al., 2003 ), a decline in functional behavior (Dixon-Gordon et al., 2011 ), and a decline in social support (Séguin & MacDonald, 2018 ) are just a few of the negative effects that have consistently been linked to emotional regulation difficulties, which include but are not limited to the use of avoidance, suppression, rumination, and self-blame strategies. Additionally, a wide range of mental problems, such as depression (Nolen-Hoeksema et al., 2008 ), anxiety disorders (Campbell-Sills et al., 2006a , 2006b ; Mennin et al., 2007 ), eating disorders (Prefit et al., 2019 ), and borderline personality disorder (Lynch et al., 2007 ; Neacsiu et al., 2010 ) are connected to self-reports of using these strategies.

Conversely, putatively adaptive strategies, including acceptance, problem-solving, and cognitive reappraisal, have consistently yielded beneficial outcomes in experimental studies. These outcomes encompass reductions in negative emotional responses, enhancements in interpersonal relationships, increased pain tolerance, reductions in physiological reactivity, and lower levels of psychopathological symptoms (Aldao et al., 2010 ; Goldin et al., 2008 ; Hayes et al., 1999 ; Richards & Gross, 2000 ).

Notably, despite the fact that therapeutic techniquest for enhancing the use of adaptive ER strategies are core elements of many therapeutic approaches, from traditional Cognitive Behavioral Therapy (CBT) to more recent third-wave interventions (Beck, 1976 ; Hofmann & Asmundson, 2008 ; Linehan, 1993 ; Roemer et al., 2008 ; Segal et al., 2002 ), the association between ER difficulties and psychopathology frequently show a stronger positive correlation compared to the inverse negative association with adaptive ER strategies, as highlighted by Aldao and Nolen-Hoeksema ( 2012a ).

Pines & Aronson ( 1988 ) characterize burnout that arises in the workplace context as a state wherein individuals encounter emotional challenges, such as experiencing fatigue and physical exhaustion due to heightened task demands. Recently, driven by the rationale that schools are the environments where students engage in significant work, the concept of burnout has been extended to educational contexts (Salmela-Aro, 2017 ; Salmela-Aro & Tynkkynen, 2012 ; Walburg, 2014 ). Academic burnout is defined as a syndrome comprising three dimensions: exhaustion stemming from school demands, a cynical and detached attitude toward one's academic environment, and feelings of inadequacy as a student (Salmela-Aro et al., 2004 ; Schaufeli et al., 2002 ).

School burnout has quickly garnered international attention, despite its relatively recent emergence, underscoring its relevance across multiple nations (Herrmann et al., 2019 ; May et al., 2015 ; Meylan et al., 2015 ; Yang & Chen, 2016 ). Similar to other emotional difficulties, it has been observed among students from various educational systems and academic policies, suggesting that this phenomenon transcends cultural and geographical boundaries (Walburg, 2014 ).

The link between ER and school burnout can be understood through Gross's ( 1998a ) process model of emotion regulation. This model suggests that an individual's emotional responses are influenced by their ER strategies, which are adaptive or maladaptive reactions to stressors like academic pressure. Given that academic stress greatly influences school burnout (Jiang et al., 2021 ; Nikdel et al., 2019 ), the ER strategies students use to manage this stress may impact their likelihood of experiencing burnout. In essence, whether a student employs efficient ER strategies or encounters ER difficulties could influence their susceptibility to school burnout.

The exploration of ER in relation to student burnout has garnered attention through various studies. However, the existing body of research is not yet robust enough, and its outcomes are not universally congruent. Suppression, defined as efforts to inhibit ongoing emotional expression (Balzarotti et al., 2010 ), has demonstrated a positive and significant correlation with both general and specific burnout dimensions (Chacón-Cuberos et al., 2019 ; Seibert et al., 2017 ), with the exception of the study conducted by Yu et al., ( 2022 ), where there is a negative, but not significant association between suppression and reduced accomplishment. Notably, research by Muchacka-Cymerman and Tomaszek ( 2018 ) indicates that ER strategies, encompassing both dispositional and situational approaches, exhibit a negative relationship with overall burnout. Situational ER, however, displays a negative impact on dimensions like inadequacy and declining interest, particularly concerning the school environment.

Cognitive ER strategies such as reappraisal, positive refocusing, and planning are, generally, negatively associated with burnout, while self-blame, other-blame, rumination, and catastrophizing present a positive association with burnout (Dominguez-Lara, 2018 ; Vinter et al., 2021 ). It's important to note that these relationships have not been consistently replicated across all investigations. Inconsistencies in the findings highlight the complexity of the interactions and the potential influence of various contextual factors. Consequently, there remains a critical need for further research to thoroughly examine these associations and identify the factors contributing to the variability in results.

Existing Research

Although we were unable to identify any reviews or meta-analyses that synthesize the literature concerning emotion regulation strategies and student burnout, recent meta-analyses have identified the role of emotion regulation across pathologies. A recent network meta-analysis identified the role of rumination and non-acceptance of emotions to be closely related to eating disorders (Leppanen et al., 2022 ). Further, compared to healthy controls, people presenting bipolar disorder symptoms reported significantly higher difficulties in emotion regulation (Miola et al., 2022 ). Weiss et al. ( 2022 ) identified a small to medium association between emotion regulation and substance use, and a subsequent meta-analysis conducted by Stellern et al. ( 2023 ) confirmed that individuals with substance use disorders have significantly higher emotion regulation difficulties compared to controls. The study of Dawel et al. ( 2021 ) represents the many research papers asking the question”Cause or symptom” in the context of emotion regulation. The longitudinal study brings forward the bidirectional relationship between ER and depression and anxiety, particularly in the case of suppression, suggesting that suppressing emotions is indicative of and can predict psychological distress.

Despite the increasing research attention to academic burnout in recent years, the current body of literature primarily concentrates on specific groups such as medical students (Almutairi et al., 2022 ; Frajerman et al., 2019 ), educators (Aloe et al., 2014 ; Park & Shin, 2020 ), and students at the secondary and tertiary education levels (Madigan & Curran, 2021 ) in the context of meta-analyses and reviews. A limited number of recent reviews have expanded their focus to include a more diverse range of participants, encompassing middle school, graduate, and university students (Kim et al., 2018 , 2021 ), with a particular emphasis on investigating social support and exploring the demand-control-support model in relation to student burnout.

The significance of managing burnout in educational settings is becoming more widely acknowledged, as seen by the rise in interventions designed to reduce the symptoms of burnout in students. Specific interventions for alleviating burnout symptoms among students continue to proliferate (Madigan et al., 2023 ), with a focus on stress reduction through mindfulness-based strategies (Lo et al., 2021 ; Modrego-Alarcón et al., 2021 ) and rational-emotive behavioral techniques (Ogbuanya et al., 2019 ) to enhance emotion-regulation skills (Charbonnier et al., 2022 ) and foster rational thinking (Bresó et al., 2011 ; Ezeudu et al., 2020 ). This underscores the significance of emotion regulation in addressing burnout.

Despite several randomized clinical trials addressing student burnout and an emerging body of research relating emotion regulation and academic burnout, there's a lack of a systematic examination of how emotion regulation strategies relate to various dimensions of student burnout. This highlights the necessity for a systematic review of existing evidence. The current meta-analysis addresses the association between emotion regulation strategies and student burnout.

A secondary objective is to test the moderating effect of school level and female percentage in the sample, as well as study quality, in order to identify possible sources of heterogeneity among effect sizes. By analyzing the moderating effect of school level and gender, we may determine if the strength of the association between student burnout and emotion regulation is contingent upon the educational setting and participant characteristics. This offers information on the findings' generalizability to all included student demographics, including those in elementary, middle, and secondary education and of different genders. Additionally, the reliability and validity of meta-analytic results rely on the evaluation of research quality, and the inclusion of study quality rating allows us to determine if the observed association between emotion regulation and student burnout differs based on the methodological rigor of the included studies.

Materials and Methods

Study protocol.

The present meta-analysis has been carried out following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement (Moher et al., 2009 ). The protocol for the meta-analysis was pre-registered in PROSPERO (PROSPERO, 2022 CRD42022325570).

Selection of Studies

A systematic search was performed using relevant databases (PubMed, Web of Science, PsychINFO, and Scopus). The search was carried out on 25 May of 2023 using 25 key terms related to the variables of interest, such as: (a) academic burnout, (b) school burnout, (c) student burnout (d) education burnout, (d) exhaustion, (e) cynicism, (f) inadequacy, (g) emotion regulation, (h) coping, (i) self-blame, (j) acceptance, and (h) problem solving.

Studies of any design published in peer-reviewed journals were eligible for inclusion, provided they used empirical data to assess the relationship between student burnout and emotion regulation strategies. Only studies that employed samples of children, adolescents, and youth were eligible for inclusion. For the purpose of the current paper, we define youth as people aged 18 to 25, based on how it is typically defined in the literature (Westhues & Cohen, 1997 ).

Studies were excluded from the meta-analysis if they: (a) were not a quantitative study, (b) did not explore the relationship between academic burnout and emotion regulation strategies, (c) did not have a sample that can be defined as consisting of children and youth (Scales et al., 2016 ), (e) did not utilize Pearson’s correlation or measures that could be converted to a Pearson’s correlation, (f) include medical school or associated disciplines samples.

Statistical Analysis

For the data analysis, we employed Comprehensive Meta-Analysis 4 software. Anticipating significant heterogeneity in the included studies, we opted for a random effects meta-analytic approach instead of a fixed-effects model, a choice that acknowledges and accounts for potential variations in effect sizes across studies, contributing to a more robust and generalizable synthesis of the results. Heterogeneity among the studies was assessed using the I 2 and Q statistics, adhering to the interpretation thresholds outlined in the Cochrane Handbook (Deeks et al., 2023 ).

Publication bias was assessed through a multi-faceted approach. We first examined the funnel plot for the primary outcome measures, a graphical representation revealing potential asymmetry that might indicate publication bias. Furthermore, we utilized Duval and Tweedie's trim and fill procedure (Duval & Tweedie, 2000 ), as implemented in CMA, to estimate the effect size after accounting for potential publication bias. Additionally, Egger's test of the intercept was conducted to quantify the bias detected by the funnel plot and to determine its statistical significance.

When dealing with continuous moderating variables, we employed meta-regression to evaluate the significance of their effects. For categorical moderating variables, we conducted subgroup analyses to test for significance. To ensure the validity of these analyses, it was essential that there was a minimum of three effect sizes within each subgroup under the same moderating variable, following the guidelines outlined by Junyan and Minqiang ( 2020 ). In accordance with the guidance provided in the Cochrane Handbook (Schmid et al., 2020 ), our application of meta-regression analyses was limited to cases where a minimum of 10 studies were available for each examined covariate. This approach ensures that there is a sufficient number of studies to support meaningful statistical analysis and reliable conclusions when exploring the influence of various covariates on the observed relationships.

Data Extraction and Quality Assessment

In addition to the identification information (i.e., authors, publication year), we extracted data required for the effect size calculation for the variables relevant to burnout and emotion regulation strategies. Where data was unavailable, the authors were contacted via email in order to provide the necessary information. Potential moderator variables were coded in order to examine the sources of variation in study findings. The potential moderators included: (a) participants’ gender, (b), grade level (c) study quality, and (d) mean age.

The full-text articles were independently assessed using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields tool (Kmet et al., 2004 ) by a pair of coders (II and SM), to ensure the reliability of the data, resulting in a substantial level of agreement (Cohen’s k  = 0.89). The disagreements and discrepancies between the two coders were resolved through discussion and consensus. If consensus could not be reached, a third researcher (OD) was consulted to resolve the disagreement.

The checklist items focused on evaluating the alignment of the study's design with its stated objectives, the methodology employed, the level of precision in presenting the results, and the accuracy of the drawn conclusions. The assessment criteria were composed of 14 items, which were evaluated using a 3-point Likert scale (with responses of 2 for "yes," 1 for "partly," and 0 for "no"). A cumulative score was computed for each study based on these items. For studies where certain checklist items were not relevant due to their design, those items were marked as "n/a" and were excluded from the cumulative score calculation.

Study Selection

The combined search terms yielded a total of 15,179 results. The duplicate studies were removed using Zotero, and a total of 8,022 studies remained. The initial screening focused on the titles and abstracts of all remaining studies, removing all documents that target irrelevant predictors or outcomes, as well as qualitative studies and reviews. Two assessors (II and SA) independently screened the papers against the inclusion and exclusion criteria. A number of 7,934 records were removed, while the remaining 88 were sought for retrieval. Out of the 88 articles, we were unable to find one, while another has been retracted by the journal. Finally, 86 articles were assessed for eligibility. A total of 20 articles met the inclusion criteria (see Fig.  1 ). Although a specific cutoff criterion for reliability coefficients was not imposed during study selection, the majority of the included studies had alpha Cronbach values for the instruments assessing emotion regulation and school burnout greater than 0.70.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart of the study selection process

Data Overview

Among the included studies, four focused on middle school students, two encompassed high school student samples, and the remaining 14 articles involved samples of university students. The majority of the included studies had cross-sectional designs (17), while the rest consisted of 2 longitudinal studies and one non-randomized controlled pilot study. The percentage of females within the samples ranged from 46% to 88.3%, averaging 65%, while the mean age of participants ranged from 10.39 to 25. The investigated emotional regulation strategies within the included studies exhibit variation, encompassing other-blame, self-blame, acceptance, rumination, catastrophizing, putting into perspective, reappraisal, planning, behavioral and mental disengagement, expressive suppression, and others (see Table  1 for a detailed study presentation).

Study Quality

Every study surpasses a quality threshold of 0.60, and 75% of the studies achieve a score above the more conservative threshold indicated by Kmet et al. ( 2004 ). This indicates a minimal risk of bias in these studies. Moreover, 80% of the studies adequately describe their objectives, while the appropriateness of the study design is recognized in 50% of the cases, mostly utilizing cross-sectional designs. While 95% of the studies provide sufficient descriptions of their samples, only 10% employ appropriate sampling methods, with the majority relying on convenience sampling. Notably, there is just one interventional study that lacks random allocation and blinding of investigators or subjects.

In terms of measurement, 85% of the studies employ validated and reliable tools. Adequacy in sample size and well-justified and appropriate analytic methods are observed across all included studies. While approximately 50% of the studies present estimates of variance, a mere 30% of them acknowledge the control of confounding variables. Lastly, 95% of the studies provide results in comprehensive detail, with 60% effectively grounding their discussions in the obtained results. The quality assessment criteria and results can be consulted in Supplementary Material 4 .

Pooled Effects

A sensitivity analysis using standardized residuals was conducted. Provided that the residuals are normally distributed, 95% of them would fall within the range of -2 to 2. Residuals outside this range were considered unusual. We applied this cutoff in our meta-analysis to identify any outliers. The results of the analysis revealed that several relationships had standardized residuals falling outside the specified range. Re-analysis excluding these outliers demonstrated that our initial results were robust and did not significantly change in magnitude or significance. As a result, we have moved on with the analysis for the entire sample.

The calculated overall effects can be consulted in Table  2 . The correlation between ER difficulties and student burnout is a significant one, with significant positive associations between ER difficulties and overall burnout (k = 13), r  = 0.25 (95% CI = 0.182; 0.311), p  < 0.001, as well as individual burnout dimensions: cynicism (k = 9), r  = 0.28 (95% CI = 0.195; 0.353) p  < 0.001, lack of efficacy (k = 8), r  = 0.17 (95% CI = 0.023; 0.303), p  < 0.05 and emotional exhaustion (k = 11), r  = 0.27 (95% CI = 0.207; 0.335) p  < 0.001. Regarding the relationship between adaptive ER strategies and student burnout, a statistically significant result is observed solely between overall student burnout and adaptive ER (k = 17), r  = -14 (95% CI = -0.239; 0.046) p  < 0.005. The forest plots can be consulted in Supplementary Material 1 .

Heterogeneity and Publication Bias

Table 3 shows that all Q tests were significant, indicating that there is significant variation among the effect sizes of the individual studies included in the meta-analysis. Further, all I 2 indices are over 75%, ranging from 83.67% to 99.32%, which also indicates high heterogeneity (Borenstein et al., 2017 ). This consistently high level of heterogeneity indicates substantial variation in effect sizes, pointing to influential factors that significantly shape the outcomes of the included studies. Consequentially, subgroup and meta-regression analyses are to be carried out in order to unravel the underlying factors driving this pronounced heterogeneity. The results of the publication bias analysis are presented individually below and, additionally, you can consult the funnel plots included in Supplementary Material 2 .

Adaptive ER and School Burnout

Upon visual examination of the funnel plot, asymmetry to the right of the mean was observed. To validate this observation, a trim-and-fill analysis using Duval and Tweedie’s method was conducted, revealing the absence of three studies on the left side of the mean. The adjusted effect size ( r  = -0.17, 95% CI [0.27; 0.68]) resulting from this analysis was found to be higher than the initially observed effect size. Nevertheless, the application of Egger’s test did not yield a significant indication of publication bias ( B  = -5.34, 95% CI [-11.85; 1.16], p  = 0.10).

Adaptive ER and Cynicism

Following a visual examination of the funnel plot, a symmetrical arrangement of effect sizes around the mean was apparent. This finding was contradicted by the application of Duval and Tweedie's trim-and-fill method, which revealed two missing studies to the right of the mean. The adjusted effect size ( r  = 0.04, 95% CI [-0.21; 0.13]) is smaller than the initially observed effect size. The application of Egger’s test did not yield a significant indication of publication bias ( B  = -2.187, 95% CI [-8.57; 4.19], p  = 0.43).

ER difficulties and Lack of Efficacy

The visual examination of the funnel plot revealed asymmetry to the right of the mean. This finding was validated by the application of Duval and Tweedie's trim-and-fill method, which revealed two missing studies to the left of the mean and a lower adjusted effect size ( r  = 0.08, 95% CI [-0.07; 0.23]), the effect becoming statistically non-significant. The application of Egger’s test did not yield a significant indication of publication bias ( B  = 7.76, 95% CI [-16.53; 32.05], p  = 0.46).

Adaptive ER and Emotional Exhaustion

The visual examination of the funnel plot revealed asymmetry to the left of the mean. The trim-and-fill method also revealed one missing study to the right of the mean and a lower adjusted effect size ( r  = 0.00, 95% CI [-0.13; 0.12]). The application of Egger’s test did not yield a significant indication of publication bias ( B  = 7.02, 95% CI [-23.05; 9.02], p  = 0.46).

Adaptive ER and Lack of Efficacy; ER difficulties and School Burnout, Cynicism, and Exhaustion

Upon visually assessing the funnel plot, a balanced distribution of effect sizes centered around the mean was observed. This observation is corroborated by the application of Duval and Tweedie's trim-and-fill method, which also revealed no indication of missing studies. The adjusted effect size remained consistent, and the intercept signifying publication bias was found to be statistically insignificant.

Moderator Analysis

We performed moderator analyses for the categorical variables, in the case of significant relationships that were uncovered in the initial analysis. These analyses were carried out specifically for cases where there were more than three effect sizes available within each subgroup that fell under the same moderating variable.

Students’ grade level was used as a categorical moderator. Pre-university students included students enrolled in primary and secondary education, while the university student category included tertiary education students. The results, presented in Table  4 , show that the moderating effect of grade level is not significant for the relationship between adaptive ER and overall school burnout Q (1) = 0.20, p  = 0.66. At a specific level, the moderating effect is significant for the relationship between ER difficulties and overall burnout Q (1) = 9.81, p  = 0.002, cynicism Q (1) = 16.27, p  < 0.001, lack of efficacy Q (1) = 15.47 ( p  < 0.001), and emotional exhaustion Q (1) = 13.85, p  < 0.001. A particularity of the moderator analysis in the relationship between ER difficulties and lack of efficacy is that, once the effect of the moderator is accounted for, the relationship is not statistically significant anymore for the university level, r  = -0.01 (95% CI = -0.132; 0.138), but significant for the pre-university level, r  = 0.33 (95% CI = 0.217; 0.439).

Meta-regressions

Meta-regression analyses were employed to examine how the effect size or relationship between variables changes based on continuous moderator variables. We included as moderators the female percentage (the proportion of female participants in each study’s sample) and the study quality assessed based on the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields tool (Kmet et al., 2004 ).

Results, presented in Table  5 , show that study quality does not significantly influence the relationship between ER and school burnout. The proportion of female participants in the study sample significantly influences the relationship between ER difficulties and overall burnout ( β , -0.0055, SE = 0.001, p  < 0.001), as well as the emotional exhaustion dimension ( β , -0.0049, SE = 0.002, p  < 0.01). Mean age significantly influences the relationship between ER difficulties and overall burnout ( β , -0.0184, SE = 0.006, p  < 0.01). Meta-regression plots can be consulted in detail in Supplementary Material 3 .

A post hoc power analysis was conducted using the metapower package in R. For the pooled effects analysis of the relationship between ER difficulties and overall school burnout, as well as with cynicism and emotional exhaustion, the statistical power was adequate, surpassing the recommended 0.80 cutoff. The analysis of the association between ER difficulties and lack of efficacy, along with the relationship between adaptive ER and school burnout, cynicism, lack of efficacy, and emotional exhaustion were greatly underpowered. In the case of the moderator analysis, the post-hoc power analysis indicates insufficient power. Please consult the coefficients in Table  6 .

The central goal of this meta-analysis was to examine the relationship between emotion-regulation strategies and student burnout dimensions. Additionally, we focused on the possible effects of sample distribution, in particular on participants’ age, education levels they are enrolled in, and the percentage of female participants included in the sample. The study also aimed to determine how research quality influences the overall findings. Taking into consideration the possible moderating effects of sample characteristics and research quality, the study aimed to offer a thorough assessment of the literature concerning the association between emotion regulation strategies and student burnout dimensions. A correlation approach was used as the current literature predominantly consists of cross-sectional studies, with insufficient longitudinal studies or other designs that would allow for causal interpretation of the results.

The study’s main findings indicate that adaptive ER strategies are associated with overall burnout, whereas ER difficulties are associated with both overall burnout and all its dimensions encompassing emotional exhaustion, cynicism, and lack of efficacy.

Prior meta-analyses have similarly observed that adaptive ER strategies tend to exhibit modest negative associations with psychopathology, while ER difficulties generally presented more robust positive associations with psychopathology (Aldao et al., 2010 ; Miu et al., 2022 ). These findings could suggest that the observed variation in the effect of ER strategies on psychopathology, as previously indicated in the literature, can also be considered in the context of academic burnout.

However, it would be an oversimplification to conclude that adaptive ER strategies are less effective in preventing psychopathology than ER difficulties are in creating vulnerability to it. Alternatively, as previously underlined, researchers should consider the frequency, flexibility, and variability in the way ER strategies are applied and how they relate to well-being and psychopathology. Further, it’s important to also address the possible directionality of the relationship. While the few studies that assume a prediction model for academic burnout and ER treat ER as a predictor for burnout and its dimensions (see Seibert et al., 2017 ; Vizoso et al., 2019 ), we were unable to identify studies that assume the role of burnout in the development of ER difficulties. Additionally, the studies identified that relate to academic burnout have a cross-sectional design that makes it even more difficult to pinpoint the ecological directionality of the relationship.

While the focus on the causal role of ER strategies in psychopathology and psychological difficulties is of great importance for psychological interventions, addressing a factor that merely reflects an effect or consequence of psychopathology will not lead to an effective solution. According to Gross ( 2015 ), emotion regulation strategies are employed when there is a discrepancy between a person's current emotional state and their desired emotional state. Consequently, individuals could be likely to also utilize emotion regulation strategies in response to academic burnout. Additionally, studies that have utilized a longitudinal approach have demonstrated that, in the case of spontaneous ER, people with a history of psychopathology attempt to regulate their emotions more when presented with negative stimuli (Campbell-Sills et al., 2006a , 2006b ; Ehring et al., 2010 ; Gruber et al., 2012 ). The results of Dawel et al. ( 2021 ) further solidify a bidirectional model that could and should be also applied to academic burnout research.

Following the moderator analysis, the results indicate that the moderating effect of grade level did not have a substantial impact on the relationship between adaptive ER and school burnout. In the context of this discussion, it is important to note that regarding the relationship between adaptive ER and overall burnout, there is an imbalance in the distribution of studies between the university and pre-university levels, which could potentially present a source of bias or error.

When it comes to the relationship between ER difficulties and burnout, the inclusion of the moderator exhibited notable significance, overall and at the dimensions’ level. Particularly noteworthy is the finding that, within the relationship involving ER difficulties and lack of efficacy, the inclusion of the moderator rendered the association statistically insignificant for university-level students, while maintaining significance for pre-university-level students. The outcomes consistently demonstrate larger effect sizes for the relationship between ER difficulties and burnout at the pre-university level in comparison to the university level. Additionally, the mean age significantly influences the relationship between ER difficulties and overall burnout.

These findings may imply the presence of additional variables that exert a varying influence at the two educational levels and as a function of age. There are several contextual factors that could be framing the current findings, such as parental education anxiety (Wu et al., 2022 ), parenting behaviors, classroom atmosphere (Lin & Yang, 2021 ), and self-efficacy (Naderi et al., 2018 ). As the level of independence drastically increases from pre-university to university, the influence of negative parental behaviors and attitudes can become limited. Furthermore, the university-level learning environment often provides a satisfying and challenging educational experience, with greater opportunities for students to engage in decision-making and take an active role in their learning (Belaineh, 2017 ), which can serve as a protective factor against student’s academic burnout (Grech, 2021 ). At an individual level, many years of experience in navigating the educational environment can increase youths’ self-efficacy in the educational context and offer proper learning tools and techniques, which can further influence various aspects of self-regulated learning, such as monitoring of working time and task persistence (Bouffard-Bouchard et al., 1991 ; Cattelino et al., 2019 ).

The findings of the meta-regression analysis suggest that the association between ER and school burnout is not significantly impacted by study quality. It’s important to interpret these findings in the context of rather homogenous study quality ratings that can limit the detection of significant impacts.

The current results underline that the correlation between ER difficulties and both overall burnout and the emotional exhaustion dimension is significantly influenced by the percentage of female participants in the study sample. Previous research has shown that girls experience higher levels of stress, as well as higher expectations concerning their school performance, which can originate not only intrinsically, but also from external sources such as parents, peers, and educators (Östberg et al., 2015 ). These heightened expectations and stress levels may contribute to the gender differences in how emotion regulation difficulties are associated with school burnout.

The results of this meta-analysis suggest that most of the included studies present an increased level of methodological quality, reaching or surpassing the quality thresholds previously established. These encouraging results indicate a minimal risk of bias in the selected research. Moreover, it’s notable that a sizable proportion of the included studies clearly articulate their research objectives and employ well-established measurement tools, that would accurately capture the constructs of interest. There are still several areas of improvement, especially with regard to variable conceptualization and sampling methods, highlighting the importance of maintaining methodological rigor in this area of research.

Significant Q tests and I 2 identified in the case of several analyses indicate a strong heterogeneity among the effect sizes of individual studies in the meta-analysis's findings. This variability suggests that there is a significant level of diversity and variation among the effects observed in the studies, and it is improbable that this diversity is solely attributable to random chance. Even with as few as 10 studies, with 30 participants in the primary studies, the Q test has been demonstrated to have good power for identifying heterogeneity (Maeda & Harwell, 2016 ). Recent research (Mickenautsch et al., 2024 ), suggests that the I 2 statistic is not influenced by the number of studies and sample sizes included in a meta-analysis. While the relationships between Adaptive ER—cynicism, ER difficulties—cynicism, Adaptive ER—lack of efficacy, and ER difficulties—lack of efficacy are based on a limited number of studies (8–9 studies), it's noteworthy that the primary study sample sizes for these relationships are relatively large, averaging above 300. This suggests that despite the small number of studies, the robustness of the findings may be supported by the substantial sample sizes, which can contribute to the statistical power of the analysis.

However, it's essential to consider potential limitations such as range restriction or measurement error, which could impact the validity of the findings. Despite these considerations, the combination of substantial primary study sample sizes and the robustness of the Q test provides a basis for confidence in the results.

The results obtained when publication bias was examined using funnel plots, trim-and-fill analyses, and Egger's tests were varying across different outcomes. In the case of adaptive emotion regulation (ER) and school burnout, no evidence of publication bias was found, suggesting that the observed effects are likely robust. The trim-and-fill analysis, however, indicated the existence of missing studies for adaptive ER and cynicism, potentially influencing the initial effect size estimate. For ER difficulties and lack of efficacy, the adjustment for missing studies in the trim-and-fill analysis led to a non-significant effect. Additionally, adaptive ER and emotional exhaustion displayed a similar pattern with the trim-and-fill method leading to a lower, non-significant effect size. This indicates the need for additional studies to be included in future meta-analyses. According to the Cochrane Handbook (Higgins et al., 2011 ), the results of Egger’s test and funnel plot asymmetry should be interpreted with caution, when conducted on fewer than 10 studies.

The results of the post-hoc power analysis reveal that the relationship between ER difficulties and cynicism, as well as emotional exhaustion, meets the threshold of 0.80 for statistical power, as suggested by Harrer et al. ( 2022 ). This implies that our study had a high likelihood of detecting significant associations between ER difficulties and these specific outcomes, providing robust evidence for the observed relationships. However, for the relationship between ER difficulties and overall burnout, the power coefficient falls just below the indicated threshold. While our study still demonstrated considerable power to detect effects, the slightly lower coefficient suggests a marginally reduced probability of detecting significant associations between ER difficulties and overall burnout.

The power coefficients for the remaining post-hoc analyses are fairly small, which suggests that there is not enough statistical power to find meaningful relationships. This shows that there might not have been enough power in our investigation to find significant correlations between the variables we sought to investigate. Even if these analyses' power coefficients are lower than ideal, it's important to consider the study's limitations and implications when interpreting the results.

Limitations and Future Directions

One important limitation of our meta-analysis is represented by the small number of studies included in the analysis. Smaller meta-analyses could result in less reliable findings, with estimates that could be significantly influenced by outliers and inclusion of studies with extreme results. The small number of studies also interferes with the interpretation of both Q and I 2 heterogeneity indices (von Hippel, 2015 ). In small sample sizes, it may be challenging to detect true heterogeneity, and the I 2 value may be imprecise or underestimate the actual heterogeneity.

The studies included in the current meta-analysis focused on investigating how individuals generally respond to stressors. However, it's crucial to remember that people commonly use various ER strategies based on particular contexts, or they could even combine ER strategies within a single context. This adaptability in ER strategies reflects the dynamic and context-dependent nature of emotional regulation, where people draw upon various tools and approaches to effectively manage their emotions in different circumstances.

Given the heterogeneity of studies that investigate ER as a context-dependent phenomenon in the context of academic burnout, as well as the diverse nature of these existing studies, it becomes imperative for future research to consider a number of key aspects. First and foremost, future studies should aim to expand the body of literature on this topic by conducting more research specifically focusing on the context-dependent and flexible nature of ER in the context of academic burnout and other psychopathologies. Taking into account the diversity of educational environments, curricula, and student demographics, these research initiatives should also include a wide range of academic contexts.

Furthermore, it is advisable for researchers to implement a uniform methodology for assessing and documenting ER strategies. This consistency in measurement will simplify the process of comparing results among different studies, bolster the reliability of the data, and pave the way for more extensive and comprehensive meta-analyses.

Insufficient research that delves into the connection between burnout and particular emotional regulation (ER) strategies, such as reappraisal or suppression, has made it unfeasible to conduct a meaningful analysis within the scope of the current meta-analysis, that could further bring specificity as to which ER strategies could influence or be affected in the context of academic burnout. Consequentially, the expansion of the inclusion criteria for future meta-analyses should be considered, along with the replication of the current meta-analysis in the context of future publications on this topic.

Future interventions aimed at addressing academic burnout should adopt a tailored approach that takes into consideration age or school-level influences, as well as gender differences. Implementing prevention programs in pre-university educational settings can play a pivotal role in equipping children and adolescents with vital emotion regulation skills and stress management strategies. Additionally, it is essential to provide additional support to girls, recognizing their unique stressors and increased academic expectations.

Implications

Our meta-analysis has several implications, both theoretical and practical. Firstly, the meta-analysis extends the understanding of the relationship between emotion regulation (ER) strategies and student burnout dimensions. Although the correlational and cross-sectional nature of the included studies does not allow for drawing causal implications, the results represent a great stepping stone for future research. Secondly, the results highlight the intricacy of ER strategies and their applicability in educational contexts. Along with the identified differences between preuniversity and university students, this emphasizes the importance of developmental and contextual factors in ER research and the necessity of having an elaborate understanding of the ways in which these strategies are used in various situations and according to individual particularities. The significant impact of the percentage of female participants on the relationship between ER strategies and academic burnout points to the need for gender-sensitive approaches in ER research. On a practical level, our results suggest the need for targeted interventions aimed at the specific needs of different educational levels and age groups, as well as gender-specific strategies to address ER difficulties.

In conclusion, the findings of the current meta-analysis reveal that adaptive ER strategies are associated with overall burnout, while ER difficulties are linked to both overall burnout and its constituent dimensions, including emotional exhaustion, cynicism, and lack of efficacy. These results align with prior research in the domain of psychopathology, suggesting that adaptive ER strategies may be more efficient in preventing psychopathology than ER difficulties are in creating vulnerability to it, or that academic burnout negatively influences the use of adaptive ER strategies in the youth population. As an alternative explanation, it might also be that the association between ER strategies, well-being, and burnout can vary based on the context, frequency, flexibility, and variability of their application. Furthermore, our study identified the moderating role of grade level and the sample’s gender composition in shaping these associations. The academic environment, parental influences, and self-efficacy may contribute to the observed differences between pre-university and university levels and age differences.

Despite some methodological limitations, the current meta-analysis underscores the need for context-dependent ER research and consistent measurement approaches in future investigations of academic burnout and psychopathology. The heterogeneity among studies may suggest variability in the relationship between emotion regulation and student burnout across different contexts. This variability could be explained through methodological differences, assessment methods, and other contextual factors that were not uniformly accounted for in the included studies. The included studies do not provide insights into changes over time as most studies were cross-sectional. Future research should aim to better understand the underlying reasons for the observed differences and to reach more conclusive insights through longitudinal research designs.

Overall, this meta-analysis contributes to a deeper understanding of the intricate relationship between ER strategies and student burnout and serves as a good reference point for future research within the academic burnout field.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Alarcon, G. M., Edwards, J. M., & Menke, L. E. (2011). Student Burnout and Engagement: A Test of the Conservation of Resources Theory. The Journal of Psychology, 145 (3), 211–227. https://doi.org/10.1080/00223980.2011.555432

Article   Google Scholar  

Aldao, A., & Nolen-Hoeksema, S. (2012a). The influence of context on the implementation of adaptive emotion regulation strategies. Behaviour Research and Therapy, 50 (7), 493–501. https://doi.org/10.1016/j.brat.2012.04.004

Aldao, A., & Nolen-Hoeksema, S. (2012b). When are adaptive strategies most predictive of psychopathology? Journal of Abnormal Psychology, 121 (1), 276–281. https://doi.org/10.1037/a0023598

Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30 (2), 217–237. https://doi.org/10.1016/j.cpr.2009.11.004

Almutairi, H., Alsubaiei, A., Abduljawad, S., Alshatti, A., Fekih-Romdhane, F., Husni, M., & Jahrami, H. (2022). Prevalence of burnout in medical students: A systematic review and meta-analysis. International Journal of Social Psychiatry, 68 (6), 1157–1170. https://doi.org/10.1177/00207640221106691

Aloe, A. M., Amo, L. C., & Shanahan, M. E. (2014). Classroom Management Self-Efficacy and Burnout: A Multivariate Meta-analysis. Educational Psychology Review, 26 (1), 101–126. https://doi.org/10.1007/s10648-013-9244-0

Arias-Gundín, O. (Olga), & Vizoso-Gómez, C. (Carmen). (2018). Relación entre estrategias activas de afrontamiento, burnout y engagement en futuros educadores . https://doi.org/10.15581/004.35.409-427

Asareh, N., Pirani, Z., & Zanganeh, F. (2022). Evaluating the effectiveness of self-help cognitive and emotion regulation training On the psychological capital and academic motivation of female students with anxiety. Journal of School Psychology, 11 (2), 96–110. https://doi.org/10.22098/jsp.2022.1702

Balzarotti, S., John, O. P., & Gross, J. J. (2010). An Italian Adaptation of the Emotion Regulation Questionnaire. European Journal of Psychological Assessment, 26 (1), 61–67. https://doi.org/10.1027/1015-5759/a000009

Beck, A. T. (1976). Cognitive therapy and the emotional disorders. International Universities Press.

Bedewy, D., & Gabriel, A. (2015). Examining perceptions of academic stress and its sources among university students: The Perception of Academic Stress Scale. Health Psychology Open, 2 (2), 205510291559671. https://doi.org/10.1177/2055102915596714

Belaineh, M. S. (2017). Students’ Conception of Learning Environment and Their Approach to Learning and Its Implication on Quality Education. Educational Research and Reviews, 12 (14), 695–703.

Boada-Grau, J., Merino-Tejedor, E., Sánchez-García, J.-C., Prizmic-Kuzmica, A.-J., & Vigil-Colet, A. (2015). Adaptation and psychometric properties of the SBI-U scale for Academic Burnout in university students. Anales de Psicología / Annals of Psychology, 31 (1). https://doi.org/10.6018/analesps.31.1.168581

Borenstein, M., Higgins, J., Hedges, L., & Rothstein, H. (2017). Basics of meta-analysis: I(2) is not an absolute measure of heterogeneity. Research synthesis methods, 8. https://doi.org/10.1002/jrsm.1230

Bouffard-Bouchard, T., Parent, S., & Larivee, S. (1991). Influence of Self-Efficacy on Self-Regulation and Performance among Junior and Senior High-School Age Students. International Journal of Behavioral Development, 14 (2), 153–164. https://doi.org/10.1177/016502549101400203

Bresó, E., Schaufeli, W. B., & Salanova, M. (2011). Can a self-efficacy-based intervention decrease burnout, increase engagement, and enhance performance? A Quasi-Experimental Study. Higher Education, 61 (4), 339–355. https://doi.org/10.1007/s10734-010-9334-6

Burić, I., Sorić, I., & Penezić, Z. (2016). Emotion regulation in academic domain: Development and validation of the academic emotion regulation questionnaire (AERQ). Personality and Individual Differences, 96 , 138–147. https://doi.org/10.1016/j.paid.2016.02.074

Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G. (2006a). Effects of suppression and acceptance on emotional responses of individuals with anxiety and mood disorders. Behaviour Research and Therapy, 44 (9), 1251–1263. https://doi.org/10.1016/j.brat.2005.10.001

Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G. (2006b). Acceptability and suppression of negative emotion in anxiety and mood disorders. Emotion, 6 (4), 587–595. https://doi.org/10.1037/1528-3542.6.4.587

Carver, C. S. (1997). You want to measure coping but your protocol’ too long: Consider the brief cope. International Journal of Behavioral Medicine, 4 (1), 92–100. https://doi.org/10.1207/s15327558ijbm0401_6

Carver, C. S., Scheier, M. F., & Weintraub, J. K. (1989). Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology, 56 (2), 267–283. https://doi.org/10.1037/0022-3514.56.2.267

Cattelino, E., Morelli, M., Baiocco, R., & Chirumbolo, A. (2019). From external regulation to school achievement: The mediation of self-efficacy at school. Journal of Applied Developmental Psychology, 60 , 127–133. https://doi.org/10.1016/j.appdev.2018.09.007

Chacón-Cuberos, R., Martínez-Martínez, A., García-Garnica, M., Pistón-Rodríguez, M. D., & Expósito-López, J. (2019). The Relationship between Emotional Regulation and School Burnout: Structural Equation Model According to Dedication to Tutoring. International Journal of Environmental Research and Public Health, 16 (23), 4703. https://doi.org/10.3390/ijerph16234703

Charbonnier, E., Trémolière, B., Baussard, L., Goncalves, A., Lespiau, F., Philippe, A. G., & Le Vigouroux, S. (2022). Effects of an online self-help intervention on university students’ mental health during COVID-19: A non-randomized controlled pilot study. Computers in Human Behavior Reports, 5 , 100175. https://doi.org/10.1016/j.chbr.2022.100175

Chen, S., Zheng, Q., Pan, J., & Zheng, S. (2000). Preliminary development of the Coping Style Scale for Middle School Students. Chinese Journal of Clinical Psychology, 8 , 211–214, 237.

Córdova Olivera, P., Gasser Gordillo, P., Naranjo Mejía, H., La Fuente Taborga, I., Grajeda Chacón, A., & Sanjinés Unzueta, A. (2023). Academic stress as a predictor of mental health in university students. Cogent Education, 10 (2), 2232686. https://doi.org/10.1080/2331186X.2023.2232686

Davis, E. L., & Levine, L. J. (2013). Emotion Regulation Strategies That Promote Learning: Reappraisal Enhances Children’s Memory for Educational Information: Reappraisal and Memory in Children. Child Development, 84 (1), 361–374. https://doi.org/10.1111/j.1467-8624.2012.01836.x

Dawel, A., Shou, Y., Gulliver, A., Cherbuin, N., Banfield, M., Murray, K., Calear, A. L., Morse, A. R., Farrer, L. M., & Smithson, M. (2021). Cause or symptom? A longitudinal test of bidirectional relationships between emotion regulation strategies and mental health symptoms. Emotion, 21 (7), 1511–1521. https://doi.org/10.1037/emo0001018

Deb, S., Strodl, E., & Sun, H. (2015). Academic stress, parental pressure, anxiety and mental health among Indian high school students. International Journal of Psychology and Behavioral Science, 5 (1), 1.

Google Scholar  

Deeks, J. J., Bossuyt, P. M., Leeflang, M. M., & Takwoingi, Y. (2023). Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy . John Wiley & Sons.

Book   Google Scholar  

Dixon-Gordon, K. L., Chapman, A. L., Lovasz, N., & Walters, K. (2011). Too upset to think: The interplay of borderline personality features, negative emotions, and social problem solving in the laboratory. Personality Disorders: Theory, Research, and Treatment, 2 (4), 243–260. https://doi.org/10.1037/a0021799

Dominguez-Lara, S. A. (2018). Agotamiento emocional académico en estudiantes universitarios: ¿cuánto influyen las estrategias cognitivas de regulación emocional? Educación Médica, 19 (2), 96–103. https://doi.org/10.1016/j.edumed.2016.11.010

Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56 (2), 455–463. https://doi.org/10.1111/j.0006-341x.2000.00455.x

Ehring, T., Tuschen-Caffier, B., Schnülle, J., Fischer, S., & Gross, J. J. (2010). Emotion regulation and vulnerability to depression: Spontaneous versus instructed use of emotion suppression and reappraisal. Emotion, 10 (4), 563–572. https://doi.org/10.1037/a0019010

Ezeudu, F. O., Attah, F. O., Onah, A. E., Nwangwu, T. L., & Nnadi, E. M. (2020). Intervention for burnout among postgraduate chemistry education students. Journal of International Medical Research, 48 (1), 0300060519866279. https://doi.org/10.1177/0300060519866279

Fong, M., & Loi, N. M. (2016). The Mediating Role of Self-compassion in Student Psychological Health. Australian Psychologist, 51 (6), 431–441. https://doi.org/10.1111/ap.12185

Frajerman, A., Morvan, Y., Krebs, M.-O., Gorwood, P., & Chaumette, B. (2019). Burnout in medical students before residency: A systematic review and meta-analysis. European Psychiatry: The Journal of the Association of European Psychiatrists, 55 , 36–42. https://doi.org/10.1016/j.eurpsy.2018.08.006

Garnefski, N., Kraaij, V., & Spinhoven, P. (2001). Negative life events, cognitive emotion regulation and emotional problems. Personality and Individual Differences, 30 (8), 1311–1327. https://doi.org/10.1016/S0191-8869(00)00113-6

Goldin, P. R., McRae, K., Ramel, W., & Gross, J. J. (2008). The neural bases of emotion regulation: Reappraisal and suppression of negative emotion. Biological Psychiatry, 63 (6), 577–586. https://doi.org/10.1016/j.biopsych.2007.05.031

Grech, M. (2021). The Effect of the Educational Environment on the rate of Burnout among Postgraduate Medical Trainees – A Narrative Literature Review. Journal of Medical Education and Curricular Development, 8 , 23821205211018700. https://doi.org/10.1177/23821205211018700

Gross, J. J. (1998a). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2 (3), 271–299. https://doi.org/10.1037/1089-2680.2.3.271

Gross, J. J. (1998b). Antecedent- and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology, 74 (1), 224–237. https://doi.org/10.1037/0022-3514.74.1.224

Gross, J. J. (2013). Emotion regulation: Taking stock and moving forward. Emotion, 13 (3), 359–365. https://doi.org/10.1037/a0032135

Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26 (1), 1–26. https://doi.org/10.1080/1047840X.2014.940781

Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85 (2), 348–362. https://doi.org/10.1037/0022-3514.85.2.348

Gross, J. J., & Levenson, R. W. (1993). Emotional suppression: Physiology, self-report, and expressive behavior. Journal of Personality and Social Psychology, 64 (6), 970–986. https://doi.org/10.1037/0022-3514.64.6.970

Gruber, J., Harvey, A. G., & Gross, J. J. (2012). When trying is not enough: Emotion regulation and the effort–success gap in bipolar disorder. Emotion, 12 (5), 997–1003. https://doi.org/10.1037/a0026822

Guessoum, S. B., Lachal, J., Radjack, R., Carretier, E., Minassian, S., Benoit, L., & Moro, M. R. (2020). Adolescent psychiatric disorders during the COVID-19 pandemic and lockdown. Psychiatry Research, 291 , 113264. https://doi.org/10.1016/j.psychres.2020.113264

Harrer, M., Cuijpers, P., Furukawa, T. A., & Ebert, D. D. (2022). Doing meta-analysis with R: A hands-on guide (First edition). CRC Press.

Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (1999). Acceptance and commitment therapy: An experiential approach to behavior change (pp. xvi, 304). Guilford Press.

Herrmann, J., Koeppen, K., & Kessels, U. (2019). Do girls take school too seriously? Investigating gender differences in school burnout from a self-worth perspective. Learning and Individual Differences, 69 , 150–161. https://doi.org/10.1016/j.lindif.2018.11.011

Higgins, J. P. T., & Green, S. (Eds.) (2011.). Cochrane handbook for systematic reviews of interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration. Retrieved May 13, 2024 from www.handbook.cochrane.org .

Hofmann, S. G., & Asmundson, G. J. G. (2008). Acceptance and mindfulness-based therapy: New wave or old hat? Clinical Psychology Review, 28 (1), 1–16. https://doi.org/10.1016/j.cpr.2007.09.003

Hystad, S. W., Eid, J., Laberg, J. C., Johnsen, B. H., & Bartone, P. T. (2009). Academic Stress and Health: Exploring the Moderating Role of Personality Hardiness. Scandinavian Journal of Educational Research, 53 (5), 421–429. https://doi.org/10.1080/00313830903180349

Ibda, H., Wulandari, T. S., Abdillah, A., Hastuti, A. P., & Mahsun, M. (2023). Student academic stress during the COVID-19 pandemic: A systematic literature review. International Journal of Public Health Science (IJPHS), 12 (1), 286. https://doi.org/10.11591/ijphs.v12i1.21983

Jiang, S., Ren, Q., Jiang, C., & Wang, L. (2021). Academic stress and depression of Chinese adolescents in junior high schools: Moderated mediation model of school burnout and self-esteem. Journal of Affective Disorders, 295 , 384–389. https://doi.org/10.1016/j.jad.2021.08.085

Junyan, F., & Minqiang, Z. (2020). What is the minimum number of effect sizes required in meta-regression? An estimation based on statistical power and estimation precision. Advances in Psychological Science, 28 (4), 673. https://doi.org/10.3724/SP.J.1042.2020.00673

Kim, B., Jee, S., Lee, J., An, S., & Lee, S. M. (2018). Relationships between social support and student burnout: A meta-analytic approach. Stress and Health, 34 (1), 127–134. https://doi.org/10.1002/smi.2771

Kim, S., Kim, H., Park, E. H., Kim, B., Lee, S. M., & Kim, B. (2021). Applying the demand–control–support model on burnout in students: A meta-analysis. Psychology in the Schools, 58 (11), 2130–2147. https://doi.org/10.1002/pits.22581

Kmet, Leanne M. ; Cook, Linda S. ; Lee, Robert C. (2004). Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields . https://doi.org/10.7939/R37M04F16

Kobylińska, D., & Kusev, P. (2019). Flexible Emotion Regulation: How Situational Demands and Individual Differences Influence the Effectiveness of Regulatory Strategies. Frontiers in Psychology , 10 . https://doi.org/10.3389/fpsyg.2019.00072

Koole, S. L. (2009). The psychology of emotion regulation: An integrative review. Cognition and Emotion, 23 (1), 4–41. https://doi.org/10.1080/02699930802619031

Kristensen, T. S., Borritz, M., Villadsen, E., & Christensen, K. B. (2005). The copenhagen burnout inventory: A new tool for the assessment of burnout. Work & Stress, 19 (3), 192–207. https://doi.org/10.1080/02678370500297720

Larsen, R. J. (2000). Toward a science of mood regulation. Psychological Inquiry, 11 (3), 129–141. https://doi.org/10.1207/S15327965PLI1103_01

Lau, S. C., Chow, H. J., Wong, S. C., & Lim, C. S. (2020). An empirical study of the influence of individual-related factors on undergraduates’ academic burnout: Malaysian context. Journal of Applied Research in Higher Education, 13 (4), 1181–1197. https://doi.org/10.1108/JARHE-02-2020-0037

Leppanen, J., Brown, D., McLinden, H., Williams, S., & Tchanturia, K. (2022). The Role of Emotion Regulation in Eating Disorders: A Network Meta-Analysis Approach. Frontiers in Psychiatry, 13. https://doi.org/10.3389/fpsyt.2022.793094

Libert, C., Chabrol, H., & Laconi, S. (2019). Exploration du burn-out et du surengagement académique dans un échantillon d’étudiants. Journal De Thérapie Comportementale Et Cognitive, 29 (3), 119–131. https://doi.org/10.1016/j.jtcc.2019.01.001

Lin, F., & Yang, K. (2021). The External and Internal Factors of Academic Burnout: 2021 4th International Conference on Humanities Education and Social Sciences (ICHESS 2021), Xishuangbanna, China. https://doi.org/10.2991/assehr.k.211220.307

Linehan, M. M. (1993). Cognitive-behavioral treatment of borderline personality disorder (pp. xvii, 558). Guilford Press.

Lo, H. H. M., Ngai, S., & Yam, K. (2021). Effects of Mindfulness-Based Stress Reduction on Health and Social Care Education: A Cohort-Controlled Study. Mindfulness, 12 (8), 2050–2058. https://doi.org/10.1007/s12671-021-01663-z

Luszczynska, A., Diehl, M., Gutiérrez-Doña, B., Kuusinen, P., & Schwarzer, R. (2004). Measuring one component of dispositional self-regulation: Attention control in goal pursuit. Personality and Individual Differences, 37 (3), 555–566. https://doi.org/10.1016/j.paid.2003.09.026

Luo, Y., Wang, Z., Zhang, H., Chen, A., & Quan, S. (2016). The effect of perfectionism on school burnout among adolescence: The mediator of self-esteem and coping style. Personality and Individual Differences, 88 , 202–208. https://doi.org/10.1016/j.paid.2015.08.056

Luo, Y., Deng, Y., & Zhang, H. (2020). The influences of parental emotional warmth on the association between perceived teacher–student relationships and academic stress among middle school students in China. Children and Youth Services Review, 114 , 105014. https://doi.org/10.1016/j.childyouth.2020.105014

Lynch, T. R., Trost, W. T., Salsman, N., & Linehan, M. M. (2007). Dialectical behavior therapy for borderline personality disorder. Annual Review of Clinical Psychology, 3 , 181–205. https://doi.org/10.1146/annurev.clinpsy.2.022305.095229

Madigan, D. J., & Curran, T. (2021). Does burnout affect academic achievement? A meta-analysis of over 100,000 students. Educational Psychology Review, 33 (2), 387–405. https://doi.org/10.1007/s10648-020-09533-1

Madigan, D. J., Kim, L. E., & Glandorf, H. L. (2023). Interventions to reduce burnout in students: A systematic review and meta-analysis. European Journal of Psychology of Education . https://doi.org/10.1007/s10212-023-00731-3

Maeda, Y., & Harwell, M. (2016). Guidelines for using the Q Test in Meta-Analysis. Mid-Western Educational Researcher, 28 (1). Retrieved May 22, 2024, from https://scholarworks.bgsu.edu/mwer/vol28/iss1/4

Marques, H., Brites, R., Nunes, O., Hipólito, J., & Brandão, T. (2023). Attachment, emotion regulation, and burnout among university students: A mediational hypothesis. Educational Psychology, 43 (4), 344–362. https://doi.org/10.1080/01443410.2023.2212889

Matud, M. P., Díaz, A., Bethencourt, J. M., & Ibáñez, I. (2020). Stress and Psychological Distress in Emerging Adulthood: A Gender Analysis. Journal of Clinical Medicine, 9 (9), 2859. https://doi.org/10.3390/jcm9092859

May, R. W., Bauer, K. N., & Fincham, F. D. (2015). School burnout: Diminished academic and cognitive performance. Learning and Individual Differences, 42 , 126–131. https://doi.org/10.1016/j.lindif.2015.07.015

Mennin, D. S., Holaway, R. M., Fresco, D. M., Moore, M. T., & Heimberg, R. G. (2007). Delineating components of emotion and its dysregulation in anxiety and mood psychopathology. Behavior Therapy, 38 (3), 284–302. https://doi.org/10.1016/j.beth.2006.09.001

Merino-Tejedor, E., Hontangas, P. M., & Boada-Grau, J. (2016). Career adaptability and its relation to self-regulation, career construction, and academic engagement among Spanish university students. Journal of Vocational Behavior, 93 , 92–102. https://doi.org/10.1016/j.jvb.2016.01.005

Meylan, N., Doudin, P.-A., Curchod-Ruedi, D., & Stephan, P. (2015). Burnout scolaire et soutien social: L’importance du soutien des parents et des enseignants. Psychologie Française, 60 (1), 1–15. https://doi.org/10.1016/j.psfr.2014.01.003

Mickenautsch, S., Yengopal, V., Mickenautsch, S., & Yengopal, V. (2024). Trial Number and Sample Size Do Not Affect the Accuracy of the I2-Point Estimate for Testing Selection Bias Risk in Meta-Analyses. Cureus, 16 , 4. https://doi.org/10.7759/cureus.58961

Midgley, C., Maehr, M., Hruda, L., Anderman, E., Anderman, L., Freeman, K., Gheen, M., Kaplan, A., Kumar, R., Middleton, M., Nelson, J., Roeser, R., & Urdan, T. (2000). The patterns of adaptive learning scales (PALS) 2000 [Dataset].

Miola, A., Cattarinussi, G., Antiga, G., Caiolo, S., Solmi, M., & Sambataro, F. (2022). Difficulties in emotion regulation in bipolar disorder: A systematic review and meta-analysis. Journal of Affective Disorders, 302 , 352–360. https://doi.org/10.1016/j.jad.2022.01.102

Miu, A. C., Szentágotai-Tătar, A., Balázsi, R., Nechita, D., Bunea, I., & Pollak, S. D. (2022). Emotion regulation as mediator between childhood adversity and psychopathology: A meta-analysis. Clinical Psychology Review, 93 , 102141. https://doi.org/10.1016/j.cpr.2022.102141

Modrego-Alarcón, M., López-Del-Hoyo, Y., García-Campayo, J., Pérez-Aranda, A., Navarro-Gil, M., Beltrán-Ruiz, M., Morillo, H., Delgado-Suarez, I., Oliván-Arévalo, R., & Montero-Marin, J. (2021). Efficacy of a mindfulness-based programme with and without virtual reality support to reduce stress in university students: A randomized controlled trial. Behaviour Research and Therapy, 142 , 103866. https://doi.org/10.1016/j.brat.2021.103866

Mohammadi Bytamar, J., Saed, O., & Khakpoor, S. (2020). Emotion Regulation Difficulties and Academic Procrastination. Frontiers in Psychology, 11 , 524588. https://doi.org/10.3389/fpsyg.2020.524588

Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ, 339 , b2535. https://doi.org/10.1136/bmj.b2535

Muchacka-Cymerman, A., & Tomaszek, K. (2018). Polish Adaptation of the ESSBS School-Burnout Scale: Pilot Study Results. Hacettepe University Journal of Education , 1–16. https://doi.org/10.16986/HUJE.2018043462

Naderi, Z., Bakhtiari, S., Momennasab, M., Abootalebi, M., & Mirzaei, T. (2018). Prediction of academic burnout and academic performance based on the need for cognition and general self-efficacy: A cross-sectional analytical study. Revista Latinoamericana De Hipertensión, 13 (6), 584–591.

Narimanj, A., Kazemi, R., & Narimani, M. (2021). Relationship between Cognitive Emotion Regulation, Personal Intelligence and Academic Burnout. Journal of Modern Psychological Researches, 16 (61), 65–74.

Neacsiu, A. D., Rizvi, S. L., & Linehan, M. M. (2010). Dialectical behavior therapy skills use as a mediator and outcome of treatment for borderline personality disorder. Behaviour Research and Therapy, 48 (9), 832–839. https://doi.org/10.1016/j.brat.2010.05.017

Neff, K. D. (2003). The development and validation of a scale to measure self-compassion. Self and Identity, 2 (3), 223–250. https://doi.org/10.1080/15298860309027

Nikdel, F., Hadi, J., & Ali, T. (2019). SOCIAL SCIENCES & HUMANITIES Students’ Academic Stress, Stress Response and Academic Burnout: Mediating Role of Self-Efficacy .

Noh, H., Chang, E., Jang, Y., Lee, J. H., & Lee, S. M. (2016). Suppressor Effects of Positive and Negative Religious Coping on Academic Burnout Among Korean Middle School Students. Journal of Religion and Health, 55 (1), 135–146. https://doi.org/10.1007/s10943-015-0007-8

Nolen-Hoeksema, S., Wisco, B. E., & Lyubomirsky, S. (2008). Rethinking Rumination. Perspectives on Psychological Science, 3 (5), 400–424. https://doi.org/10.1111/j.1745-6924.2008.00088.x

Nyklícek, I., & Temoshok, L. (2004). Emotional expression and health: Advances in theory, assessment and clinical applications . Routledge.

Ogbuanya, T. C., Eseadi, C., Orji, C. T., Omeje, J. C., Anyanwu, J. I., Ugwoke, S. C., & Edeh, N. C. (2019). Effect of Rational-Emotive Behavior Therapy Program on the Symptoms of Burnout Syndrome Among Undergraduate Electronics Work Students in Nigeria. Psychological Reports, 122 (1), 4–22. https://doi.org/10.1177/0033294117748587

Östberg, V., Almquist, Y. B., Folkesson, L., Låftman, S. B., Modin, B., & Lindfors, P. (2015). The Complexity of Stress in Mid-Adolescent Girls and Boys. Child Indicators Research, 8 (2), 403–423. https://doi.org/10.1007/s12187-014-9245-7

Park, E.-Y., & Shin, M. (2020). A Meta-Analysis of Special Education Teachers’ Burnout. SAGE Open, 10 (2), 2158244020918297. https://doi.org/10.1177/2158244020918297

Parkinson, B., & Totterdell, P. (1999). Classifying affect-regulation strategies. Cognition and Emotion, 13 (3), 277–303. https://doi.org/10.1080/026999399379285

Pines, A., & Aronson, E. (1988). Career Burnout: Causes and Cures . Free Press.

Popescu, B., Maricuțoiu, L. P., & De Witte, H. (2023). The student version of the Burnout assessement tool (BAT): Psychometric properties and evidence regarding measurement validity on a romanian sample. Current Psychology . https://doi.org/10.1007/s12144-023-04232-w

Prefit, A.-B., Cândea, D. M., & Szentagotai-Tătar, A. (2019). Emotion regulation across eating pathology: A meta-analysis. Appetite, 143 , 104438. https://doi.org/10.1016/j.appet.2019.104438

Prospero. (2022). Systematic review registration: Emotion regulation and academic burnout in youths: a meta-analysis. Retrieved May 22, 2024, from  https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=325570

Ramírez, M. T. G., & Hernández, R. L. (2007). ESCALA DE CANSANCIO EMOCIONAL (ECE) PARA ESTUDIANTES UNIVERSITARIOS: PROPIEDADES PSICOMÉTRICAS EN UNA MUESTRA DE MÉXICO. Anales de Psicología / Annals of Psychology, 23 (2).

Richards, J. M., & Gross, J. J. (2000). Emotion regulation and memory: The cognitive costs of keeping one’s cool. Journal of Personality and Social Psychology, 79 (3), 410–424. https://doi.org/10.1037/0022-3514.79.3.410

Richards, J. M., Butler, E. A., & Gross, J. J. (2003). Emotion regulation in romantic relationships: The cognitive consequences of concealing feelings. Journal of Social and Personal Relationships, 20 (5), 599–620. https://doi.org/10.1177/02654075030205002

Roemer, L., Orsillo, S. M., & Salters-Pedneault, K. (2008). Efficacy of an acceptance-based behavior therapy for generalized anxiety disorder: Evaluation in a randomized controlled trial. Journal of Consulting and Clinical Psychology, 76 (6), 1083–1089. https://doi.org/10.1037/a0012720

Salmela-Aro, K. (2017). Dark and bright sides of thriving – school burnout and engagement in the Finnish context. European Journal of Developmental Psychology, 14 (3), 337–349. https://doi.org/10.1080/17405629.2016.1207517

Salmela-Aro, K., & Tynkkynen, L. (2012). Gendered pathways in school burnout among adolescents. Journal of Adolescence, 35 (4), 929–939. https://doi.org/10.1016/j.adolescence.2012.01.001

Salmela-aro *, K., Näätänen, P., & Nurmi, J. (2004). The role of work-related personal projects during two burnout interventions: A longitudinal study. Work & Stress, 18(3), 208–230. https://doi.org/10.1080/02678370412331317480

Salmela-Aro, K., Kiuru, N., Leskinen, E., & Nurmi, J.-E. (2009). School burnout inventory (SBI). European Journal of Psychological Assessment, 25 (1), 48–57. https://doi.org/10.1027/1015-5759.25.1.48

Santos Alves Peixoto, L., Guedes Gondim, S. M., & Pereira, C. R. (2022). Emotion Regulation, Stress, and Well-Being in Academic Education: Analyzing the Effect of Mindfulness-Based Intervention. Trends in Psychology, 30 (1), 33–57. https://doi.org/10.1007/s43076-021-00092-0

Scales, P. C., Benson, P. L., Oesterle, S., Hill, K. G., Hawkins, J. D., & Pashak, T. J. (2016). The dimensions of successful young adult development: A conceptual and measurement framework. Applied Developmental Science, 20 (3), 150–174. https://doi.org/10.1080/10888691.2015.1082429

Schaufeli, W. B., Salanova, M., González-romá, V., & Bakker, A. B. (2002). The measurement of engagement and burnout: A two sample confirmatory factor analytic approach. Journal of Happiness Studies, 3 (1), 71–92. https://doi.org/10.1023/A:1015630930326

Schaufeli, W. B., Desart, S., & De Witte, H. (2020). Burnout assessment tool (BAT)—development, validity, and reliability. International Journal of Environmental Research and Public Health, 17 (24). https://doi.org/10.3390/ijerph17249495

Schmid, C. H., Stijnen, T., & White, I. (2020). Handbook of Meta-Analysis . CRC Press.

Segal, Z. V., Williams, J. M. G., & Teasdale, J. D. (2002). Mindfulness-based cognitive therapy for depression: A new approach to preventing relapse (pp. xiv, 351). Guilford Press.

Séguin, D. G., & MacDonald, B. (2018). The role of emotion regulation and temperament in the prediction of the quality of social relationships in early childhood. Early Child Development and Care, 188 (8), 1147–1163. https://doi.org/10.1080/03004430.2016.1251678

Seibert, G. S., Bauer, K. N., May, R. W., & Fincham, F. D. (2017). Emotion regulation and academic underperformance: The role of school burnout. Learning and Individual Differences, 60 , 1–9. https://doi.org/10.1016/j.lindif.2017.10.001

Shahidi, S., Akbari, H., & Zargar, F. (2017). Effectiveness of mindfulness-based stress reduction on emotion regulation and test anxiety in female high school students. Journal of Education and Health Promotion, 6 , 87. https://doi.org/10.4103/jehp.jehp_98_16

Shih, S.-S. (2013). The effects of autonomy support versus psychological control and work engagement versus academic burnout on adolescents’ use of avoidance strategies. School Psychology International, 34 (3), 330–347. https://doi.org/10.1177/0143034312466423

Shih, S.-S. (2015a). An Examination of Academic Coping Among Taiwanese Adolescents. The Journal of Educational Research, 108 (3), 175–185. https://doi.org/10.1080/00220671.2013.867473

Shih, S.-S. (2015b). The relationships among Taiwanese adolescents’ perceived classroom environment, academic coping, and burnout. School Psychology Quarterly: The Official Journal of the Division of School Psychology, American Psychological Association, 30 (2), 307–320. https://doi.org/10.1037/spq0000093

Stellern, J., Xiao, K. B., Grennell, E., Sanches, M., Gowin, J. L., & Sloan, M. E. (2023). Emotion regulation in substance use disorders: A systematic review and meta-analysis. Addiction, 118 (1), 30–47. https://doi.org/10.1111/add.16001

Tobin, D. L., Holroyd, K. A., Reynolds, R. V., & Wigal, J. K. (1989). The hierarchical factor structure of the Coping Strategies Inventory. Cognitive Therapy and Research, 13 (4), 343–361. https://doi.org/10.1007/BF01173478

Troy, A. S., Shallcross, A. J., & Mauss, I. B. (2013). A Person-by-Situation Approach to Emotion Regulation: Cognitive Reappraisal Can Either Help or Hurt. Depending on the Context. Psychological Science, 24 (12), 2505–2514. https://doi.org/10.1177/0956797613496434

Tull, M. T., & Aldao, A. (2015). Editorial overview: New directions in the science of emotion regulation. Current Opinion in Psychology, 3 , iv–x. https://doi.org/10.1016/j.copsyc.2015.03.009

Vinter, K., Aus, K., & Arro, G. (2021). Adolescent girls’ and boys’ academic burnout and its associations with cognitive emotion regulation strategies. Educational Psychology, 41 (8), 1061–1077. https://doi.org/10.1080/01443410.2020.1855631

Vizoso, C., Arias-Gundín, O., & Rodríguez, C. (2019). Exploring coping and optimism as predictors of academic burnout and performance among university students. Educational Psychology, 39 (6), 768–783. https://doi.org/10.1080/01443410.2018.1545996

von Hippel, P. T. (2015). The heterogeneity statistic I(2) can be biased in small meta-analyses. BMC Medical Research Methodology, 15 , 35. https://doi.org/10.1186/s12874-015-0024-z

Walburg, V. (2014). Burnout among high school students: A literature review. Children and Youth Services Review, 42 , 28–33. https://doi.org/10.1016/j.childyouth.2014.03.020

Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: A meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. Psychological Bulletin, 138 (4), 775–808. https://doi.org/10.1037/a0027600

Weiss, N. H., Kiefer, R., Goncharenko, S., Raudales, A. M., Forkus, S. R., Schick, M. R., & Contractor, A. A. (2022). Emotion regulation and substance use: A meta-analysis. Drug and Alcohol Dependence, 230 , 109131. https://doi.org/10.1016/j.drugalcdep.2021.109131

Westhues, A., & Cohen, J. S. (1997). A comparison of the adjustment of adolescent and young adult inter-country adoptees and their siblings. International Journal of Behavioral Development, 20 (1), 47–65. https://doi.org/10.1080/016502597385432

Wu, K., Wang, F., Wang, W., & Li, Y. (2022). Parents’ Education Anxiety and Children’s Academic Burnout: The Role of Parental Burnout and Family Function. Frontiers in Psychology , 12 . https://doi.org/10.3389/fpsyg.2021.764824

Yang, H., & Chen, J. (2016). Learning Perfectionism and Learning Burnout in a Primary School Student Sample: A Test of a Learning-Stress Mediation Model. Journal of Child and Family Studies, 25 (1), 345–353. https://doi.org/10.1007/s10826-015-0213-8

Yang, C., Chen, A., & Chen, Y. (2021). College students’ stress and health in the COVID-19 pandemic: The role of academic workload, separation from school, and fears of contagion. PLoS ONE, 16 (2), e0246676. https://doi.org/10.1371/journal.pone.0246676

Yildiz, M. A. (2017). Pathways to positivity from perceived stress in adolescents: Multiple mediation of emotion regulation and coping strategies. Current Issues in Personality Psychology, 5 (4), 272–284. https://doi.org/10.5114/cipp.2017.67894

Yu, X., Wang, Y., & Liu, F. (2022). Language learning motivation and burnout among english as a foreign language undergraduates: The moderating role of maladaptive emotion regulation strategies. Frontiers in Psychology , 13 .  https://www.frontiersin.org/articles/10.3389/fpsyg.2022.808118

Zahniser, E., & Conley, C. S. (2018). Interactions of emotion regulation and perceived stress in predicting emerging adults’ subsequent internalizing symptoms. Motivation and Emotion, 42 (5), 763–773. https://doi.org/10.1007/s11031-018-9696-0

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This work was supported by two grants awarded to the corresponding author from the Romanian National Authority for Scientific Research, CNCS—UEFISCDI (Grant number PN-III-P4-ID-PCE-2020-2170 and PN-III-P2-2.1-PED-2021-3882)

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Qualitative vs Quantitative Research Methods & Data Analysis

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The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

• Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
• Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.

On This Page:

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography .

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Mixed methods research
• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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Critically Thinking About Qualitative Versus Quantitative Research

What should we do regarding our research questions and methodology.

Posted January 26, 2022 | Reviewed by Davia Sills

• Neither a quantitative nor a qualitative methodology is the right way to approach every scientific question.
• Rather, the nature of the question determines which methodology is best suited to address it.
• Often, researchers benefit from a mixed approach that incorporates both quantitative and qualitative methodologies.

As a researcher who has used a wide variety of methodologies, I understand the importance of acknowledging that we, as researchers, do not pick the methodology; rather, the research question dictates it. So, you can only imagine how annoyed I get when I hear of undergraduates designing their research projects based on preconceived notions, like "quantitative is more straightforward," or "qualitative is easier." Apart from the fact that neither of these assertions is actually the case, these young researchers are blatantly missing one of the foundational steps of good research: If you are interested in researching a particular area, you must get to know the area (i.e., through reading) and then develop a question based on that reading.

The nature of the question will dictate the most appropriate methodological approach.

I’ve debated with researchers in the past who are "exclusively" qualitative or "exclusively" quantitative. Depending on the rationale for their exclusivity, I might question a little deeper, learn something, and move on, or I might debate further. Sometimes, I throw some contentious statements out to see what the responses are like. For example, "Qualitative research, in isolation, is nothing but glorified journalism . " This one might not be new to you. Yes, qualitative is flawed, but so, too, is quantitative.

Let's try this one: "Numbers don’t lie, just the researchers who interpret them." If researchers are going to have a pop at qual for subjectivity, why don’t they recognize the same issues in quant? The numbers in a results section may be objectively correct, but their meaningfulness is only made clear through the interpretation of the human reporting them. This is not a criticism but is an important observation for those who believe in the absolute objectivity of quantitative reporting. The subjectivity associated with this interpretation may miss something crucial in the interpretation of the numbers because, hey, we’re only human.

With that, I love quantitative research, but I’m not unreasonable about it. Let’s say we’ve evaluated a three-arm RCT—the new therapeutic intervention is significantly efficacious, with a large effect, for enhancing "x" in people living with "y." One might conclude that this intervention works and that we must conduct further research on it to further support its efficacy—this is, of course, a fine suggestion, consistent with good research practice and epistemological understanding.

However, blindly recommending the intervention based on the interpretation of numbers alone might be suspect—think of all the variables that could be involved in a 4-, 8-, 12-, or 52-week intervention with human participants. It would be foolish to believe that all variables were considered—so, here is a fantastic example of where a qualitative methodology might be useful. At the end of the intervention, a researcher might decide to interview a random 20 percent of the cohort who participated in the intervention group about their experience and the program’s strengths and weaknesses. The findings from this qualitative element might help further explain the effects, aid the initial interpretation, and bring to life new ideas and concepts that had been missing from the initial interpretation. In this respect, infusing a qualitative approach at the end of quantitative analysis has shown its benefits—a mixed approach to intervention evaluation is very useful.

What about before that? Well, let’s say I want to develop another intervention to enhance "z," but there’s little research on it, and that which has been conducted isn’t of the highest quality; furthermore, we don’t know about people’s experiences with "z" or even other variables associated with it.

To design an intervention around "z" would be ‘jumping the gun’ at best (and a waste of funds). It seems that an exploration of some sort is necessary. This is where qualitative again shines—giving us an opportunity to explore what "z" is from the perspective of a relevant cohort(s).

Of course, we cannot generalize the findings; we cannot draw a definitive conclusion as to what "z" is. But what the findings facilitate is providing a foundation from which to work; for example, we still cannot say that "z" is this, that, or the other, but it appears that it might be associated with "a," "b" and "c." Thus, future research should investigate the nature of "z" as a particular concept, in relation to "a," "b" and "c." Again, a qualitative methodology shows its worth. In the previous examples, a qualitative method was used because the research questions warranted it.

Through considering the potentially controversial statements about qual and quant above, we are pushed into examining the strengths and weaknesses of research methodologies (regardless of our exclusivity with a particular approach). This is useful if we’re going to think critically about finding answers to our research questions. But simply considering these does not let poor research practice off the hook.

For example, credible qualitative researchers acknowledge that generalizability is not the point of their research; however, that doesn’t stop some less-than-credible researchers from presenting their "findings" as generalizable as possible, without actually using the word. Such practices should be frowned upon—so should making a career out of strictly using qualitative methodology in an attempt to find answers core to the human condition. All these researchers are really doing is spending a career exploring, yet never really finding anything (despite arguing to the contrary, albeit avoiding the word "generalize").

The solution to this problem, again, is to truly listen to what your research question is telling you. Eventually, it’s going to recommend a quantitative approach. Likewise, a "numbers person" will be recommended a qualitative approach from time to time—flip around the example above, and there’s a similar criticism. Again, embrace a mixed approach.

What's the point of this argument?

I conduct both research methodologies. Which do I prefer? Simple—whichever one helps me most appropriately answer my research question.

Do I have problems with qualitative methodologies? Absolutely—but I have issues with quantitative methods as well. Having these issues is good—it means that you recognize the limitations of your tools, which increases the chances of you "fixing," "sharpening" or "changing out" your tools when necessary.

So, the next time someone speaks with you about labeling researchers as one type or another, ask them why they think that way, ask them which they think you are, and then reflect on the responses alongside your own views of methodology and epistemology. It might just help you become a better researcher.

Christopher Dwyer, Ph.D., is a lecturer at the Technological University of the Shannon in Athlone, Ireland.

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Synthesising quantitative and qualitative evidence to inform guidelines on complex interventions: clarifying the purposes, designs and outlining some methods

1 School of Social Sciences, Bangor University, Wales, UK

Andrew Booth

2 School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK

Graham Moore

3 School of Social Sciences, Cardiff University, Wales, UK

Kate Flemming

4 Department of Health Sciences, The University of York, York, UK

Özge Tunçalp

5 Department of Reproductive Health and Research including UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), World Health Organization, Geneva, Switzerland

Elham Shakibazadeh

6 Department of Health Education and Promotion, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

Associated Data

bmjgh-2018-000893supp001.pdf

bmjgh-2018-000893supp002.pdf

bmjgh-2018-000893supp003.pdf

bmjgh-2018-000893supp005.pdf

bmjgh-2018-000893supp004.pdf

Guideline developers are increasingly dealing with more difficult decisions concerning whether to recommend complex interventions in complex and highly variable health systems. There is greater recognition that both quantitative and qualitative evidence can be combined in a mixed-method synthesis and that this can be helpful in understanding how complexity impacts on interventions in specific contexts. This paper aims to clarify the different purposes, review designs, questions, synthesis methods and opportunities to combine quantitative and qualitative evidence to explore the complexity of complex interventions and health systems. Three case studies of guidelines developed by WHO, which incorporated quantitative and qualitative evidence, are used to illustrate possible uses of mixed-method reviews and evidence. Additional examples of methods that can be used or may have potential for use in a guideline process are outlined. Consideration is given to the opportunities for potential integration of quantitative and qualitative evidence at different stages of the review and guideline process. Encouragement is given to guideline commissioners and developers and review authors to consider including quantitative and qualitative evidence. Recommendations are made concerning the future development of methods to better address questions in systematic reviews and guidelines that adopt a complexity perspective.

Summary box

• When combined in a mixed-method synthesis, quantitative and qualitative evidence can potentially contribute to understanding how complex interventions work and for whom, and how the complex health systems into which they are implemented respond and adapt.
• The different purposes and designs for combining quantitative and qualitative evidence in a mixed-method synthesis for a guideline process are described.
• Questions relevant to gaining an understanding of the complexity of complex interventions and the wider health systems within which they are implemented that can be addressed by mixed-method syntheses are presented.
• The practical methodological guidance in this paper is intended to help guideline producers and review authors commission and conduct mixed-method syntheses where appropriate.
• If more mixed-method syntheses are conducted, guideline developers will have greater opportunities to access this evidence to inform decision-making.

Introduction

Recognition has grown that while quantitative methods remain vital, they are usually insufficient to address complex health systems related research questions. 1 Quantitative methods rely on an ability to anticipate what must be measured in advance. Introducing change into a complex health system gives rise to emergent reactions, which cannot be fully predicted in advance. Emergent reactions can often only be understood through combining quantitative methods with a more flexible qualitative lens. 2 Adopting a more pluralist position enables a diverse range of research options to the researcher depending on the research question being investigated. 3–5 As a consequence, where a research study sits within the multitude of methods available is driven by the question being asked, rather than any particular methodological or philosophical stance. 6

Publication of guidance on designing complex intervention process evaluations and other works advocating mixed-methods approaches to intervention research have stimulated better quality evidence for synthesis. 1 7–13 Methods for synthesising qualitative 14 and mixed-method evidence have been developed or are in development. Mixed-method research and review definitions are outlined in box 1 .

Defining mixed-method research and reviews

Pluye and Hong 52 define mixed-methods research as “a research approach in which a researcher integrates (a) qualitative and quantitative research questions, (b) qualitative research methods* and quantitative research designs, (c) techniques for collecting and analyzing qualitative and quantitative evidence, and (d) qualitative findings and quantitative results”.A mixed-method synthesis can integrate quantitative, qualitative and mixed-method evidence or data from primary studies.† Mixed-method primary studies are usually disaggregated into quantitative and qualitative evidence and data for the purposes of synthesis. Thomas and Harden further define three ways in which reviews are mixed. 53

• The types of studies included and hence the type of findings to be synthesised (ie, qualitative/textual and quantitative/numerical).
• The types of synthesis method used (eg, statistical meta-analysis and qualitative synthesis).
• The mode of analysis: theory testing AND theory building.

*A qualitative study is one that uses qualitative methods of data collection and analysis to produce a narrative understanding of the phenomena of interest. Qualitative methods of data collection may include, for example, interviews, focus groups, observations and analysis of documents.

†The Cochrane Qualitative and Implementation Methods group coined the term ‘qualitative evidence synthesis’ to mean that the synthesis could also include qualitative data. For example, qualitative data from case studies, grey literature reports and open-ended questions from surveys. ‘Evidence’ and ‘data’ are used interchangeably in this paper.

This paper is one of a series that aims to explore the implications of complexity for systematic reviews and guideline development, commissioned by WHO. This paper is concerned with the methodological implications of including quantitative and qualitative evidence in mixed-method systematic reviews and guideline development for complex interventions. The guidance was developed through a process of bringing together experts in the field, literature searching and consensus building with end users (guideline developers, clinicians and reviewers). We clarify the different purposes, review designs, questions and synthesis methods that may be applicable to combine quantitative and qualitative evidence to explore the complexity of complex interventions and health systems. Three case studies of WHO guidelines that incorporated quantitative and qualitative evidence are used to illustrate possible uses of mixed-method reviews and mechanisms of integration ( table 1 , online supplementary files 1–3 ). Additional examples of methods that can be used or may have potential for use in a guideline process are outlined. Opportunities for potential integration of quantitative and qualitative evidence at different stages of the review and guideline process are presented. Specific considerations when using an evidence to decision framework such as the Developing and Evaluating Communication strategies to support Informed Decisions and practice based on Evidence (DECIDE) framework 15 or the new WHO-INTEGRATE evidence to decision framework 16 at the review design and evidence to decision stage are outlined. See online supplementary file 4 for an example of a health systems DECIDE framework and Rehfuess et al 16 for the new WHO-INTEGRATE framework. Encouragement is given to guideline commissioners and developers and review authors to consider including quantitative and qualitative evidence in guidelines of complex interventions that take a complexity perspective and health systems focus.

Designs and methods and their use or applicability in guidelines and systematic reviews taking a complexity perspective

Supplementary data

Taking a complexity perspective.

The first paper in this series 17 outlines aspects of complexity associated with complex interventions and health systems that can potentially be explored by different types of evidence, including synthesis of quantitative and qualitative evidence. Petticrew et al 17 distinguish between a complex interventions perspective and a complex systems perspective. A complex interventions perspective defines interventions as having “implicit conceptual boundaries, representing a flexible, but common set of practices, often linked by an explicit or implicit theory about how they work”. A complex systems perspective differs in that “ complexity arises from the relationships and interactions between a system’s agents (eg, people, or groups that interact with each other and their environment), and its context. A system perspective conceives the intervention as being part of the system, and emphasises changes and interconnections within the system itself”. Aspects of complexity associated with implementation of complex interventions in health systems that could potentially be addressed with a synthesis of quantitative and qualitative evidence are summarised in table 2 . Another paper in the series outlines criteria used in a new evidence to decision framework for making decisions about complex interventions implemented in complex systems, against which the need for quantitative and qualitative evidence can be mapped. 16 A further paper 18 that explores how context is dealt with in guidelines and reviews taking a complexity perspective also recommends using both quantitative and qualitative evidence to better understand context as a source of complexity. Mixed-method syntheses of quantitative and qualitative evidence can also help with understanding of whether there has been theory failure and or implementation failure. The Cochrane Qualitative and Implementation Methods Group provide additional guidance on exploring implementation and theory failure that can be adapted to address aspects of complexity of complex interventions when implemented in health systems. 19

Health-system complexity-related questions that a synthesis of quantitative and qualitative evidence could address (derived from Petticrew et al 17 )

It may not be apparent which aspects of complexity or which elements of the complex intervention or health system can be explored in a guideline process, or whether combining qualitative and quantitative evidence in a mixed-method synthesis will be useful, until the available evidence is scoped and mapped. 17 20 A more extensive lead in phase is typically required to scope the available evidence, engage with stakeholders and to refine the review parameters and questions that can then be mapped against potential review designs and methods of synthesis. 20 At the scoping stage, it is also common to decide on a theoretical perspective 21 or undertake further work to refine a theoretical perspective. 22 This is also the stage to begin articulating the programme theory of the complex intervention that may be further developed to refine an understanding of complexity and show how the intervention is implemented in and impacts on the wider health system. 17 23 24 In practice, this process can be lengthy, iterative and fluid with multiple revisions to the review scope, often developing and adapting a logic model 17 as the available evidence becomes known and the potential to incorporate different types of review designs and syntheses of quantitative and qualitative evidence becomes better understood. 25 Further questions, propositions or hypotheses may emerge as the reviews progress and therefore the protocols generally need to be developed iteratively over time rather than a priori.

Following a scoping exercise and definition of key questions, the next step in the guideline development process is to identify existing or commission new systematic reviews to locate and summarise the best available evidence in relation to each question. For example, case study 2, ‘Optimising health worker roles for maternal and newborn health through task shifting’, included quantitative reviews that did and did not take an additional complexity perspective, and qualitative evidence syntheses that were able to explain how specific elements of complexity impacted on intervention outcomes within the wider health system. Further understanding of health system complexity was facilitated through the conduct of additional country-level case studies that contributed to an overall understanding of what worked and what happened when lay health worker interventions were implemented. See table 1 online supplementary file 2 .

There are a few existing examples, which we draw on in this paper, but integrating quantitative and qualitative evidence in a mixed-method synthesis is relatively uncommon in a guideline process. Box 2 includes a set of key questions that guideline developers and review authors contemplating combining quantitative and qualitative evidence in mixed-methods design might ask. Subsequent sections provide more information and signposting to further reading to help address these key questions.

Key questions that guideline developers and review authors contemplating combining quantitative and qualitative evidence in a mixed-methods design might ask

Compound questions requiring both quantitative and qualitative evidence?

Questions requiring mixed-methods studies?

Separate quantitative and qualitative questions?

Separate quantitative and qualitative research studies?

Related quantitative and qualitative research studies?

Mixed-methods studies?

Quantitative unpublished data and/or qualitative unpublished data, eg, narrative survey data?

Throughout the review?

Following separate reviews?

At the question point?

At the synthesis point?

At the evidence to recommendations stage?

Or a combination?

Narrative synthesis or summary?

Quantitising approach, eg, frequency analysis?

Qualitising approach, eg, thematic synthesis?

Tabulation?

Logic model?

Conceptual model/framework?

Graphical approach?

• WHICH: Which mixed-method designs, methodologies and methods best fit into a guideline process to inform recommendations?

Complexity-related questions that a synthesis of quantitative and qualitative evidence can potentially address

Petticrew et al 17 define the different aspects of complexity and examples of complexity-related questions that can potentially be explored in guidelines and systematic reviews taking a complexity perspective. Relevant aspects of complexity outlined by Petticrew et al 17 are summarised in table 2 below, together with the corresponding questions that could be addressed in a synthesis combining qualitative and quantitative evidence. Importantly, the aspects of complexity and their associated concepts of interest have however yet to be translated fully in primary health research or systematic reviews. There are few known examples where selected complexity concepts have been used to analyse or reanalyse a primary intervention study. Most notable is Chandler et al 26 who specifically set out to identify and translate a set of relevant complexity theory concepts for application in health systems research. Chandler then reanalysed a trial process evaluation using selected complexity theory concepts to better understand the complex causal pathway in the health system that explains some aspects of complexity in table 2 .

Rehfeuss et al 16 also recommends upfront consideration of the WHO-INTEGRATE evidence to decision criteria when planning a guideline and formulating questions. The criteria reflect WHO norms and values and take account of a complexity perspective. The framework can be used by guideline development groups as a menu to decide which criteria to prioritise, and which study types and synthesis methods can be used to collect evidence for each criterion. Many of the criteria and their related questions can be addressed using a synthesis of quantitative and qualitative evidence: the balance of benefits and harms, human rights and sociocultural acceptability, health equity, societal implications and feasibility (see table 3 ). Similar aspects in the DECIDE framework 15 could also be addressed using synthesis of qualitative and quantitative evidence.

Integrate evidence to decision framework criteria, example questions and types of studies to potentially address these questions (derived from Rehfeuss et al 16 )

GIS, Geographical Information System; RCT, randomised controlled trial.

Questions as anchors or compasses

Questions can serve as an ‘anchor’ by articulating the specific aspects of complexity to be explored (eg, Is successful implementation of the intervention context dependent?). 27 Anchor questions such as “How does intervention x impact on socioeconomic inequalities in health behaviour/outcome x” are the kind of health system question that requires a synthesis of both quantitative and qualitative evidence and hence a mixed-method synthesis. Quantitative evidence can quantify the difference in effect, but does not answer the question of how . The ‘how’ question can be partly answered with quantitative and qualitative evidence. For example, quantitative evidence may reveal where socioeconomic status and inequality emerges in the health system (an emergent property) by exploring questions such as “ Does patterning emerge during uptake because fewer people from certain groups come into contact with an intervention in the first place? ” or “ are people from certain backgrounds more likely to drop out, or to maintain effects beyond an intervention differently? ” Qualitative evidence may help understand the reasons behind all of these mechanisms. Alternatively, questions can act as ‘compasses’ where a question sets out a starting point from which to explore further and to potentially ask further questions or develop propositions or hypotheses to explore through a complexity perspective (eg, What factors enhance or hinder implementation?). 27 Other papers in this series provide further guidance on developing questions for qualitative evidence syntheses and guidance on question formulation. 14 28

For anchor and compass questions, additional application of a theory (eg, complexity theory) can help focus evidence synthesis and presentation to explore and explain complexity issues. 17 21 Development of a review specific logic model(s) can help to further refine an initial understanding of any complexity-related issues of interest associated with a specific intervention, and if appropriate the health system or section of the health system within which to contextualise the review question and analyse data. 17 23–25 Specific tools are available to help clarify context and complex interventions. 17 18

If a complexity perspective, and certain criteria within evidence to decision frameworks, is deemed relevant and desirable by guideline developers, it is only possible to pursue a complexity perspective if the evidence is available. Careful scoping using knowledge maps or scoping reviews will help inform development of questions that are answerable with available evidence. 20 If evidence of effect is not available, then a different approach to develop questions leading to a more general narrative understanding of what happened when complex interventions were implemented in a health system will be required (such as in case study 3—risk communication guideline). This should not mean that the original questions developed for which no evidence was found when scoping the literature were not important. An important function of creating a knowledge map is also to identify gaps to inform a future research agenda.

Table 2 and online supplementary files 1–3 outline examples of questions in the three case studies, which were all ‘COMPASS’ questions for the qualitative evidence syntheses.

Types of integration and synthesis designs in mixed-method reviews

The shift towards integration of qualitative and quantitative evidence in primary research has, in recent years, begun to be mirrored within research synthesis. 29–31 The natural extension to undertaking quantitative or qualitative reviews has been the development of methods for integrating qualitative and quantitative evidence within reviews, and within the guideline process using evidence to decision-frameworks. Advocating the integration of quantitative and qualitative evidence assumes a complementarity between research methodologies, and a need for both types of evidence to inform policy and practice. Below, we briefly outline the current designs for integrating qualitative and quantitative evidence within a mixed-method review or synthesis.

One of the early approaches to integrating qualitative and quantitative evidence detailed by Sandelowski et al 32 advocated three basic review designs: segregated, integrated and contingent designs, which have been further developed by Heyvaert et al 33 ( box 3 ).

Segregated, integrated and contingent designs 32 33

Segregated design.

Conventional separate distinction between quantitative and qualitative approaches based on the assumption they are different entities and should be treated separately; can be distinguished from each other; their findings warrant separate analyses and syntheses. Ultimately, the separate synthesis results can themselves be synthesised.

Integrated design

The methodological differences between qualitative and quantitative studies are minimised as both are viewed as producing findings that can be readily synthesised into one another because they address the same research purposed and questions. Transformation involves either turning qualitative data into quantitative (quantitising) or quantitative findings are turned into qualitative (qualitising) to facilitate their integration.

Contingent design

Takes a cyclical approach to synthesis, with the findings from one synthesis informing the focus of the next synthesis, until all the research objectives have been addressed. Studies are not necessarily grouped and categorised as qualitative or quantitative.

A recent review of more than 400 systematic reviews 34 combining quantitative and qualitative evidence identified two main synthesis designs—convergent and sequential. In a convergent design, qualitative and quantitative evidence is collated and analysed in a parallel or complementary manner, whereas in a sequential synthesis, the collation and analysis of quantitative and qualitative evidence takes place in a sequence with one synthesis informing the other ( box 4 ). 6 These designs can be seen to build on the work of Sandelowski et al , 32 35 particularly in relation to the transformation of data from qualitative to quantitative (and vice versa) and the sequential synthesis design, with a cyclical approach to reviewing that evokes Sandelowski’s contingent design.

Convergent and sequential synthesis designs 34

Convergent synthesis design.

Qualitative and quantitative research is collected and analysed at the same time in a parallel or complementary manner. Integration can occur at three points:

a. Data-based convergent synthesis design

All included studies are analysed using the same methods and results presented together. As only one synthesis method is used, data transformation occurs (qualitised or quantised). Usually addressed one review question.

b. Results-based convergent synthesis design

Qualitative and quantitative data are analysed and presented separately but integrated using a further synthesis method; eg, narratively, tables, matrices or reanalysing evidence. The results of both syntheses are combined in a third synthesis. Usually addresses an overall review question with subquestions.

c. Parallel-results convergent synthesis design

Qualitative and quantitative data are analysed and presented separately with integration occurring in the interpretation of results in the discussion section. Usually addresses two or more complimentary review questions.

Sequential synthesis design

A two-phase approach, data collection and analysis of one type of evidence (eg, qualitative), occurs after and is informed by the collection and analysis of the other type (eg, quantitative). Usually addresses an overall question with subquestions with both syntheses complementing each other.

The three case studies ( table 1 , online supplementary files 1–3 ) illustrate the diverse combination of review designs and synthesis methods that were considered the most appropriate for specific guidelines.

Methods for conducting mixed-method reviews in the context of guidelines for complex interventions

In this section, we draw on examples where specific review designs and methods have been or can be used to explore selected aspects of complexity in guidelines or systematic reviews. We also identify other review methods that could potentially be used to explore aspects of complexity. Of particular note, we could not find any specific examples of systematic methods to synthesise highly diverse research designs as advocated by Petticrew et al 17 and summarised in tables 2 and 3 . For example, we could not find examples of methods to synthesise qualitative studies, case studies, quantitative longitudinal data, possibly historical data, effectiveness studies providing evidence of differential effects across different contexts, and system modelling studies (eg, agent-based modelling) to explore system adaptivity.

There are different ways that quantitative and qualitative evidence can be integrated into a review and then into a guideline development process. In practice, some methods enable integration of different types of evidence in a single synthesis, while in other methods, the single systematic review may include a series of stand-alone reviews or syntheses that are then combined in a cross-study synthesis. Table 1 provides an overview of the characteristics of different review designs and methods and guidance on their applicability for a guideline process. Designs and methods that have already been used in WHO guideline development are described in part A of the table. Part B outlines a design and method that can be used in a guideline process, and part C covers those that have the potential to integrate quantitative, qualitative and mixed-method evidence in a single review design (such as meta-narrative reviews and Bayesian syntheses), but their application in a guideline context has yet to be demonstrated.

Points of integration when integrating quantitative and qualitative evidence in guideline development

Depending on the review design (see boxes 3 and 4 ), integration can potentially take place at a review team and design level, and more commonly at several key points of the review or guideline process. The following sections outline potential points of integration and associated practical considerations when integrating quantitative and qualitative evidence in guideline development.

Review team level

In a guideline process, it is common for syntheses of quantitative and qualitative evidence to be done separately by different teams and then to integrate the evidence. A practical consideration relates to the organisation, composition and expertise of the review teams and ways of working. If the quantitative and qualitative reviews are being conducted separately and then brought together by the same team members, who are equally comfortable operating within both paradigms, then a consistent approach across both paradigms becomes possible. If, however, a team is being split between the quantitative and qualitative reviews, then the strengths of specialisation can be harnessed, for example, in quality assessment or synthesis. Optimally, at least one, if not more, of the team members should be involved in both quantitative and qualitative reviews to offer the possibility of making connexions throughout the review and not simply at re-agreed junctures. This mirrors O’Cathain’s conclusion that mixed-methods primary research tends to work only when there is a principal investigator who values and is able to oversee integration. 9 10 While the above decisions have been articulated in the context of two types of evidence, variously quantitative and qualitative, they equally apply when considering how to handle studies reporting a mixed-method study design, where data are usually disaggregated into quantitative and qualitative for the purposes of synthesis (see case study 3—risk communication in humanitarian disasters).

Question formulation

Clearly specified key question(s), derived from a scoping or consultation exercise, will make it clear if quantitative and qualitative evidence is required in a guideline development process and which aspects will be addressed by which types of evidence. For the remaining stages of the process, as documented below, a review team faces challenges as to whether to handle each type of evidence separately, regardless of whether sequentially or in parallel, with a view to joining the two products on completion or to attempt integration throughout the review process. In each case, the underlying choice is of efficiencies and potential comparability vs sensitivity to the underlying paradigm.

Once key questions are clearly defined, the guideline development group typically needs to consider whether to conduct a single sensitive search to address all potential subtopics (lumping) or whether to conduct specific searches for each subtopic (splitting). 36 A related consideration is whether to search separately for qualitative, quantitative and mixed-method evidence ‘streams’ or whether to conduct a single search and then identify specific study types at the subsequent sifting stage. These two considerations often mean a trade-off between a single search process involving very large numbers of records or a more protracted search process retrieving smaller numbers of records. Both approaches have advantages and choice may depend on the respective availability of resources for searching and sifting.

Screening and selecting studies

Closely related to decisions around searching are considerations relating to screening and selecting studies for inclusion in a systematic review. An important consideration here is whether the review team will screen records for all review types, regardless of their subsequent involvement (‘altruistic sifting’), or specialise in screening for the study type with which they are most familiar. The risk of missing relevant reports might be minimised by whole team screening for empirical reports in the first instance and then coding them for a specific quantitative, qualitative or mixed-methods report at a subsequent stage.

Assessment of methodological limitations in primary studies

Within a guideline process, review teams may be more limited in their choice of instruments to assess methodological limitations of primary studies as there are mandatory requirements to use the Cochrane risk of bias tool 37 to feed into Grading of Recommendations Assessment, Development and Evaluation (GRADE) 38 or to select from a small pool of qualitative appraisal instruments in order to apply GRADE; Confidence in the Evidence from Reviews of Qualitative Research (GRADE-CERQual) 39 to assess the overall certainty or confidence in findings. The Cochrane Qualitative and Implementation Methods Group has recently issued guidance on the selection of appraisal instruments and core assessment criteria. 40 The Mixed-Methods Appraisal Tool, which is currently undergoing further development, offers a single quality assessment instrument for quantitative, qualitative and mixed-methods studies. 41 Other options include using corresponding instruments from within the same ‘stable’, for example, using different Critical Appraisal Skills Programme instruments. 42 While using instruments developed by the same team or organisation may achieve a degree of epistemological consonance, benefits may come more from consistency of approach and reporting rather than from a shared view of quality. Alternatively, a more paradigm-sensitive approach would involve selecting the best instrument for each respective review while deferring challenges from later heterogeneity of reporting.

Data extraction

The way in which data and evidence are extracted from primary research studies for review will be influenced by the type of integrated synthesis being undertaken and the review purpose. Initially, decisions need to be made regarding the nature and type of data and evidence that are to be extracted from the included studies. Method-specific reporting guidelines 43 44 provide a good template as to what quantitative and qualitative data it is potentially possible to extract from different types of method-specific study reports, although in practice reporting quality varies. Online supplementary file 5 provides a hypothetical example of the different types of studies from which quantitative and qualitative evidence could potentially be extracted for synthesis.

The decisions around what data or evidence to extract will be guided by how ‘integrated’ the mixed-method review will be. For those reviews where the quantitative and qualitative findings of studies are synthesised separately and integrated at the point of findings (eg, segregated or contingent approaches or sequential synthesis design), separate data extraction approaches will likely be used.

Where integration occurs during the process of the review (eg, integrated approach or convergent synthesis design), an integrated approach to data extraction may be considered, depending on the purpose of the review. This may involve the use of a data extraction framework, the choice of which needs to be congruent with the approach to synthesis chosen for the review. 40 45 The integrative or theoretical framework may be decided on a priori if a pre-developed theoretical or conceptual framework is available in the literature. 27 The development of a framework may alternatively arise from the reading of the included studies, in relation to the purpose of the review, early in the process. The Cochrane Qualitative and Implementation Methods Group provide further guidance on extraction of qualitative data, including use of software. 40

Synthesis and integration

Relatively few synthesis methods start off being integrated from the beginning, and these methods have generally been subject to less testing and evaluation particularly in a guideline context (see table 1 ). A review design that started off being integrated from the beginning may be suitable for some guideline contexts (such as in case study 3—risk communication in humanitarian disasters—where there was little evidence of effect), but in general if there are sufficient trials then a separate systematic review and meta-analysis will be required for a guideline. Other papers in this series offer guidance on methods for synthesising quantitative 46 and qualitative evidence 14 in reviews that take a complexity perspective. Further guidance on integrating quantitative and qualitative evidence in a systematic review is provided by the Cochrane Qualitative and Implementation Methods Group. 19 27 29 40 47

Types of findings produced by specific methods

It is highly likely (unless there are well-designed process evaluations) that the primary studies may not themselves seek to address the complexity-related questions required for a guideline process. In which case, review authors will need to configure the available evidence and transform the evidence through the synthesis process to produce explanations, propositions and hypotheses (ie, findings) that were not obvious at primary study level. It is important that guideline commissioners, developers and review authors are aware that specific methods are intended to produce a type of finding with a specific purpose (such as developing new theory in the case of meta-ethnography). 48 Case study 1 (antenatal care guideline) provides an example of how a meta-ethnography was used to develop a new theory as an end product, 48 49 as well as framework synthesis which produced descriptive and explanatory findings that were more easily incorporated into the guideline process. 27 The definitions ( box 5 ) may be helpful when defining the different types of findings.

Different levels of findings

Descriptive findings —qualitative evidence-driven translated descriptive themes that do not move beyond the primary studies.

Explanatory findings —may either be at a descriptive or theoretical level. At the descriptive level, qualitative evidence is used to explain phenomena observed in quantitative results, such as why implementation failed in specific circumstances. At the theoretical level, the transformed and interpreted findings that go beyond the primary studies can be used to explain the descriptive findings. The latter description is generally the accepted definition in the wider qualitative community.

Hypothetical or theoretical finding —qualitative evidence-driven transformed themes (or lines of argument) that go beyond the primary studies. Although similar, Thomas and Harden 56 make a distinction in the purposes between two types of theoretical findings: analytical themes and the product of meta-ethnographies, third-order interpretations. 48

Analytical themes are a product of interrogating descriptive themes by placing the synthesis within an external theoretical framework (such as the review question and subquestions) and are considered more appropriate when a specific review question is being addressed (eg, in a guideline or to inform policy). 56

Third-order interpretations come from translating studies into one another while preserving the original context and are more appropriate when a body of literature is being explored in and of itself with broader or emergent review questions. 48

Bringing mixed-method evidence together in evidence to decision (EtD) frameworks

A critical element of guideline development is the formulation of recommendations by the Guideline Development Group, and EtD frameworks help to facilitate this process. 16 The EtD framework can also be used as a mechanism to integrate and display quantitative and qualitative evidence and findings mapped against the EtD framework domains with hyperlinks to more detailed evidence summaries from contributing reviews (see table 1 ). It is commonly the EtD framework that enables the findings of the separate quantitative and qualitative reviews to be brought together in a guideline process. Specific challenges when populating the DECIDE evidence to decision framework 15 were noted in case study 3 (risk communication in humanitarian disasters) as there was an absence of intervention effect data and the interventions to communicate public health risks were context specific and varied. These problems would not, however, have been addressed by substitution of the DECIDE framework with the new INTEGRATE 16 evidence to decision framework. A d ifferent type of EtD framework needs to be developed for reviews that do not include sufficient evidence of intervention effect.

Mixed-method review and synthesis methods are generally the least developed of all systematic review methods. It is acknowledged that methods for combining quantitative and qualitative evidence are generally poorly articulated. 29 50 There are however some fairly well-established methods for using qualitative evidence to explore aspects of complexity (such as contextual, implementation and outcome complexity), which can be combined with evidence of effect (see sections A and B of table 1 ). 14 There are good examples of systematic reviews that use these methods to combine quantitative and qualitative evidence, and examples of guideline recommendations that were informed by evidence from both quantitative and qualitative reviews (eg, case studies 1–3). With the exception of case study 3 (risk communication), the quantitative and qualitative reviews for these specific guidelines have been conducted separately, and the findings subsequently brought together in an EtD framework to inform recommendations.

Other mixed-method review designs have potential to contribute to understanding of complex interventions and to explore aspects of wider health systems complexity but have not been sufficiently developed and tested for this specific purpose, or used in a guideline process (section C of table 1 ). Some methods such as meta-narrative reviews also explore different questions to those usually asked in a guideline process. Methods for processing (eg, quality appraisal) and synthesising the highly diverse evidence suggested in tables 2 and 3 that are required to explore specific aspects of health systems complexity (such as system adaptivity) and to populate some sections of the INTEGRATE EtD framework remain underdeveloped or in need of development.

In addition to the required methodological development mentioned above, there is no GRADE approach 38 for assessing confidence in findings developed from combined quantitative and qualitative evidence. Another paper in this series outlines how to deal with complexity and grading different types of quantitative evidence, 51 and the GRADE CERQual approach for qualitative findings is described elsewhere, 39 but both these approaches are applied to method-specific and not mixed-method findings. An unofficial adaptation of GRADE was used in the risk communication guideline that reported mixed-method findings. Nor is there a reporting guideline for mixed-method reviews, 47 and for now reports will need to conform to the relevant reporting requirements of the respective method-specific guideline. There is a need to further adapt and test DECIDE, 15 WHO-INTEGRATE 16 and other types of evidence to decision frameworks to accommodate evidence from mixed-method syntheses which do not set out to determine the statistical effects of interventions and in circumstances where there are no trials.

When conducting quantitative and qualitative reviews that will subsequently be combined, there are specific considerations for managing and integrating the different types of evidence throughout the review process. We have summarised different options for combining qualitative and quantitative evidence in mixed-method syntheses that guideline developers and systematic reviewers can choose from, as well as outlining the opportunities to integrate evidence at different stages of the review and guideline development process.

Review commissioners, authors and guideline developers generally have less experience of combining qualitative and evidence in mixed-methods reviews. In particular, there is a relatively small group of reviewers who are skilled at undertaking fully integrated mixed-method reviews. Commissioning additional qualitative and mixed-method reviews creates an additional cost. Large complex mixed-method reviews generally take more time to complete. Careful consideration needs to be given as to which guidelines would benefit most from additional qualitative and mixed-method syntheses. More training is required to develop capacity and there is a need to develop processes for preparing the guideline panel to consider and use mixed-method evidence in their decision-making.

This paper has presented how qualitative and quantitative evidence, combined in mixed-method reviews, can help understand aspects of complex interventions and the systems within which they are implemented. There are further opportunities to use these methods, and to further develop the methods, to look more widely at additional aspects of complexity. There is a range of review designs and synthesis methods to choose from depending on the question being asked or the questions that may emerge during the conduct of the synthesis. Additional methods need to be developed (or existing methods further adapted) in order to synthesise the full range of diverse evidence that is desirable to explore the complexity-related questions when complex interventions are implemented into health systems. We encourage review commissioners and authors, and guideline developers to consider using mixed-methods reviews and synthesis in guidelines and to report on their usefulness in the guideline development process.

Handling editor: Soumyadeep Bhaumik

Contributors: JN, AB, GM, KF, ÖT and ES drafted the manuscript. All authors contributed to paper development and writing and agreed the final manuscript. Anayda Portela and Susan Norris from WHO managed the series. Helen Smith was series Editor. We thank all those who provided feedback on various iterations.

Funding: Funding provided by the World Health Organization Department of Maternal, Newborn, Child and Adolescent Health through grants received from the United States Agency for International Development and the Norwegian Agency for Development Cooperation.

Disclaimer: ÖT is a staff member of WHO. The author alone is responsible for the views expressed in this publication and they do not necessarily represent the decisions or policies of WHO.

Competing interests: No financial interests declared. JN, AB and ÖT have an intellectual interest in GRADE CERQual; and JN has an intellectual interest in the iCAT_SR tool.

Patient consent: Not required.

Provenance and peer review: Not commissioned; externally peer reviewed.

Data sharing statement: No additional data are available.

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