Applying the demand–control–support model on burnout in students: A meta‐analysis

Kim, Soyeon; Kim, Hankyul; Park, Eun Hye; Kim, Boram; Lee, Sang Min; Kim, Boyoung

doi:10.1002/pits.22581

Cited by 16 publications

(15 citation statements)

References 103 publications

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“…Lastly, putting these results in perspective, we can consider the few statistically significant effects (positive relationship with community support and negative relationship with colleagues' support) as suggestive rather than solid evidence. In the study by Kim et al [100], fourteen empirical studies on burnout in students were reviewed and support was found to be negatively associated with all three burnout dimensions. Similarly, a systematic review of the work environment and burnout, not confined to any specific occupational group, showed moderately strong evidence of a relationship between low workplace support and increased emotional exhaustion [101].…”

Section: Interpretation Of Findingsmentioning

confidence: 99%

Determinants of Burnout among Teachers: A Systematic Review of Longitudinal Studies

Mijakoski

Cheptea

Marca

et al. 2022

IJERPH

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We aimed to review the determinants of burnout onset in teachers. The study was conducted according to the PROSPERO protocol CRD42018105901, with a focus on teachers. We performed a literature search from 1990 to 2021 in three databases: MEDLINE, PsycINFO, and Embase. We included longitudinal studies assessing burnout as a dependent variable, with a sample of at least 50 teachers. We summarized studies by the types of determinant and used the MEVORECH tool for a risk of bias assessment (RBA). The quantitative synthesis focused on emotional exhaustion. We standardized the reported regression coefficients and their standard errors and plotted them using R software to distinguish between detrimental and protective determinants. A qualitative analysis of the included studies (n = 33) identified 61 burnout determinants. The RBA showed that most studies had external and internal validity issues. Most studies implemented two waves (W) of data collection with 6–12 months between W1 and W2. Four types of determinants were summarized quantitatively, namely support, conflict, organizational context, and individual characteristics, based on six studies. This systematic review identified detrimental determinants of teacher exhaustion, including job satisfaction, work climate or pressure, teacher self-efficacy, neuroticism, perceived collective exhaustion, and classroom disruption. We recommend that authors consider using harmonized methods and protocols such as those developed in OMEGA-NET and other research consortia

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Section: Interpretation Of Findingsmentioning

confidence: 99%

Determinants of Burnout among Teachers: A Systematic Review of Longitudinal Studies

Mijakoski

Cheptea

Marca

et al. 2022

IJERPH

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“…Lee and Ashforth ( 73 ) believed that compared with cynicism and inefficacy in job burnout, emotional exhaustion has a higher correlation with demands (including time pressure as an indicator) and resource variables. More recently, Kim et al ( 33 ) found a positive correlation between study demands and emotional exhaustion in the school setting through a meta-analysis. Similar findings show a significant positive correlation between study demands and emotional exhaustion among high school students ( 34 ) and college students ( 20 ).…”

Section: Discussionmentioning

confidence: 99%

“…As one of the study resources, perceived social support has been widely discussed in a variety of studies ( 20 , 26 – 28 ). Many studies show that social support is negatively correlated with student burnout ( 27 , 33 , 48 ). Social support from school or teachers, parents, and peers is negatively correlated with student burnout ( 27 , 45 – 47 ); that is probably because social support has a promotive effect on reducing student emotional exhaustion ( 48 ).…”

Section: Discussionmentioning

confidence: 99%

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First-Year College Students' Mental Health in the Post-COVID-19 Era in Guangxi, China: A Study Demands-Resources Model Perspective

Wei

et al. 2022

Front. Public Health

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The post-COVID-19 era means that the COVID-19 is basically under control; however, the risk of the pandemic still affects people's work, study, and life, physically and psychologically. In this era, due to the more challenges first-year college students face, more attention should be paid to their mental health. An emerging study demands-resources (SD-R) model can explain the influencing mechanism of college students' mental health. This model suggests that study demands increase the risk of student burnout, which results in mental health problems; meanwhile, study resources reduce student burnout and increase student engagement, thus improving mental health. Based on the SD-R model, this study explores the impacts of time pressure, emotional exhaustion, perceived social support, and student engagement on mental health and provides adequate measures to reduce the risk of mental health problems among first-year students. Time pressure, perceived social support, emotional exhaustion, student engagement, and mental health scales were used to investigate 537 first-year students at three universities in Guangxi, China, of whom 290 (54%) were female, and 247 (46%) were male, and the average age was 18.97 ± 1.01. Results indicated that: (1) Moderate scores on time pressure and emotional exhaustion and slightly-above-the-median scores on perceived social support, student engagement, and mental health were found among first-year students in the post-COVID-19 era. (2) Time pressure had a positive relationship with emotional exhaustion and a negative relationship with mental health. (3) Perceived social support was negatively correlated with emotional exhaustion but positively correlated with student engagement, and thus improved mental health. Results of this study with a sample of first-year college students in China support the hypotheses based on the SD-R model. These findings suggest that increasing perceived social support and student engagement while decreasing time pressure and emotional exhaustion may promote mental health among first-year college students.

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“…Academic burnout has three main manifestations, namely exhaustion due to the demands of learning (emotional exhaustion), a cynical or transcendental attitude toward one’s own learning (depersonalization), and a sense of incompetence and difficulty in generating satisfaction as a student [ 42 ] as well as a negative evaluation of the educational environment (low personal achievement) [ 43 ]. The main characteristic of burnout is a combination of exhaustion (low activation) and cynicism (low identity), while the opposite of academic dedication is characterized by vitality (high activation) and dedication (high identity) [ 44 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Classroom Digital Teaching and College Students’ Academic Burnout in the Post COVID-19 Era: A Cross-Sectional Study

Song

Wang

Zhang

2022

IJERPH

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The continued development of digital technology and its overuse in teaching and learning in the post-epidemic era have brought about digital health risks, which are associated with academic burnout among college students. This study focused on the relationship between classroom digital teaching and students’ academic burnout and designed the Classroom Burnout Inventory (CBI) and the Classroom Burnout Causes Inventory (CBCI) to conduct a cross-sectional survey of 206 Chinese university students. Correlations and regression analyses were conducted between key factors and burnout values through a path model of “Digital teaching-Teaching & learning process-Causes subjects-Burnout”. The results of the study show that an inappropriate and excessive use of unintegrated digital teaching and learning technologies in the classroom was positively correlated with academic burnout among college students. Burnout levels and the three manifestations were not correlated with students’ gender, grade, and major. In terms of causes, the academic burnout of college students was more correlated with their own personal reasons than with external factors such as teachers, universities, and environments. Integrating digital technology platforms, enhancing teacher leadership in the digital classroom, and strengthening peer support and students’ psychological resilience are all meaningful explorations of academic burnout prevention strategies.

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Applying the demand–control–support model on burnout in students: A meta‐analysis

Cited by 16 publications

References 103 publications

Determinants of Burnout among Teachers: A Systematic Review of Longitudinal Studies

Determinants of Burnout among Teachers: A Systematic Review of Longitudinal Studies

First-Year College Students' Mental Health in the Post-COVID-19 Era in Guangxi, China: A Study Demands-Resources Model Perspective

Classroom Digital Teaching and College Students’ Academic Burnout in the Post COVID-19 Era: A Cross-Sectional Study

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