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Holistic Assessment of Factors Associated with Exhaustion, the Main Symptom of Burnout: A Meta-Analysis of Longitudinal Studies

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  • Yara Shoman

    (Center of Primary Care and Public Health (Unisanté), University of Lausanne, 1066 Epalinges-Lausanne, Switzerland)

  • Valentin Rousson

    (Center of Primary Care and Public Health (Unisanté), University of Lausanne, 1066 Epalinges-Lausanne, Switzerland)

  • Renzo Bianchi

    (Department of Psychology, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway)

  • Irina Guseva Canu

    (Center of Primary Care and Public Health (Unisanté), University of Lausanne, 1066 Epalinges-Lausanne, Switzerland)

Abstract

Background: This meta-analysis summarized longitudinal findings pertaining to exhaustion’s predictors. In so doing, our aim was ultimately to identify target factors for the prevention of burnout. Methods: We searched for studies that (a) examined predictors of exhaustion longitudinally and (b) reported correlation coefficients as an effect estimate. We conducted our literature search in three databases: MEDLINE, PsycINFO, and Embase. We focused on studies published between January 1990 and November 2020. Predictors were grouped into families, subfamilies, and subgroups. A meta-analysis of z-transformed correlation coefficients (rho) was performed. The results were scrutinized in relation to studies’ follow-up length. Results: We included 65 studies assessing 242 predictors of different types captured across different occupations. Our findings highlighted mostly weak associations (rho < 0.30). For six predictors—Job control, Job resources, Interactions at work, Communication and leadership, Job attitudes, and Work-family interface—longer length of follow-up involved weaker associations with exhaustion. The quality of the evidence available was generally low. Conclusions: The evidence available does not point to clear target factors for preventing burnout. The decrease in associations as the follow-up length increases may suggest a relatively short latency period, followed by recovery. Higher-quality cohorts should be conducted to better understand the etiology and course of burnout.

Suggested Citation

  • Yara Shoman & Valentin Rousson & Renzo Bianchi & Irina Guseva Canu, 2022. "Holistic Assessment of Factors Associated with Exhaustion, the Main Symptom of Burnout: A Meta-Analysis of Longitudinal Studies," IJERPH, MDPI, vol. 19(20), pages 1-21, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13037-:d:938856
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    References listed on IDEAS

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    1. Sabine Kaiser & Joshua Patras & Frode Adolfsen & Astrid M. Richardsen & Monica Martinussen, 2020. "Using the Job Demands–Resources Model to Evaluate Work-Related Outcomes Among Norwegian Health Care Workers," SAGE Open, , vol. 10(3), pages 21582440209, July.
    2. Olaf M Dekkers & Jan P Vandenbroucke & Myriam Cevallos & Andrew G Renehan & Douglas G Altman & Matthias Egger, 2019. "COSMOS-E: Guidance on conducting systematic reviews and meta-analyses of observational studies of etiology," PLOS Medicine, Public Library of Science, vol. 16(2), pages 1-24, February.
    3. Yu‐fang Guo & Yuan‐hui Luo & Louisa Lam & Wendy Cross & Virginia Plummer & Jing‐ping Zhang, 2018. "Burnout and its association with resilience in nurses: A cross‐sectional study," Journal of Clinical Nursing, John Wiley & Sons, vol. 27(1-2), pages 441-449, January.
    4. Yara Shoman & Emna El May & Sandy Carla Marca & Pascal Wild & Renzo Bianchi & Merete Drevvatne Bugge & Cigdem Caglayan & Dimitru Cheptea & Marco Gnesi & Lode Godderis & Sibel Kiran & Damien M. McElven, 2021. "Predictors of Occupational Burnout: A Systematic Review," IJERPH, MDPI, vol. 18(17), pages 1-17, August.
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