Interventions to reduce occupational burnout in general practitioners: a systematic review and meta-analysis protocol.
General practitioners (GPs) are at high risk of burnout, which threatens physicians' mental health, care quality, and the sustainability of primary health care systems. Although a growing number of interventions have been developed to prevent or reduce burnout among GPs, their effectiveness and the mechanisms through which they work remain unclear.
We will conduct a systematic review and meta-analysis of interventions aimed at preventing or reducing burnout in GPs, following the Cochrane Handbook and the PRISMA 2020 statement. Randomized controlled trials, cluster-randomized trials, and non-randomized controlled studies evaluating individual-, group-, organisational-, or system-level interventions will be eligible. We will search PubMed (MEDLINE), Embase (Elsevier), Web of Science Core Collection, CNKI, Wanfang Data, and VIP (Weipu) and other databases from inception, without language restrictions. Two reviewers will independently screen studies, extract data and assess risk of bias using the revised Cochrane risk-of-bias tool (RoB 2) and the ROBINS-I tool. Where appropriate, we will pool effect sizes for overall burnout and its dimensions using random-effects models, and explore heterogeneity and subgroup effects based on the job demands-resources model. When meta-analysis is not feasible, we will provide a narrative synthesis. Certainty of the evidence will be assessed with GRADE.
PROSPERO, Identifier CRD420251064119.
We will conduct a systematic review and meta-analysis of interventions aimed at preventing or reducing burnout in GPs, following the Cochrane Handbook and the PRISMA 2020 statement. Randomized controlled trials, cluster-randomized trials, and non-randomized controlled studies evaluating individual-, group-, organisational-, or system-level interventions will be eligible. We will search PubMed (MEDLINE), Embase (Elsevier), Web of Science Core Collection, CNKI, Wanfang Data, and VIP (Weipu) and other databases from inception, without language restrictions. Two reviewers will independently screen studies, extract data and assess risk of bias using the revised Cochrane risk-of-bias tool (RoB 2) and the ROBINS-I tool. Where appropriate, we will pool effect sizes for overall burnout and its dimensions using random-effects models, and explore heterogeneity and subgroup effects based on the job demands-resources model. When meta-analysis is not feasible, we will provide a narrative synthesis. Certainty of the evidence will be assessed with GRADE.
PROSPERO, Identifier CRD420251064119.
Authors
Xi Xi, Li Li, Chen Chen, Xia Xia, Zhang Zhang, Chen Chen, Li Li, Shuai Shuai, Zou Zou
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