Interventions to reduce occupational burnout in general practitioners: a systematic review and meta-analysis protocol

Background: 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. Methods: 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. Systematic review registration: PROSPERO, Identifier CRD420251064119.

Authors

Institutions

Publication Details

Journal
Frontiers in Public Health
Published
2026-03-31
DOI
https://doi.org/10.3389/fpubh.2026.1748369
Primary Topic
Healthcare professionals’ stress and burnout
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Interventions to reduce occupational burnout in general practitioners: a systematic review and meta-analysis protocol

Wei Xi, Shanping Chen, Yanting Chen, Junxian Li et al.
Frontiers in Public Health
Healthcare professionals’ stress and burnout
article

Interventions to reduce occupational burnout in general practitioners: a systematic review and meta-analysis protocol

Wei Xi, Shanping Chen, Yanting Chen, Junxian Li, Zihao Zhang, Xiaolong Shuai, Chuan Zou, Peisheng Xia, Zhonghan Li
article en

Abstract

Background: 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. Methods: 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. Systematic review registration: PROSPERO, Identifier CRD420251064119.

Frontiers in Public HealthVol. 14
West China Medical Center of Sichuan University (CN), Health First (US), Chengdu Fifth People's Hospital (CN), Chengdu University of Traditional Chinese Medicine (CN)
Chengdu University of Traditional Chinese Medicine, Chengdu University
Openalex Percentile: Top 28%
Healthcare professionals’ stress and burnout
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.