Systematic Review and Meta-Analysis of Randomized Trials Testing Interventions to Reduce Physician Burnout
Open accessAbstract
Background Physicians deal with intense professional pressures, which may contribute to increasing burnout. We sought to evaluate the efficacy of interventions designed to reduce burnout in physicians, physicians-in-training, and other health care professionals. Methods We searched PubMed and Embase (through January 6, 2023) and reference lists. We included all randomized studies assessing an intervention designed to reduce professional burnout in physicians and other health care personnel. We adhered to the PRISMA reporting guidelines. We abstracted data on study and participant characteristics, study outcomes, and study quality. We used a random-effects model to pool mean differences in burnout change (pre- and post-intervention) between intervention and control arms. Results Thirty-one of the 38 eligible studies (81.6%) used the Maslach Burnout Inventory (MBI) questionnaire to assess burnout. When comparing the intervention and control groups, the mean difference in the emotional exhaustion component of the MBI was -1.11 (95% confidence interval [CI], -2.14 to -0.09; I2: 74.5%; 20 studies); the mean difference in the depersonalization component of the MBI was -0.32 (95% CI, -0.63 to -0.01; I2: 54.2%; 17 studies); and the mean difference in the personal accomplishment component of the MBI was 1.11 (95% CI, -0.21 to 2.43; I2: 94.3%; 16 studies). Conclusions Studies testing interventions to decrease physician burnout led to significant numerical improvements in some domains of burnout, but it is unlikely that these changes result in meaningful changes in clinical burnout. Further, the limited follow-up time, biased assessments, and heterogeneity in intervention efficacy suggest that a more nuanced understanding of the causes of burnout is needed to develop more effective interventions.
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The magnitude of change was similar to effects reported in prior reviews of physicians and mixed clinician samples.
“The magnitude of change was similar to effects reported in prior reviews of physicians and mixed clinician samples [11,14,19].”
From Individual-Focused Interventions for Physician Burnout: A Meta-Analysis of Mindfulness, Coaching, and Peer Support (2025) · cites this paper as [19]
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- Authors
- Haslam, A., Tuia, J., Miller, S. L., & Prasad, V.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Haslam, Alyson
- Venue
- The American Journal of Medicine
- Publisher
- Elsevier BV
- Published
- 2024-03
- Volume
- 137
- Issue
- 3
- Pages
- 249-257.e1
- ISSN
- 0002-9343 (ISSN-L)
- OpenAlex
- W4387996281
- Cited by
- 40
- References
- 54
- Citations by year
- 2026: 8 · 2025: 23 · 2024: 9
- FWCI
- 2.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- University of California San Francisco
- Arnold Ventures
- Topics
- Health Sciences › Health Professions › General Health Professions › Healthcare professionals’ stress and burnout
- Health Sciences › Health Professions › Occupational Therapy › Occupational Health and Burnout
- Social Sciences › Psychology › Social Psychology › Stress and Burnout Research
- Keywords
- physician burnout, burnout intervention, emotional exhaustion, depersonalization, personal accomplishment, Maslach Burnout Inventory, healthcare workers, intervention efficacy
- MeSH terms
- Burnout, Professional, Humans, Physicians, Psychological Tests, Surveys and Questionnaires, Randomized Controlled Trials as Topic, Self Report
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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