Abstract

In their meta-analysis of observational studies, Low et al. showed a high prevalence of burnout syndrome (BOS) among medical and surgical residents across the globe with an aggregate prevalence of burnout as 51.0% (CI: 45.0–57%). However, the sample size in many of the included studies was quite low (only 26 out of 47 included studies had a sample size of more than 100 participants), and almost all of the 47 studies reported a rate of respondents of less than 80% (43 out of 47, 91.4%). Furthermore, in many of them, the rate of respondents was unknown (5 out of 47) or less than 50% of eligible persons (23 out of 47 studies). As BOS is a self-reported syndrome, healthcare professionals who decided to participate in those studies were many of those affected by BOS, making the percentage of respondents potentially overstated due to the nonresponse bias. Policy decision-making in public health relies on evidence-based research; therefore, quality evaluation of studies in meta-analysis is essential to draw useful data for policymakers.

Highlights

  • Policy decision-making in public health relies on evidence-based research

  • The meta-analysis [5] of observational cohort and cross-sectional studies carried out by Low et al, reporting the prevalence of burnout syndrome measured with the Maslach Burnout Inventory among medical residents, is absolutely valuable as an effort to fill a deep gap of knowledge in an occupational sector where costs and consequences of burnout syndrome may be very relevant, as the quality of cure delivered by healthcare professionals may be compromised [6,7]

  • In every systematic review and meta-analysis, the quality evaluation of included studies is essential to drawing useful data to be translated by policymakers into public health decisions

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Summary

Introduction

Policy decision-making in public health relies on evidence-based research. Systematic reviews and meta-analyses on prevalence of burnout syndrome in physicians often lead to contradictory results given the difficulty of defining and measuring with precision this puzzling syndrome.

Results
Conclusion
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