Prevalencia del síndrome de burnout en médicos que trabajan en España: revisión sistemática y metaanálisis
Bibliographic record
Abstract
Analizar la prevalencia del síndrome de desgaste profesional o burnout en médicos que trabajan en España mediante una revisión sistemática con metaanálisis. Se realizaron búsquedas en PubMed/MEDLINE, Embase y PsycINFO (hasta junio de 2023). Se incluyeron estudios observacionales realizados en España que presentaran la prevalencia de burnout en médicos. De cada estudio se extrajeron las características metodológicas y los resultados, y se evaluó su calidad. Se realizó una síntesis narrativa con metaanálisis de efectos aleatorios para el cálculo de proporciones. Se incluyeron 67 estudios con 16.076 participantes. Para la variable principal, el metaanálisis reveló una prevalencia global de burnout en médicos del 24% (IC95%: 19%-29%; 46 estudios; 8821 participantes; I2 = 97%). A partir de análisis de subgrupos se observaron diferencias según el criterio diagnóstico utilizado: prevalencia del 18% (IC95%: 13%-23%) utilizando tres dimensiones de burnout, 29% (IC95%: 24%-34%) para dos dimensiones y 51% (IC95%: 42%-60%) para una dimensión. La heterogeneidad entre estudios no pudo ser explicada por completo a través de análisis adicionales, y no se encontraron diferencias estadísticamente significativas con otras variables (p. ej., calidad de los estudios, ámbito de trabajo, categoría profesional o por especialidad médica). Se aprecia una alta prevalencia del síndrome de burnout en médicos que trabajan en España. Estos resultados pueden contribuir a conocer mejor la carga asociada al burnout en médicos y al diseño de futuros estudios. Parecen ser necesarias estrategias para prevenir y mitigar esta situación. Open Science Framework: https://osf.io/b2h4m/ To analyze the prevalence of burnout syndrome in physicians working in Spain through a systematic review with meta-analysis We searched PubMed/MEDLINE, Embase, and PsycINFO (up to June 2023). Observational studies conducted in Spain reporting the prevalence of burnout in physicians were included. From each study, methodological characteristics and results were extracted, and their quality was evaluated. We performed a narrative synthesis with random effects meta-analysis to calculate proportions. Sixty-seven studies with 16,076 participants were included. For the primary outcome, the meta-analysis revealed a global prevalence of burnout in physicians of 24% (95%CI: 19%-29%; 46 studies; 8821 participants; I2 = 97%). From subgroup analysis, differences were observed depending on the diagnostic criteria used: 18% (95%CI: 13%-23%) for three dimensions of burnout, 29% (95%CI: 24%-34%) for two dimensions and 51% (95%CI: 42%-60%) for one dimension. The heterogeneity between studies could not be fully explained through additional analyses where non-statistically significant differences were found with other variables (e.g., study quality, setting, professional category or medical specialty). A high prevalence of burnout syndrome was found in physicians working in Spain. These results can contribute to estimating the burden associated with burnout in physicians at a national level and to the design of future studies. Strategies appear to be necessary to prevent and mitigate this situation. Open Science Framework: https://osf.io/b2h4m/
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.082 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.025 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".