Associated factors of Burnout Syndrome in Peruvian health professionals before Covid 19 pandemic: A systematic review
Bibliographic record
Abstract
Introduction: The Burnout Syndrome (BS) constitutes a prevalent occupational health problem in the group of health professionals. Objective: To describe the prevalence and factors associated with BS in Peruvian health professionals. Method: A systematic review and meta-analysis of the literature were accomplished. Key terms were used: "burnout", "professional exhaustion", with words related to Peru. The databases consulted were LILACS/ Virtual health library, Medline/PubMed, Science Direct, EBSCO, Scopus, SciELO, and RENATI-SUNEDU, published from 2000 to 2020. The methodological quality assessment was accomplished using the Newcastle Ottawa instrument. Results: 33 studies were identified (11 scientific articles and 22 graduate theses), the median of the participants included in each study was 76 (IQR: 47-106). The median total score was 55.8 points (IQR: 44-61). The meta-analysis identified the global prevalence of moderate BS by subgroups of regions of Peru, it was 53% (95% CI: 36% to 70%); by profession 54% (95% CI: 28% to 79%); by general areas 61% (95% CI: 39% to 70%) and emergency 40% (95% CI: 18% to 64%). Most of the factors associated with BS are related to work (work environment, dysfunctional group behavior, time of service, satisfaction, and workload); and sociodemographic (age, sex, and profession). Conclusions: The BS and its three dimensions are more frequently associated with work, sociodemographic and individual factors. SB and the dimensions of emotional exhaustion and depersonalization are associated with factors outside of work. It is the first systematic review of the subject in Peru, being useful to generate proposals for public policies in occupational health and health intervention programs.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".