Prevalence of burnout among nurses in Iran: a systematic review and meta‐analysis
Bibliographic record
Abstract
AIM: This study aimed to summarize the available information in the literature to make an accurate estimate of the prevalence of burnout among Iranian nurses. BACKGROUND AND INTRODUCTION: Burnout is a work-related stress syndrome that has negative impact on healthcare providers, patients and healthcare delivery systems. METHOD: A comprehensive search of literature using international [PubMed, Scopus and the Institute for Scientific Information (ISI)] and Iranian scientific data bases [Scientific Information Database (SID), IranMedex and Magiran] was conducted to identify English and Persian language studies, published between 2000 and 2016, that examined the prevalence of burnout among nurses in Iran. The I-squared test and Chi-squared-based Q-test suggested heterogeneity of reported prevalence among the qualified studies; thus, a random-effects model was applied to estimate the overall prevalence of burnout among nurses in Iran. RESULTS: Based on 21 selected articles with 4180 participants, the overall prevalence of burnout among Iranian nurses was estimated to be 36% [95% confidence interval (CI), 20-53%] in Iran. Meta-regression indicated that sample size and year of data collection, mean age of samples, female to male ratio and geographic regions were not statistically significantly associated with the prevalence of burnout. Also, based on Egger's test and funnel plot, there is no publication bias among studies included in the analysis. CONCLUSION: Professional burnout affects more than one-third of nursing staff in Iran; thus, effective interventions and strategies are required to reduce and prevent burnout among nurses. IMPLICATION FOR NURSING AND HEALTH POLICY: Due to the negative consequences of burnout on patients, nurses and organizations, nursing and healthcare managers should intervene to prevent and reduce burnout among nurses in Iran. Policy attention should focus on developing effective interventions to prevent and minimize the burden of burnout among nurses in Iran. Nurses' involvement in the policy-making process is crucial in the implementation of effective programs and initiatives tailored to address the higher prevalence of burnout among Iranian nurses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".