PREVALENCE OF DEPRESSION, STRESS AND ANXIETY IN NURSES OF INTENSIVE CARE UNITS IN IRANIAN HOSPITALS: A SYSTEMATIC REVIEW, META-ANALYSIS AND META-REGRESSION
Bibliographic record
Abstract
Background & Aims Nurses in intensive care units face unique challenges that can have serious effects on their mental health and job performance, leading to depression, stress, and anxiety.This study was conducted to determine the prevalence of depression, stress, and anxiety among nurses in critical care units in Iranian hospitals through a systematic review and meta-analysis.Materials & Methods: An electronic search was conducted in PubMed, Scopus, Web of Science, ScienceDirect, Scientific Information Database, and Magiran until June 2024.A manual search was also conducted in key review articles and primary sources.The studies were limited to Persian and English languages.Study bias was evaluated using the Newcastle-Ottawa Scale checklist, and data analysis was carried out using Comprehensive Meta-Analysis software version 3. Results: A total of 18 observational studies involving 2,611 nurses were included in the study.The results of the meta-analysis indicated that the prevalence of depression, stress, and anxiety among ICU nurses was 28% (95% confidence interval [CI] 0.14-0.47,P=0.03), 68% (95% CI 0.53-0.80,P=0.01), and 53% (95% CI 0.29-0.76,P=0.76), respectively.There was no significant relationship between the prevalence of stress and the year of publication of the study (P>0.05).Publication bias was not observed in the study. Conclusion:Intensive care unit nurses experience depression, stress, and anxiety.Therefore, implementing effective measures to identify and alleviate these issues among nurses can enhance their well-being and positively impact the quality of patient care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".