Period Prevalence and Reporting Rate of Needlestick Injuries to Nurses in Iran: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
The purpose of this systematic review and meta-analysis was to provide a precise estimate of the period prevalence of needlestick injuries (NSI) among nurses working in hospitals in Iran and the reporting rate of NSI to nurse managers. We searched both international (PubMed, Scopus and the Institute for Scientific Information) and Iranian (Scientific Information Database, Iranmedex and Magiran) scientific databases to find studies published from 2000 to 2016 of NSI among Iranian nurses. The following keywords in Persian and English were used: "needle-stick" or "needle stick" or "needlestick," with and without "injury" or "injuries," "prevalence" or "frequency," "nurses" or "nursing staff," and "Iran." In a sample of 21 articles with 6,480 participants, we estimated that the overall 1-year period prevalence of NSI was 44% (95% confidence interval [CI], 35-53%) among Iranian nurses. The overall 1-year period prevalence of reporting NSI to nurse managers was 42% (95% CI, 33-52%). In meta-regression analysis, sample size, mean age, years of experience, and gender ratio were not associated with prevalence of NSI or reporting rate. The year of data collection was positively associated with period prevalence of NSI (p < .05), but not with the period prevalence of reporting NSI to nurse managers. Results indicated a high NSI period prevalence and low NSI reporting rate among nurses in Iran. Thus, effective interventions are required in hospitals in Iran to reduce the prevalence and increase the reporting rate of NSI. © 2017 Wiley Periodicals, Inc.
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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 | 0.029 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".