Incidence and characteristics of needlestick injuries among medical trainees at a community teaching hospital: A cross-sectional study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: This field study aimed to determine the incidence and distribution of needlestick injuries among medical trainees at a community teaching hospital in Toronto, Canada. METHODS: The study was performed during the 2013-2015 academic years at Toronto East General Hospital (TEGH), a University of Toronto-affiliated community-teaching hospital during the 2013-2015 academic years. Eight-hundred and forty trainees, including medical students, residents, and post-graduate fellows, were identified and invited via email to participate in an anonymous online fluidsurveys.com survey of 16 qualitative and quantitative questions. RESULTS: Three-hundred and fifty trainees responded (42% response rate). Eighty-eight (25%) respondents reported experiencing at least one injury at TEGH. In total, our survey identified 195 total injuries. Surgical trainees were significantly more likely to incur injuries than non-surgical trainees (IRR = 3.03, 95% CI 1.80-5.10). Orthopaedic surgery trainees had the highest risk of a needlestick injury, being over 12 times more likely to be injured than emergency medicine trainees (IRR = 12.4, 95% CI 2.11-72.32). Only 28 of the 88 most recent needlestick injuries were reported to occupational health. Trainees reported a perception of insignificant risk, lack of resources and support for reporting, and injury stigmatization as reasons for not reporting needlestick injuries. CONCLUSIONS: Needlestick injuries were a common underreported risk to medical trainees at TEGH. Future research should investigate strategies to reduce injury and improve reporting among the high-risk and reporting-averse trainees.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it