Post-traumatic Stress Disorder in Resident Physicians
Bibliographic record
Abstract
Background Research suggests that symptoms of post-traumatic stress disorder (PTSD) may be common in physicians who have experienced a traumatic event, but it is unclear if medical residents suffer from similar symptoms. Objective To determine the prevalence of PTSD symptoms in the resident physician population of the University of British Columbia based on the new Diagnostic and Statistical Manual of Mental Disorders-fifth edition (DSM-5) criteria. Method A link to an online questionnaire containing 27 questions, including residency training and year, as well as the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-fifth edition (PCL-5) was e-mailed and completed by the resident physicians of the University of British Columbia. Results Forty-three residents completed the survey and 38 had complete data. Mean PCL-5 score was 10.3 for the 38 subjects. Differences between PCL-5 score and resident year yielded the following: postgraduate year (PGY)-1=8.6; PGY-2=16.5; PGY-3=3.6; PGY-4=4.0; PGY-5=7.7. With respect to the type of traumatic event and PCL-5 score, the following was observed: Death=5.3, Violence=13.8, Medical Error=8.0, Bullying=38.0, None=45.0. The Kruskal-Wallis test showed no statistically significant differences in total PCL-5 score for PGY or type of traumatic event. Regardless of post-graduate year or trauma experience, four subjects out of 38 (10.5%) had a total PCL-5 score of 33 or greater, while one subject (2.5%) had a score greater than 50. Conclusion The results from this study conclude that resident physicians do suffer from PTSD symptoms at a rate higher than the average American population. As PTSD symptoms can often be very distressing and potentially affect work ethic negatively, further studies are indicated to better understand these symptoms and hopefully lead to better care in treating PTSD symptoms in resident physicians.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".