Effect of colleague and coworker abuse on family physicians in Canada.
Bibliographic record
Abstract
OBJECTIVE: To assess the effects of physician-colleague and coworker abuse on family physicians in Canada. DESIGN: A mixed-methods, bilingual study that included surveys and telephone interviews. SETTING: Canada. PARTICIPANTS: Family physicians in active practice who were members of the College of Family Physicians of Canada in 2009. METHODS: Surveys were mailed to a random sample of family physicians (N = 3802), and 37 family physicians who had been abused in the past year participated in telephone interviews. MAIN FINDINGS: A total of 770 surveys (20%) were completed. A small number of respondents reported having been subjected to abuse by physician colleagues (9%) or coworkers (6%) in the previous month. Many of the respondents reported that the same physician colleagues or coworkers were repeat abusers. More than three-quarters (77%) of the physician-colleague abusers were men, whereas more than three-quarters (77%) of the other coworker abusers were women. Interviewed family physicians described feeling humiliated and unappreciated, and developed symptoms of anxiety or depression. As a result of the abuse, some family physicians terminated their employment or refused to work in certain environments. The most striking effect of this abuse was that respondents reported losing confidence in their professional abilities and skills. CONCLUSION: Although only a small number of family physicians experience abuse by physician colleagues and other coworkers, the effects can be considerable. Victims reported a loss of confidence in their clinical abilities and some subsequently were faced with mental health issues.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".