Coping strategies, depression, and anxiety among Ontario family medicine residents.
Bibliographic record
Abstract
OBJECTIVE: To assess the current prevalence of depression and anxiety among Ontario family medicine residents, and to describe their coping strategies. DESIGN: Surveys mailed to residents integrated DSM-IV diagnostic criteria and a previously validated Patient Health Questionnaire. SETTING: Ontario family medicine programs from June to August 2002. PARTICIPANTS: Residents entering, advancing in, or graduating from residency programs: approximately 216 yearly for a total of 649 residents. MAIN OUTCOME MEASURES: Types and frequency of coping skills used by residents; prevalence of depressive and anxiety disorders. RESULTS: Response rate for residents entering programs was 46% and for graduating residents was 30% (37% response rate overall). Prevalence of depressive disorders was 20% (13% major depressive disorders, 7% other depressive syndromes)(odds ratio [OR] 3.4, confidence interval [CI] 2.7 to 7.5, P < .001). Prevalence of generalized anxiety disorder was 12%, and 2% of residents met criteria for panic syndrome (OR 4.3, CI 1.6 to 11.8, P = .002). Rates were similar for men and women. Medical training was commonly identified as a negative influence on the mental health of troubled residents. Residents most often turned to family and friends when they needed help (43.7% of respondents). About 17.3% saw their family doctors, 15.4% counselors, and 7.9% psychiatrists. Some residents (13.4%) used medication to deal with their affective symptoms, 7.1% underwent cognitive-behavioural therapy, and 8.3% required a leave of absence from their programs. More than half (61.8%) indicated recreational use of alcohol and drugs, 1.2% identified use due to addiction, and 5.9% used drugs to help cope with their problems. Four respondents admitted concern that they might commit suicide during residency; a different three had made previous attempts. CONCLUSION: Affective disorders (both depression and anxiety syndromes) are three to four times more common among Ontario family practice residents than in the general population; male and female residents are equally affected. Most residents with these problems report negative effects on their function at work. Medical training is the most commonly identified negative influence on mental health. While residents most often obtain help from family members and friends, many seek professional help.
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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 | 0.002 |
| 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) | 0.002 | 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".