How bipolar disorders are managed in family practice: self-assessment survey.
Bibliographic record
Abstract
OBJECTIVE: To investigate family physicians' experience in diagnosing and managing bipolar disorder, how they rate their undergraduate and postgraduate training in this area, and what they think they need to learn in the future. DESIGN: Survey questionnaire. SETTING: Family practices in London, Ont. PARTICIPANTS: Random sample of 297 family physicians. MAIN OUTCOME MEASURES: Physicians' experience in diagnosing and managing patients with bipolar disorder, rating of their undergraduate and postgraduate training in this area, and thoughts about what they need to learn in the future. RESULTS: Of 297 surveys sent out, 147 (49.5%) were returned. Male respondents accounted for 62%, and female respondents 37%, of completed surveys. Average year of graduation from medical school was 1979. The most common response for level of experience in diagnosing and treating bipolar disorders was "somewhat comfortable." Physicians frequently reported screening for symptoms of mood disorders (42%), and most of them were sharing care with other professionals (88%). Undergraduate training was rated as poor (42%) or satisfactory (46%), and postgraduate training was rated as poor (42%) or satisfactory (44%). Physicians thought they needed more education in issues of diagnosis and pharmacotherapy. CONCLUSION: Family physicians were only somewhat comfortable with diagnosing and managing bipolar disorders, and most thought their undergraduate and graduate training in this area had been, at best, satisfactory. They expressed a need for more education in the areas of diagnosis and pharmacotherapy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".