Population-based use of mental health services and patterns of delivery among family physicians, 1992 to 2001.
Bibliographic record
Abstract
OBJECTIVE: To examine 9-year rates of family physician (FP) and psychiatrist use, as well as patterns of mental health services delivery by FPs. METHOD: We used population-based data from Winnipeg, Manitoba, to construct mutually exclusive cohorts of adults treated for major or minor mental health disorders in fiscal years 1992-1993 to 2000-2001. For each year, we measured patterns of use in this population and patterns of mental health practice among FPs. RESULTS: The treatment prevalence rate was 224 per 1000 in 2000-2001 and 174 per 1000 in 1992-1993, and the rates for major and minor mental health disorders increased over the 9-year period by 15% and 31%, respectively. In 2000-2001, 92% of adults treated for mental illness saw at least one FP, and 45% saw an FP but no psychiatrist. Adults with major or minor mental health disorders visited an FP on average 9.1 and 6.9 times yearly, respectively, and FP visit rates remained relatively stable. There was a gradient in use by socioeconomic status: adults from communities with lower socioeconomic status had the highest rates of use. By 2000-2001, 24% of FPs billed for services related to psychosocial conditions as often as they did for the most frequent conditions seen in primary care. CONCLUSION: Between 1992-1993 and 2000-2001, the study population's patterns of FP and psychiatrist use remained relatively stable. In more recent years, FPs provided more mental health services than in previous years; this related to increased treatment prevalence rather than to increases in use per adult. FPs played a major role in the provision of mental health care.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".