Original Research Prevalence of Depression and Prescriptions for
Bibliographic record
Abstract
Depression prevalence rates for this rural community were greater than rates reported for the Canadian population. The depression prevalence rate for the Aboriginal population was not greater than that for the non-Aboriginal population. Not all patients with depression–anxiety disorders are prescribed antidepressants, and not everyone prescribed an antidepressant has a depression–anxiety disorder. The higher suicide rates reported for First Nations people may be more closely related to something like binge-drinking behaviour than to higher depression rates in this population. Limitations This study was based on a retrospective chart review performed by one clinician. It was difficult to make precise DSM-IV diagnoses on the basis of chart data provided. The results are for one rural community; the applicability to other communities is unclear. Objective: To determine the prevalence of depression–anxiety disorders and the degree to which physicians prescribed antidepressants for Aboriginal and non-Aboriginal populations living in a remote rural community in British Columbia in 2001. Methods: To obtain data for our main outcome measures, we retrospectively reviewed the charts of 2375 patients living in the Bella Coola Valley as of September 2001 and attending the Bella
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".