Estimated Prevalence of the Seasonal Subtype of Major Depression in a Canadian Community Sample
Bibliographic record
Abstract
OBJECTIVE: To examine estimates of lifetime prevalence of seasonal affective disorder (SAD) in Toronto, Ontario. METHOD: Random telephone numbers were generated for the city of Toronto, and 781 respondents completed a telephone interview. Trained nonphysician interviewers conducted all interviews, which involved structured questions for diagnosing major depression. Patterns of symptom change across seasons were evaluated to establish a diagnosis of SAD according to DSM-III-R criteria. RESULTS: Correcting for sex and age, the prevalence of SAD defined by DSM-III-R criteria was 2.9% (95% CI, 1.7% to 4.0%), and the overall lifetime prevalence of major depression in the sample was 26.4% (95% CI, 23.3% to 29.4%). Some subjects were contacted for a follow-up interview conducted in person; the positive predictive value for the diagnosis of major depression for the telephone interview was 100%, and the negative predictive value was 93%. CONCLUSIONS: The seasonal subtype of depression represents 11% of all subjects with major depression, suggesting that SAD is a significant public health concern. The telephone interview demonstrated adequate reliability, indicating that it is appropriate for epidemiological surveys of this nature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".