Psychiatric Disorders in an Arctic Community
Bibliographic record
Abstract
OBJECTIVE: To determine the rates of depression, anxiety, and alcohol abuse, using modern nosology, in a random sample of residents aged 14 to 85 years living in an Arctic community. METHOD: A cross-sectional 2-step survey of randomly selected households was undertaken, using a self-report questionnaire to screen for anxiety, depression, and alcohol abuse. The survey included the Hospital Anxiety and Depression Scale (HADS) and Ewing and Roose's 4-question alcohol screening instrument (the CAGE questionnaire). Cut-off scores for the HADS and CAGE were found by comparing HADS and CAGE scores with scores on the Structured Clinical Interview for the DSM-III-R (SCID) in a stratified subsample. RESULTS: Estimated rates of depression and anxiety were 26.5% and 19.0% respectively within the past week, and estimated rates of lifetime alcohol abuse were 30.5%. CONCLUSIONS: The estimated prevalence of psychiatric disorders in this Arctic community is higher than that indicated in previous findings on Native mental health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".