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 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 | 0.004 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 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".