1062 – Predictors For Remission Of Major Depression And Anxious Disorders And For Developing Disorders In An Epidemiologic Catchment Area In Montreal, Canada: a Longitudinal Study
Bibliographic record
Abstract
Objectives The aim of this study is identifying the predictors of major depression and anxiety disorders and the predictors of the remission of these disorders. Methods A longitudinal study under the form of a community survey includes a randomly selected sample of 2,434 individuals between 15 and 65 years of age (T1); 1,815 agreed to be re-interviewed two years later (T2). Mental disorders were identified with the Composite International Diagnostic Interview, including mood disorders (major depression, and mania), and some anxiety disorders: panic disorder (PD), social phobia (SP), and agoraphobia (AG). Logistic regression was used to identify predictors (T1) of remission of mood disoders and anxiety disorders at T2 and predictor of new cases at T2. Results The prevalence of mental disorders for the two waves of the research program will be presented. For major depression (MD), among the 145 subjects who had MD at T1, 69% recovered at T2 and among the 1553 that did not have MD at T1, 5.7% developed MD at T2. For anxiety disorders, among the 93 subjects who had these disorders at T1, 78.4% recovered at T2 and among the 1635 subjects who were free of an anxiety disorder at T1, 1.8% developed it at T2. Predictors identified for remission of disorders and for developing new disorders at T2 will be presented. Conclusion The predictors of new cases identified will allow to develop more effective prevention program and those associated to remissions will help to improve mental health services.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".