Bibliographic record
Abstract
BACKGROUND: The purpose of the present study is to explore the relation between use of antidepressants and level of alcohol consumption among depressed and nondepressed men and women. METHODS: Random-digit dialling and computer-assisted telephone interviewing were used to survey a sample of 14,063 Canadian residents, aged 18-76 years. The survey included measures of quantity and frequency of drinking, the World Health Organization's Composite International Diagnostic Interview measure of depression, and a question as to whether respondents had used antidepressants during the past year. RESULTS: Overall, depressed respondents drank more alcohol than did nondepressed respondents. This was not true, however, for depressed men who used antidepressants; they consumed a mean of 414 drinks during the preceding year, versus 579 drinks for depressed men who did not use antidepressants and 436 for nondepressed men. For women, the positive relation between depression and heavier alcohol consumption held true regardless of their use of antidepressants: 264 drinks during the preceding year for depressed women who used antidepressants; 235, for depressed women who did not use antidepressants; and 179, for nondepressed women. INTERPRETATION: Results of this cross-sectional study are consistent with a possible beneficial effect of antidepressant use upon drinking by depressed men. Further research is needed, however, to assess whether this finding results from drug effects or some other factor, and to ascertain why the effect was found among men but not women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".