Gender Differences in the Symptoms of Major Depressive Disorder
Bibliographic record
Abstract
Data from the Canadian Community Health Survey 1.2 were used for a gender analysis of individual symptoms and overall rates of depression in the preceding 12 months. Major depressive disorder was assessed using the Composite International Diagnostic Interview in this national, cross-sectional survey. The female to male ratio of major depressive disorder prevalence was 1.64:1, with n = 1766 having experienced depression (men 668, women 1098). Women reported statistically more depressive symptoms than men (p < 0.001). Depressed women were more likely to report "increased appetite" (15.5% vs. 10.7%), being "often in tears" (82.6% vs. 44.0%), "loss of interest" (86.9% vs. 81.1%), and "thoughts of death" (70.3% vs. 63.4%). No significant gender differences were found for the remaining symptoms. The data are interpreted against women's greater tendency to cry and to restrict food intake when not depressed. The question is raised whether these items preferentially bias assessment of gender differences in depression, particularly in nonclinic samples.
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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 | 0.001 | 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) | 0.003 | 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".