Is the Statistical Association between Sex and the Use of Services for Mental Health Reasons Confounded or Modified by Social Anchorage?
Bibliographic record
Abstract
OBJECTIVE: Confounding and interaction have differing implications for the interpretation of findings and the design of research, mental health services, and policy. This study aimed to verify whether the association between sex and the use of services for mental health reasons is confounded or modified by social anchorage. METHODS: We undertook a case-control study nested in Cycle 1.2 of the Canadian Community Health Survey. Cases were defined as users of general medical services for mental health reasons in the previous 12 months, and control subjects were defined as never-users of any services for mental health reasons. The pattern of social anchorage was described by the roles of parent, spouse, worker, and their combination. RESULTS: Overall, women are 2.9 times more likely than men to use general services for mental health reasons. However, this inequality between women and men decreases substantially or subsides in individuals who are less anchored to Canadian society. For instance, in single parents and in unemployed parents, the odds of using general services for mental health reasons are similar in women and in men. The pattern of social anchorage tends to modify, but not to confound, the association between sex and the use of services. CONCLUSIONS: Ignoring the interaction between sex and the pattern of social anchorage distorts the interpretation of the inequality between women and men in the use of general medical services for mental health reasons and may affect the design of comprehensive mental health services and policy.
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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 | 0.058 | 0.166 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".