The Social Epidemiology of Affective and Anxiety Disorders in Later Life in Canada
Bibliographic record
Abstract
OBJECTIVE: To examine the association between markers of social position and psychiatric disorder among older adults, and test whether social support mediates the association between social position and psychiatric disorder in this population. METHODS: We used data from the Canadian Community Health Survey: Mental Health and Well-Being to examine the social patterning of disorder. Using a series of logistic regression analyses, we regressed indicators of mood, anxiety, and any disorder on markers of social position and social support. RESULTS: A negative association between age and disorder was evident across all models, and the likelihood of reporting disorder was elevated among separated-divorced and widowed respondents relative to their married counterparts. Social support was statistically significant in all models, and mediated a considerable amount of the effect of marital status on disorder. CONCLUSIONS: Many of the markers of social position associated with disorder among younger adults continue to be important predictors among older adults, and these variables are mediated to varying degrees by social support. The results support the general notion that social circumstances are important to psychological well-being. We discuss potential explanations for findings related to sex, age, marital status, and education as predictors of disorder in later life.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".