Gender differences in health service use for mental health reasons in community dwelling older adults with suicidal ideation
Bibliographic record
Abstract
BACKGROUND: To ascertain gender-specific determinants of antidepressant and mental health (MH) service use associated with suicidal ideation. METHODS: Data used in this study came from the ESA (Enquête sur la Santé des Aînés) survey carried out in 2005-2008 on a large sample of community-dwelling older adults (n = 2,004). Multivariate logistic regression analyses were carried out. RESULTS: The two-year prevalence of suicidal ideation was 8.4% and 20.3% had persistent suicidal thoughts at one-year follow-up. In males, the prevalence of antidepressant and MH service use in respondents with suicidal ideation reached 32.2% and 48.9%, respectively. In females, the corresponding rates were 42.6% and 65.6%. Males were less likely to consult MH services than females when their MH was judged poorly. Male respondents with higher income and education were less likely to use antidepressant and MH services. However, males using benzodiazepines were more likely than females to be dispensed an antidepressant. Among respondents with suicidal ideation, gender was not associated with service use. Younger age, however, was associated with antidepressant use. CONCLUSIONS: Increased promotion campaigns sensitizing men to the prodromal symptoms of depression and the need to foster access to MH care when the disorder is manageable may be needed.
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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 | 0.000 |
| 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) | 0.002 | 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".