Suicide Ideation in Older Adults: Relationship to Mental Health Problems and Service Use
Bibliographic record
Abstract
PURPOSE: to assess the prevalence of suicide ideation among community-dwelling older adults and the relationship between suicide ideation, major psychiatric disorder, and mental health service use. DESIGN AND METHODS: we use data from the Canadian Community Health Survey 1.2: Mental Health and Well-being (CCHS 1.2). We estimate the prevalence of suicide ideation and the prevalence of major psychiatric disorder and service use among ideators versus nonideators. In multivariate models, we consider the sociodemographic, social, and mental health correlates of suicide ideation and mental health care use. RESULTS: in our sample, more than 2% of older adults reported suicide ideation in the past year and more than two thirds of these respondents did not meet the criteria for any of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition disorders assessed in the CCHS 1.2. In multivariate models, being male, younger, or widowed, reporting lower social support and higher psychological distress increased the likelihood of suicide ideation. More than 50% of the respondents who reported suicidal thoughts did not access any type of mental health care use. IMPLICATIONS: although suicide ideation is associated with depression and anxiety disorders, many older adults with suicidal thoughts do not meet the criteria for these clinical disorders. The low prevalence of service use among older adults with suicide ideation suggests the need for further inquiry into the factors associated with discussing mental health concerns with health care providers, particularly among older adults who do not meet the criteria for clinical disorder.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".