In Review Suicide and Its Prevention Among Older Adults
Bibliographic record
Abstract
dults aged 65 years or over have high rates of suicide worldwide (1). Approximately 1.3 die by suicide in Canada every day (2). Older adults have long had high suicide rates (3–7); however, programmatic study of geriatric suicide is relatively recent. The prevalence of late-life suicides may increase as the baby boom cohort reaches retirement age (8), given this population’s high suicide rates (9,10) and because they are moving into a phase of life in which rates are high. However, baby boomers ’ strength in getting health care needs met (11) may help to stem that tide. Geriatric suicidology is in Can J Psychiatry, Vol 51, No 3, March 2006 143 Objective: To review the research on the epidemiology, risk and resiliency, assessment, treatment, and prevention of late-life suicide. Method: I reviewed mortality statistics. I searched MEDLINE and PsycINFO databases for research on suicide risk and resiliency and for randomized controlled trials with suicidal outcomes. I also reviewed mental health outreach and suicide prevention initiatives. Results: Approximately 12/100 000 individuals aged 65 years or over die by suicide in Canada annually. Suicide is most prevalent among older white men; risk is associated with suicidal ideation or behaviour, mental illness, personality vulnerability, medical illness, losses and poor social supports, functional impairment, and low resiliency. Novel measures to assess late-life suicide features are under development. Few randomized treatment trials exist with at-risk older adults. Conclusions: Research is needed on risk and resiliency and clinical assessment and interventions for at-risk older adults. Collaborative outreach strategies might aid suicide prevention. (Can J Psychiatry 2006;51:143–154) Information on funding and support and author affiliations appears at the end of the article.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".