Clinical Management of Suicidality in the Elderly: An Opportunity for Involvement in the Lives of Older Patients
Bibliographic record
Abstract
OBJECTIVE: To review the risk factors for suicide in the elderly and available interventions to avert this tragedy. METHOD: Systematic literature review, based on a PubMed search for studies in English. Included were randomized controlled trials (RCTs), controlled cohort studies, and case-control studies. Wherever possible, I reviewed papers dealing with suicide rather than suicide attempts or suicide ideation. RESULTS: The search for risk factors yielded 2 relevant cohort studies and 17 relevant case-control studies. Relevant to the matter of intervention were 2 RCTs and 5 cohort studies. CONCLUSIONS: Being male as well as having mental illness (particularly depression), physical illness, and interpersonal discord are all risk factors for suicide in the elderly. There is evidence to suggest that conscientious, systematic treatment of depression in elderly individuals reduces the rate of suicide in the elderly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".