LONELINESS AND SUICIDE IDEATION IN OLDER ADULTS: A LONGITUDINAL INVESTIGATION
Bibliographic record
Abstract
Abstract Older adults have the highest rates of suicide globally, necessitating theory and research investigating suicide and its prevention in later-life. The experience of loneliness is significantly associated with depression, hopelessness, negative health outcomes, and mortality among older adults. Yet, relatively little research has focused on the role of loneliness in conferring suicide risk in later life. The purpose of the present study was thus to investigate the potential associations between loneliness and suicide ideation and behavior in a sample of community-residing older adults recruited into a larger two-year longitudinal study of psychological risk and resiliency to later-life suicide ideation. We specifically recruited 173 adults, 65 years or older, from community locations in a medium-sized Canadian city, for a study on “healthy aging.” Participants completed measures of positive and negative psychological variables, including depression, loneliness, and suicide ideation at a baseline assessment, and again at 2-4 week, 6-12 month, and 1-2 year follow-up points. Findings indicated that loneliness (UCLA Loneliness Scale) was significantly positively associated with concurrent depression and suicide ideation, negatively associated with psychological well-being and perceived social support, and differentiated between participants who endorsed or denied having ever engaged in suicide behavior. Baseline loneliness also explained significant variability in the onset of suicide ideation over a 1-2 year period of follow-up, controlling for age, sex, and baseline depression and suicide ideation. These findings will be discussed in the context of the need for increased focus on psychosocial factors when assessing and intervening to reduce suicide risk in older adults.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".