Risk and protective factors associated with intentional self‐harm among older community‐residing home care clients in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: We aim to concurrently examine risk and protective factors associated with intentional self-harm among community-residing older adults receiving home care services in Ontario, Canada. METHODS: Administrative health data from the home care sector were linked to hospital administrative data to carry out the analyses. Home care data are collected in Ontario using the Resident Assessment Instrument-Home Care (RAI-HC), an assessment tool that identifies strengths, preferences and needs of long-stay home care clients. The sample included Ontario home care clients aged 60 years or older assessed with the RAI-HC between 2007 and 2010 (N = 222,149). Multivariable analyses were performed using SAS. RESULTS: Hospital records of intentional self-harm (ISH) were present in 9.3 cases per 1000 home care clients. Risks of ISH included younger age (60-74 years; OR = 3.14, CI: 2.75-3.59), psychiatric diagnosis (OR = 2.29, CI: 2.06-2.54), alcohol use and dependence (OR = 1.69, CI: 1.34-2.14), psychotropic medication (OR = 1.94, CI: 1.75-2.15) and depressive symptoms (OR = 1.58, CI: 1.40-1.78). Protective effects were found for marital status and positive social relationships, yet these effects were more pronounced for men. Cognitive performance measures showed the odds of ISH 1.86 times higher for older adults with moderate to severe cognitive impairment. CONCLUSIONS: This study based on provincial data points to tangible areas for preventative assessment by frontline home care professionals. Of interest were the risk and protective factors that differed by sex. As demand for home care in Canada is expected to increase, these findings may inform home care professionals' appraisal and approach to suicide prevention among community-residing 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".