Sex‐based trajectories of health system use in lonely and not lonely older people: A population‐based cohort study
Bibliographic record
Abstract
BACKGROUND: There is growing interest in understanding the care needs of lonely people but studies are limited and examine healthcare settings separately. We estimated and compared healthcare trajectories in lonely and not lonely older female and male respondents to a national health survey. METHODS: We conducted a retrospective cohort study of community-dwelling, Ontario respondents (65+ years) to the 2008/2009 Canadian Community Health Survey-Healthy Aging. Respondents were classified at baseline as not lonely, moderately lonely, or severely lonely using the Three-Item Loneliness Scale and then linked with health administrative data to assess healthcare transitions over a 12 -year observation period. Annual risks of moving from the community to inpatient, long-stay home care, long-term care settings-and death-were estimated across loneliness levels using sex-stratified multistate models. RESULTS: Of 2684 respondents (58.8% female sex; mean age 77 years [standard deviation: 8]), 635 (23.7%) experienced moderate loneliness and 420 (15.6%) severe loneliness. Fewer lonely respondents remained in the community with no transitions (not lonely, 20.3%; moderately lonely, 17.5%; and severely lonely, 12.6%). Annual transition risks from the community to home care and long-term care were higher in female respondents and increased with loneliness severity for both sexes (e.g., 2-year home care risk: 6.1% [95% CI 5.5-6.6], 8.4% [95% CI 7.4-9.5] and 9.4% [95% CI 8.2-10.9] in female respondents, and 3.5% [95% CI 3.1-3.9], 5.0% [95% CI 4.0-6.0], and 5.4% [95% CI 4.0-6.8] in male respondents; 5-year long-term care risk: 9.2% [95% CI 8.0-10.8], 11.1% [95% CI 9.3-13.6] and 12.2% [95% CI 9.9-15.3] [female], and 5.3% [95% CI 4.2-6.7], 9.1% [95% CI 6.8-12.5], and 10.9% [95% CI 7.9-16.3] [male]). CONCLUSIONS: Lonely older female and male respondents were more likely to need home care and long-term care, with severely lonely female respondents having the highest probability of moving to these settings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 | 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".