Association of loneliness with healthcare transitions and mortality in older adults in Ontario, Canada: a retrospective cohort study
Bibliographic record
Abstract
Objectives To evaluate whether loneliness was associated with transition rates to and between healthcare settings and death in older adults and to examine whether associations were modified by sex. Design Retrospective cohort study. Setting Ontario, Canada, from December 2008 to February 2020. Participants Community-dwelling, Ontario respondents (≥65 years) to the 2008/2009 Canadian Community Health Survey—Healthy Aging (CCHS-HA). Exposure Baseline loneliness was measured with the Three-Item Loneliness Scale in the CCHS-HA. Respondents were classified as not lonely, moderately lonely or severely lonely. Primary outcome measures Healthcare transitions were assessed over a 12-year period through linkage to health administrative records. Relative rates of transition to and between community, inpatient hospitalisation, home care and long-term care (LTC) settings, as well as death, were estimated using a continuous-time multistate transition framework. Adjusted models were weighted and tested for sex interactions. Results Of 2671 respondents (weighted n=1 398 180), 20.9% were moderately lonely and 12.0% were severely lonely. Compared with those who were not lonely, moderately lonely respondents transitioned at a faster rate from the community to home care, and severely lonely respondents transitioned at a faster rate from the community to LTC; although, both associations were attenuated with adjustment (RR ML 1.37; 95% CI 1.00 to 1.85 and RR SL 1.96; 95% CI 0.99 to 4.12, respectively). Female and male respondents had mostly similar transition patterns. Conclusions Our findings suggest that loneliness may hasten transitions from the community to home care and LTC settings in older adults, although these transitions are mostly driven by related health and social factors.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".