The Longitudinal Relationships Between Social Isolation, Frailty, and Health Outcomes Among Canadian Older Adults
Bibliographic record
Abstract
Abstract Social isolation and frailty are global public health issues that may lead to poor health outcomes. We tested the two following hypotheses: 1) changes in social isolation and frailty are associated with adverse health outcomes over two years, 2) the associations between social isolation and health vary across different levels of frailty. We estimated a series of latent growth models to test our hypotheses using data from the FRéLE longitudinal study among 1643 Canadian community-dwelling older adults aged 65 years and over. Missing data were handled by pattern mixture models with the assumption of missing not at random. We measured social isolation through social participation, social networks, and social support from different social ties. We assessed frailty using Fried’s criteria. Our results revealed that higher frailty at baseline was associated with a higher rate of comorbidity, depression, and cognitive decline over two years. Less social participation at baseline was associated with comorbidity, depression, and changes in cognitive decline. Less social support from friends, children, partner, and family at baseline was associated with comorbidity, cognitive decline, and changes in depression. Fewer contacts with grandchildren were related to cognitive decline over time. The associations of receiving less support from partner with depression and participating less in social activities with comorbidity, depression, and cognitive decline were higher among frail or prefrail than robust older adults over time. This longitudinal study suggests that intimate connectedness and social participation may ameliorate health status in frail older populations, highlighting the importance of age-friendly city policies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 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) | 0.002 | 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".