TRANSPORTATION MOBILITY AND SOCIAL ISOLATION IN COMMUNITY-DWELLING OLDER ADULTS
Bibliographic record
Abstract
Social isolation is a common problem in community-dwelling older adults, with prevalence estimated to range from 10% to 43%. Social isolation is associated with negative health outcomes (all-cause mortality, dementia, falls, and re-hospitalizations) and reductions in quality of life and well-being in the older adult population. Despite the importance of transportation mobility to social integration, few studies have examined the relationship between of transportation mobility and social isolation in older adults. Our primary objective was to examine the factors associated with social isolation in drivers and non-drivers 65 years of age and older in rural and urban communities in the province of Alberta. Telephone interviews were conducted with adults 65+ in rural and urban Alberta, with RDD primarily used to generate the sampling frame. Predictor variables included age, gender, living arrangements, driving status, QoL, and well-being. The primary outcome variable was a composite measure of social isolation (lacking companionship, feeling left out, and feeling isolated). Overall, 1390 older adults were interviewed (1043 drivers/347 non-drivers). Results from a logistic regression indicated that driving status was a significant predictor of social isolation, with non-drivers scoring significantly higher than drivers. Gender (females), QoL (lower), and well-being (lower) also were predictive of social isolation (all P’s < .05), with the combined variables accounting for more than 20% of the variance. Our results highlight the important role that driving status plays in social isolation in community-dwelling older adults in both urban and rural areas.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".