Informal Social Support and Use of a Specialized Transportation System by Chronically Ill Older Adults
Bibliographic record
Abstract
Aging is commonly associated with an increase in chronic disease and disability, affecting access to transportation. This study examines factors that contribute to the decision to use Handy Dart transportation (a handicap-specialized service) among 869 elderly, chronically ill residents of a metropolitan region in British Columbia. Drawing on Chappell’s complementary model of support, the authors hypothesized that informal social support will be positively associated with specialized transportation service use. The authors employ the Andersen-Newman model of health use to help organize the other expected predictors. Results of logistic regression analysis revealed that the presence of regular social support, a positive attitude about Handy Dart helpfulness, being retired, disability because of arthritis, and perceived ill health were the strongest predictors of use. Age, gender, marital status, knowledge, and number of comorbid illnesses did not predict use of the service. The results are discussed within the context of changing needs for specialized transportation services.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".