Older adults' knowledge of community support services: Does social support make a difference?
Bibliographic record
Abstract
This research was undertaken to better understand older adults' knowledge of community support services (CSS) and whether social support makes a difference in this knowledge. Further, there is a need to know if people recognize a need for assistance when facing a problem; if they see CSS as a source of assistance, and where they seek information about community services. Existing research had yielded inconsistent results due to the use of different community services and different definitions of knowledge. There has been a limited exploration of social support. A telephone survey of 1152 people aged 50 and older in Hamilton, Ontario collected information on respondents' demographics, community engagement and social support. To assess knowledge, respondents listened to four vignettes of problems commonly faced by seniors and were asked, "If you were in this situation what would you do?" Knowledge of CSS was the number of agencies named. The results of the logistic regression show that being female, having a higher income, perceiving social support, belonging to clubs or organizations, and being able to name an information source were positively associated with knowledge of CSS. Most people recognized the problem presented in the vignettes and would take action. Of those who would not take action, over half did not know any CSS. Most people named at least one information source and over half named two or more. Results underscore the importance of support networks in providing informational support to individuals. People who receive support were more likely to know of CSS than those who neither provided nor received support. There are differences between being a member of a support network and a care network. Providers of care were more likely to know of CSS than providers of support. Word of mouth including family and friends was one of the five most frequently used sources of information. Policy implications focus on improving information available to seniors. Funded by CIHR and United Way of Burlington and Greater Hamilton.
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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 | 0.014 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".