Social Support Factors and Health Among a Senior Center Population in Southern Ontario, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Past research on senior centers has mainly focused on utilization, frequency, duration of attendance, participation or various activities and services. This study strives to go beyond previous research by examining social support factors and their relationship to mental and physical health across a senior center population in southern Ontario, Canada. Data were collected at two large senior centers in the Kitchener, Waterloo area. We used a self-administered survey among a sample of older participants (n=186). One-way ANOVA with post-hoc Duncan's multiple range tests, t-tests, and linear regression analyses were used to examine the influence of social support (friendship, caregiving and advice) on mental and physical health. The results indicated that caregiving is significantly related to physical health, how respondents feel in general, and happiness with personal life. Advice from others is significantly related to perceptions of having a life full of interesting things. Additionally, respondents who are volunteers perceive better health and social support than non-volunteers, those who eat at the center perceive better health and caregiving support, and those that started a new activity perceived better health and social support from friendships. Implications for social work practice, policy and future research are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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 it