Exploring the Relationship between Perceived Multidimensional Social Support and Well-Being among Community Seniors Participating in Group Exercise Programs
Bibliographic record
Abstract
This study examines the relationship between perceived multidimensional social support and well-being among community-dwelling seniors engaged in group exercise programs, aiming to address a gap in the current literature. A total of 162 older adults from two communities in Selangor, Malaysia, participated in structured group exercise sessions. Using a quantitative survey design, data were collected through the Multidimensional Scale of Perceived Social Support (MSPSS) and the BBC Well-Being Scale to assess perceived support and overall well-being, respectively. Community leaders were engaged to support the study’s approval and facilitate its implementation. Descriptive statistics were used to summarize participants’ demographic characteristics and study variables, while Pearson correlation analysis was conducted to examine the relationships between perceived social support and well-being. The sample consisted predominantly of males (63%), reflecting a gender imbalance in exercise participation that aligns with findings from previous studies. Results showed no significant correlation between perceived social support and overall well-being (r(160) = -0.113, p > .05), indicating a weak negative relationship. This suggests that higher levels of perceived social support did not correspond with notable improvements in well-being among the participants. These findings challenge the prevailing literature that often highlights a positive association between social support and well-being, suggesting that the relationship may be more nuanced within the context of community-based group exercise programs for older adults. Further investigation is needed to uncover the underlying factors that may influence this relationship in this specific demographic.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".