Supportive behaviors and relationships in group exercise for older adults: Observational research
Bibliographic record
Abstract
Meaningful relationships and physical activity are important contributors to older adults' physical and psychological well-being. Structured group exercise programs delivered in a supportive environment can lead to the development of relationships, but the behaviors facilitating a supportive environment within these programs are not well understood. The purpose of this research was to examine interpersonal interactions amongst older adults in group exercise classes and identify supportive behaviors that may contribute to the development of relationships within group exercise classes. Four observations of adults age 55 and older, who were engaged in group physical activity programs were completed at four sites (i.e., 16 observation) in Calgary. Field notes were thematically analyzed in light of successful aging and social support theory. Instructors created a supportive environment by engaging in conversations with the exercisers, providing advice, and offering assistance when needed to ensure all the exercisers felt included. Instructors provided support by offering inclusive positive feedback, and demonstrated genuine care by addressing exercisers' concerns. By ensuring there were no potential hazards on the floor when exercisers walked around, and by correcting them when they were in an incorrect position to avoid injuries, instructors helped create a safe environment facilitating trusting relationships. During the exercise class, exercisers provided each other with support by smiling, making jokes, and laughing. Many exercisers got together before or after their exercise classes to have coffee and discuss among each other. Results highlight behaviors both instructors and exercisers can adopt to facilitate a supportive environment within structured group exercise programs.Acknowledgments: Funding: Social Sciences and Humanities Research Council of Canada Insight Grant.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".