Understandings of "successful aging" among older men across the physical activity spectrum
Bibliographic record
Abstract
The literature on 'successful aging' indicates that there is no unified definition of this term and that its meaning typically depends on the academic discipline of the researcher or the perspective and circumstances of the older person (Bowling, 2007; Depp & Jeste, 2006). The purpose of this study was to examine older men's understandings of successful aging and the role physical activity plays in shaping these definitions. The sample was 12 men aged 61 – 92 years who ranged from sedentary to elite athletes. Each participant was interviewed about their health, daily activities, exercise, and aging. Interviews ranged from 45 – 90 minutes in length. Findings were interpreted using biomedical and psychosocial approaches to successful aging. Results from the analysis indicated the distinct connection between notions of successful aging and current physical activity levels. Individuals who were highly physically active were more likely to define successful aging in biomedical terms, such as being healthy and exercising, while those who were less active tended to employ a psychosocial approach by describing it in terms of acceptance, happiness, having a purpose post-retirement and being financially secure. This study shows how physical activity involvement, or lack thereof, influences (and is influenced by) the meanings of aging among older men. Such information is important for sport and exercise scientists who are working with older men in physical activity and health contexts.Acknowledgments: We would like to acknowledge SSHRC for funding support
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".