Reasons why older adults play sport: A systematic review
Bibliographic record
Abstract
BACKGROUND: Despite the known contribution of sport to health and well-being, sport participation declines in older age. However, for some people, sport continues to play an important role in older age and may contribute to improved health and well-being in older years. Although the health-related benefits of participating in sport are commonly reported, the reasons why some older adults continue to play sport are not well understood. This systematic review aimed to (1) identify studies from the literature that evaluated the reasons why older adults (aged 55 years and older) participate in sport and (2) synthesize and discuss the reasons for their participation reported in the literature. METHODS: Searches of the electronic databases Embase, Medline, PsycInfo, PubMed, and SPORTDiscus were performed. Studies were included that evaluated reasons for sport participation in adults aged 55 years and older because this is the age at which sport participation has been reported to begin declining. The studies included in this review used qualitative, quantitative, or mixed methods designs, were peer reviewed, and were published in the English language before the search date (20 January 2019). RESULTS: A total of 1732 studies were identified. After exclusions, 30 studies were included in the review (16 qualitative, 10 quantitative, and 4 mixed methods). The review presents several features and findings from the studies, including a description and systematization of the reasons for participating in sport and the main reasons that participants gave for participating in sport (maintaining health, feeling and being part of a community, and taking advantage of opportunities to develop relationships). Other reasons included competing and attaining a feeling of achievement, taking advantage of opportunities for travel, and being part of a team. Sport was identified as contributing to the overall experience of successful ageing. There were few comparative differences for participating in sport, and there were only small differences between genders for the reasons given for participation. Generally, the quality of the studies was good; however, mixed methods studies lacked appropriate data analysis procedures. CONCLUSION: Older adults play sport for a range of health-related and social reasons that can contribute to the experience of successful ageing. Strategies to increase sport participation by older adults should focus on promoting these aspects.
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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 | 0.011 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".