Life Satisfaction, Positive Affect, and Sleep Impairment in Masters Athletes: Modulation by Age, Sex, and Exercise Type
Bibliographic record
Abstract
Introduction The masters athlete has been proposed as a model of successful aging. Research studies investigating psychological outlook in older athletes have primarily addressed negative affects including depression, anxiety, and stress. The impact of lifelong exercise on positive affect and life satisfaction as well as sleep impairment that could impact on these psychological states is largely unknown. Methods A series of questionnaires (general life satisfaction, positive affect, and sleep-related impairment) were administered to 240 masters athletes participating in the World Masters Athletics Championships. Total raw scores were converted into T scores for comparison with the general population. Meaningful difference was defined by the PROMIS® as one-half standard deviation from the centering sample. Results Meaningful differences were observed for improved general life satisfaction and reduced sleep impairment for all masters athletes. Positive affect did not reach the meaningful difference threshold. No significant sex differences were found for any of the questionnaires (all p > 0.05). Similarly, no significant differences were found between endurance, sprint, and strength/power sports for general life satisfaction (p = 0.18), positive affect (p = 0.46), and sleep impairment (p = 0.77). In general, life satisfaction increased with age (r = 0.15, p = 0.02), and sleep impairment trended towards reduction with age (r = −0.13, p = 0.05). Positive affect demonstrated no correlation with age (r = 0.09, p = 0.18). Conclusion This study demonstrates that the lifestyles of masters athletes contribute to improved general life satisfaction and reduced sleep impairment but not improved positive affect. The beneficial effects were observed irrespective of age, gender, and sporting types.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".