Understanding diversity of sport participation in adolescence and perceived variety and exercise behaviour in adulthood
Bibliographic record
Abstract
Participation in exercise declines from adolescence to adulthood, yet participation in a diversity of sports during adolescence may protect individuals from this decline. However, the mechanisms that explain the relationship between participation in a diversity of sports during adolescence and exercise behaviour in adulthood have not been identified. Perceptions of variety may help explain this relationship. The purpose of this study was to examine the association between diversity of sport participation in adolescence and exercise behaviour in adulthood, and the extent to which this relationship is explained by perceptions of variety in exercise. Using a cross-sectional design, a community sample of 112 adults (Mage = 37.39 years, SD = 11.10; nfemale = 87) recalled their sport participation throughout adolescence and completed measures of perceived variety in exercise and current exercise behaviour. The results showed that diversity of sport participation did not directly predict exercise behaviour in adulthood but did indirectly through the experience of variety in exercise (point estimate = 0.09, 95%CI = 0.03 – 0.18), after controlling for age and gender (Model R2 = .09). These findings support the notion that participation in a diversity of sports during adolescence is associated with exercise behaviour in adulthood, and the extent to which people feel like they experience variety in exercise may explain this relationship. Diversification of sport participation in adolescence may facilitate perceptions of variety and be one strategy for fostering exercise behaviour in adulthood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".