Organized Sport Trajectories from Childhood to Adolescence and Health Associations
Bibliographic record
Abstract
INTRODUCTION: The purpose of this study was to identify unique organized sport trajectories from early childhood to late adolescence in an Australian pregnancy cohort, the Raine Study. METHODS: Participation in organized sport was assessed at ages 5, 8, 10, 14, and 17 yr. Physical activity, body composition, and self-rated physical and mental health were assessed at the age of 20 yr. Latent class analysis was used to identify patterns of sport participation. To assess the internal validity of the trajectory classes, differences in health characteristics between trajectories were analyzed using generalized linear models. RESULTS: For girls, three trajectory classes were identified: consistent sport participators (47.5%), sport dropouts (34.3%), and sport nonparticipators (18.1%). For boys, three trajectory classes were identified: consistent sport participators (55.2%), sport dropouts (36.9%), and sport joiners (8.1%). For girls, there were overall differences across trajectory classes in lean body mass (P = 0.003), lean mass index (P = 0.06), and physical health (P = 0.004). For boys, there were differences across classes in physical activity (P = 0.018), percent body fat (P = 0.002), lean body mass (P < 0.001), lean mass index (P < 0.001), physical health (P = 0.06), and depression scores (P = 0.27). CONCLUSION: This study identified unique, sex-specific trajectories of organized sport participation. The differences in health outcomes between trajectory classes, such as participants with consistent sport participation having more preferable health outcomes at the age of 20 yr, support the internal validity of the trajectories. Strategies are needed to identify and encourage those in the dropout trajectory to maintain their participation and those in the nonparticipator or joiner trajectories to join sport earlier. Specifically, interventions to encourage early sport participation in girls and help nonparticipating boys to join sport during adolescence may help more children receive the benefits of sport participation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".