In-school and non-school sport participation during adolescence and mental health outcomes in early adulthood
Bibliographic record
Abstract
The purpose of this longitudinal study was to (1) examine the differences between mean scores on depressive symptoms, stress, and rating of mental health in early adulthood for individuals who were not involved, sporadically involved, or consistently involved in organised in-school sport and/or non-school sport and (2) to assess the associations between sport participation throughout adolescence and mental health indicators in early adulthood. Participants (N=880; 54% female) reported school and non-school sport participation on 20 survey cycles over 5 years during adolescence. Participation was coded as not involved, sporadically involved (at least one out of five years of sport involvement), and sustained involvement (involvement across all five years). Two years later, participants (Mage=20±0.75) reported on depressive symptoms, stress, and rating of mental health. Based on the ANOVA models, participants who were not involved in school sport reported significantly (p<.05) higher depression and stress and lower rating of mental health compared to sustainers, d=.27 to .33. Participants not involved in non-school sport reported significantly (p<.05) lower rating of mental health compared to those who were sustainers, d=.36. Linear regression analyses revealed that in-school sport participation during adolescence was a significant predictor of depression (R2=0.13), stress (R2=0.10), and rating of mental health (R2=0.10) in early adulthood. School sport participation throughout adolescence seems to have a distinct protective effect against negative mental health outcomes in early adulthood. These results imply that in-school sport opportunities for adolescents are valuable for mental health later in life.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".