After the bell: adolescents’ organised leisure-time activities and well-being in the context of social and socioeconomic inequalities
Bibliographic record
Abstract
BACKGROUND: Previous research has linked adolescents' participation in organised leisure-time activities (OLTAs) to better health and well-being. It remains unclear whether these associations can be observed consistently across social and socioeconomic strata and countries. METHODS: The present study used nine nationally representative samples of adolescents aged 11, 13 and 15 years (total n=55 429) from the 2017/2018 Health Behaviour in School-aged Children survey from Europe and Canada. Regression models with mixed effects to account for nested nature of data were applied to estimate: (1) the associations of social and socioeconomic factors with OLTA participation; (2) strengths of the associations between breadth and pattern of OLTA participation with health and well-being indicators, after adjustment for the social and socioeconomic factors. RESULTS: Rates of OLTA participation varied by age, sex and country of adolescents. Participants from lower socioeconomic classes and non-nuclear families were less likely to participate in OLTAs across each of the nine countries. Moreover, breadth of OLTA participation was associated with higher well-being independent of socioeconomic status or family structure. All of the participation patterns were associated with higher life satisfaction, but sports (either alone or in combination with a non-sport OLTA) were also associated with fewer psychological complaints and excellent self-rated health. CONCLUSION: Adolescents' engagement in OLTAs was associated with adolescents' subjective well-being regardless of country, age, sex and variance in social and socioeconomic factors. Policies aimed at increasing adolescents' subjective well-being and OLTA participation should focus on adolescents from low socioeconomic classes and non-nuclear families.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".