Early Socio-Emotional Difficulty as a Childhood Barrier to the Expected Benefits of Active Play: Associated Risks for School Engagement in Adolescence
Bibliographic record
Abstract
Active play allows children to develop social and cognitive skills, which could lead to higher school engagement. Little is known about the role of child socioemotional difficulty in these associations. This study aims to examine the interaction between active play and socioemotional difficulty in childhood and their prospective association with academic engagement in adolescence. The participants were 4537 children (51.1% boys) who were longitudinally followed, between ages 6 and 14 years, from the National Longitudinal Study on Children and Youth (NLSCY), Canada. Active play (weekly organized sport and unstructured physical activity outside of school hours) and child behavior (hyperactivity, anxiety, and relational difficulties) were reported by mothers for their children at age 6 years. Academic engagement was self-reported at age 14 years. Unstructured physical activity predicted lower subsequent school engagement for boys (β = −0.057, p < 0.05). Boys with high anxiety symptoms and high relational aggression who participated in more unstructured physical activity in childhood were subsequently less engaged in school (respectively, β = −0.066, p < 0.05 and β = −0.062, p < 0.05). Girls who partook in more organized sports showed lower school engagement in adolescence when they had high anxiety symptoms (β = −0.067, p < 0.05). Although past studies have highlighted the contribution of active play to school engagement, certain socioemotional difficulties could impede the child’s ability to reap its benefits.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".