Physical activity, sport participation and depressive symptoms among early adolescents with a family history of obesity
Bibliographic record
Abstract
An inverse association between physical activity (PA) and mental health has been established in both cross-sectional and longitudinal research findings across the lifespan. However, the different intensities of PA and types have not consistently been evaluated as protective of mental health outcomes such as depression symptoms. The purpose of this study was to examine whether PA at varying intensities and sport participation were uniquely associated with depressive symptoms among 409 early adolescents (56% male; Mage = 11.66, SD = 0.89 years) with a family history of obesity. PA intensities (light and moderate-to-vigorous) were objectively assessed with an accelerometer worn for seven days. Sport participation and depressive symptoms were measured by self-report questionnaires. Sex-stratified regression analyses controlling for fat mass index (DXA) and fitness (VO2 Max) were used to examine the associations between PA, sport participation and depressive symptoms. The model predicting depressive symptoms among boys was significant (p < .05) with sport participation (b = -0.22, p < .01) emerging as a significant correlate. The model predicting depressive symptoms among girls was not significant. Based on these findings, intervention efforts aimed at reducing depressive symptoms among early adolescents could be directed at encouraging sport participation among boys with a family history of obesity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".