Association between Lifestyle Behaviours and Mental Health of Adolescents: Evidence from the Canadian HBSC Surveys, 2002–2014
Bibliographic record
Abstract
Physical activity (PA) and screen time (ST) are associated with mental health in adolescents, though little is known about their inter-relationships. This study examined the associations of PA and ST with psychosomatic complaints in adolescents. Data from four cycles of the Canadian Health Behaviour in School-aged Children (HBSC) surveys, collected between 2002 and 2014, were analysed. Eight psychosomatic health complaints were assessed and dichotomised as frequent (≥2 complaints/week) vs. infrequent. PA was assessed by number of days/week participants were physically active for ≥60 min. Discretionary ST was assessed by adding three screen uses: television, electronic games, and computer. Of the 37,829 adolescents (age 13.74 (SD 1.51) years; 52% girls), 25% boys and 39% girls reported frequent psychosomatic complaints. Multilevel logistic analyses showed that ST levels were positively associated while PA levels were negatively associated with reporting frequent psychosomatic complaints in a dose-dependent manner. Compared with ST ≤ 2 hrs/d, ST ≥ 4 hrs/d in girls and ST ≥ 6 hrs/d in boys showed higher odds of reporting psychosomatic complaints. Participating in PA ≥ 60 min every day compared to no PA showed lower odds of reporting psychosomatic complaints by 44% in girls and 57% in boys. Prospective research is needed to understand the causal pathway of these dose-dependent relationships.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".