The association between social media use and physical activity among Canadian adolescents: a Health Behaviour in School-aged Children (HBSC) study
Bibliographic record
Abstract
OBJECTIVE: To determine the association between social media use (SMU) and physical activity (PA) among Canadian adolescents. METHODS: We used data from 12,358 participants in grades 6 to 10 who responded to the Canadian component of the 2017/2018 Health Behaviour in School-aged Children (HBSC) survey. Social media intensity and problematic SMU were assessed using a 4-point mutually exclusive scale that contained three categories based on intensity (non-active, active, and intense SMU) and one category based on the presence of addiction-like symptoms irrespective of intensity (problematic SMU). PA was assessed for five domains (i.e., school curriculum, organized sport, exercise, outdoor play, and active transport) and dichotomized using the first quartile to represent high PA engagement in each domain. Meeting PA recommendation of 60 min per day of moderate-to-vigorous PA was calculated using the sum of the five domains. Logistic regression models were used to assess the association between SMU and PA, with active SMU used as the reference group for all models. RESULTS: Non-active SMU was associated with lower odds of meeting the daily PA recommendations and of high engagement in all five domains of PA when compared to active SMU. Intense SMU was associated with higher odds of meeting the daily PA recommendations. Problematic SMU was not associated with meeting daily PA recommendations, but it was significantly associated with lower odds of high PA engagement in the exercise domain. CONCLUSION: The findings of this study suggest that non-active SMU was significantly associated with lower PA levels. Problematic SMU was only significantly associated with lower PA levels in the exercise domain. Intense SMU was associated with higher odds of meeting the PA recommendation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".