Prevalence and Correlates of Exergaming in Youth
Bibliographic record
Abstract
OBJECTIVES: Less than 15% of children and adolescents participate regularly in physical activity (PA) and, with ever-increasing obesity, strategies to improve PA levels in youth are urgently needed. Exergaming offers a PA alternative that may be especially attractive in our increasingly technophilic society. However, there are no observational studies of exergaming in population-based samples of adolescents. The purpose of this study was to investigate potential sociodemographic, lifestyle, psychosocial, weight-related, and mental health correlates of exergaming as well as describe the type, timing, and intensity of exergaming in a population-based sample of adolescents. METHODS: Data on exergame use and potential sociodemographic, lifestyle, psychosocial, weight-related, and mental health correlates of exergaming were collected in mailed self-report questionnaires completed by 1241 grade 10 and 11 students from the Montreal area with a mean age of 16.8 years (SD = 0.05 years; 43% male) participating in the AdoQuest study. The independent correlates of exergaming were identified in multivariable logistic regression models. RESULTS: Nearly one-quarter (24%) of participants reported exergaming. Exergamers played 2 days per week on average, for ∼50 minutes each bout; 73% of exergamers played at a moderate or vigorous intensity. Exergamers were more likely than nonexergamers to be girls, to play nonactive video games, to watch ≥2 hours of television per day, to be stressed about weight, and to be nonsmokers. CONCLUSIONS: Many adolescents exergame at intensity levels that could help them achieve current moderate-to-vigorous PA recommendations. Interventions that encourage exergaming may increase PA and decrease sedentary behavior in select youth subgroups, notably in girls.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".