Abstract MP82: Exergaming and Physical Activity Guidelines- A Population-Based Study of Young Adults
Bibliographic record
Abstract
Background: Compared to traditional non-active video games, exergaming may contribute significantly to overall daily physical activity (PA), but the association in population-based samples has not been fully explored. Objectives: To assess whether total minutes of PA per week among exergamers differs from non-exergamers, and whether the likelihood of meeting PA guidelines differs between exergamers and non-exergamers. Methods: Data were available from the 2011-2012 wave of the Nicotine Dependence in Teens (NDIT) study (n=829). Multivariable models assessed the association between exergaming with moderate, vigorous, and moderate-to-vigorous PA (MVPA) minutes in the past week, and the association between exergaming and meeting PA guidelines after adjusting for age, household income, employment status, education, weight status, and screen time. Exergaming was defined as use ≥ 1-3 times per month in the past year, and PA guidelines were defined as ≥ 150 minutes of moderately intense PA, or ≥ 75 minutes of vigorously intense PA, or a combination. Minutes of PA were measured using the well-validated International Physical Activity Questionnaire. Sex differences in exergaming use and exergaming beliefs and attitudes were also assessed. Results: In this population-based sample of young adults (mean age 24 [SD: 0.7] years, 55% female [n=455]), 18% (n=148) of the participants were exergamers (54% female, n=80). Exergaming males and females reported an average of 88.4 and 65.7 exergaming minutes in the past week, respectively. Compared to male exergamers, female exergamers were more likely to believe that exergaming is a good way to integrate PA into their lives (p<0.001), were more likely to prefer exergaming to indoor/outdoor sports (p=0.03), and were more likely to use fitness-training exergames at home (p=0.006). Perceived levels of exertion were also significantly different between male and female exergamers. The majority of male exergamers reported light (51%, n=23) or moderate (44%, n=20) exergaming exertion, whereas female exergamers reported moderate (53%, n=30), as well as light (28%, n=16) and intense (19%, n=11) exertion (p=0.02). After adjusting for covariates, male exergamers were not significantly different from male non-exergamers in total minutes of PA per week, but female exergamers reported 47 more minutes of moderate PA in the past week compared to female non-exergamers (p=0.03). There was no association between exergaming and meeting PA guidelines in either males or females. Conclusions: Exergaming contributes to moderate-intensity PA among females but not among males in this population based sample of young adults. Exergaming may therefore be an important source of PA for women, but the current landscape of exergames may be inadequate to substantially increase minutes of PA among males. Differences in attitudes toward exergaming should be further explored.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.001 |
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".