Natural Course and Predictors of Sustained Exergaming in Young Adults
Bibliographic record
Abstract
Objective:To describe the natural course of exergaming among young adults and identify predictors of sustained exergaming. Methods:To describe the natural course, we retained 592 participants from an ongoing longitudinal study with complete data on exergaming at four time points over 12–13 years between 2010–12 and 2023 (i.e., T1–T4 at mean ages 24.0, 30.6, 33.6, and 35.2, respectively). To identify predictors of sustained exergaming, we retained 228 participants with data on 27 potential predictors at T2 and data on exergaming at T2 and T3. The association between each potential predictor and sustained exergaming was examined as an independent study using multivariable logistic regression controlling for age, sex, and educational attainment. Results:Of 592 participants, 41.3%, 34.1%, and 38.5% sustained exergaming from T1 to T2, from T2 to T3, and from T3 to T4, respectively. Only 3% of participants sustained exergaming from T1 to T4. Most participants reported light- or moderate-intensity exergaming at all time points. Higher levels of external pressure to engage in physical activity, encouragement from close friends to exercise, and taking breaks from sitting during a typical workday were each associated with lower odds of sustained exergaming. Conclusion:Although exergaming is a popular activity among young adults, long-term sustained exergaming was rare. This may link to time constraints related to life transitions, evolving interests, changes in social circles, and shifting fitness goals among young adults. Research is needed to inform strategies that promote sustained exergaming and maximize its potential for positive impact among young adults.
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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 | 0.001 | 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 | 0.001 |
| 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".