Alternate Forms of Physical Activity; Are Activity-Promoting Video Games an Effective Form of Energy Expenditure?
Bibliographic record
Abstract
Overweight and obesity, which are typically associated with an increased prevalence of hypokinetic diseases, are growing public health concerns in Canada. Aside from high calorie diets, much of the blame has been attributed to physical inactivity and sedentary behaviours. High levels of screen time are associated with overweight and obesity in youths and adults. An emerging novel alternate form of physical activity (PA) is that of Activity-Promoting Video Games (APVG) such as the Nintendo Wii system and Dance Dance Revolution. The goal of these video activities is to contribute to overall daily energy expenditure by converting normally sedentary screen time into active screen time. Some research indicates that playing these video games regularly can elicit an exercise response that meets national PA guidelines, while other research does not. The measured energy expenditure while participating in APVGs is elevated above that of sedentary counterparts, but it is not as high as participating in the real life activities simulated in the video games. Surprisingly, an interactive video game involving stationary cycling improved training adherence and common indicators of health-related fitness more than traditional stationary cycling, but did not change body composition. Although APVGs may increase daily energy expenditure when they replace sedentary screen time, their overall effectiveness in improving health is unclear. On the other hand, APVGs could achieve some increase in caloric expenditure in individuals who avoid typical forms of PA. Further high quality investigations of these new APVGs will allow clearer judgments on their effectiveness.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
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".