Assessing the Physiological Cost of Active Videogames (Xbox Kinect) Versus Sedentary Videogames in Young Healthy Males
Bibliographic record
Abstract
Objectives: \nThe aims of this study were twofold: (1) to compare the physiological costs of active videogames (AVGs) and sedentary videogames (SVGs) and (2) to compare the exercise intensities attained during AVGs with the exercise intensity criteria for moderate and vigorous physical activity, as stated in current physical activity recommendations for improving public health. \n \nMaterials and Methods: \nNineteen young males participated in the study (age, 23 ± 3 years; height, 178 ± 6 cm; weight, 78 ± 15 kg). Participants completed a maximum oxygen uptake (VO2max) test and a gaming session, including AVGs (“Reflex Ridge,” “River Rush,” and “Boxing” for the Microsoft [Redmond, WA] Kinect™) and SVGs (“FIFA 14” [Electronic Arts, Burnaby, BC, Canada] and “Call of Duty” [Activision, Santa Monica, CA]). Heart rate (HR) and oxygen uptake (VO2max) were recorded continuously during all videogames. Rating of perceived exertion (RPE) was taken every 3 minutes during AVGs and SVGs. Energy expenditure (EE), expressed as metabolic equivalents (METs), was calculated. One MET was defined as the volume of oxygen consumed at rest in a seated position and is equal to 3.5 mL of O2/kg of body mass/minute. The exercise intensity for each game was expressed as a percentage of VO2max and percentage of age-predicted maximum HR (HRmax). \n \nResults: \nExercise intensity (percentage HRmax, percentage VO2max, and RPE) and EE (METs) were significantly higher during active gaming compared with sedentary gameplay (P < 0.01). AVGs elicited moderate levels of exercise intensity (64–72 percent HRmax) in line with current recommended physical activity guidelines. \n \nConclusions: \nOur results indicate AVGs provoke physiological responses equivalent to a moderate-intensity physical activity.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".