Development of an Exergame to Deliver a Sustained Dose of High-Intensity Training: Formative Pilot Randomized Trial
Bibliographic record
Abstract
Background: Sport science can play a critical role in reducing health inequalities. The inverse relationship between life expectancy, cardiorespiratory fitness, and socioeconomic status could be addressed by performing high-intensity training (HIT), delivered in a class salient and accessible approach. Commercially available exergames have shown encouraging compliance rates but are primarily designed for entertainment purposes rather than focusing on health-related outcomes. A serious game tailored toward delivering an exercise stimulus, while reducing the aversive protocols associated with HIT, could be beneficial to engage and improve health outcomes in socially deprived males. Objective: The aims of this study were to develop an exergame capable of delivering HIT and evaluate the effect on selected health outcomes in men recruited in regions of socioeconomic deprivation. Methods: We conducted an exploratory trial in our target population, and participants were allocated to intervention (n=14) or control groups (n=10) by third-party minimization. The intervention was a 6-week training program consisting of three sessions of exergaming per week. The sessions involved a structured warm-up, then brief intermittent repetitions in the form of boxing rounds (10 s, 20 s, and 30 s) against their peers with a work/rest ratio of 0.25. Results: Retention to the intervention was 87.5% (21/24). Over the duration of the intervention, session attendance was 67.5% (170/252); repetition mean and peak heart rates (% of maximal) and session ratings of perceived exertion (AU, arbitrary units) were 86.3 (5.4%), 89.9 (6.1%), and 7.5 (2.2 AU), respectively. The effect of the intervention, when compared with the control, was a likely small beneficial improvement in predicted maximum oxygen consumption (VO2 max, 3.0; 90% confidence limits ±2.6%). Effects on body mass, waist circumference, and blood pressure were either trivial or unclear. Conclusions: Over the 6-week intervention, the exergame delivered a consistent and sustained dose of HIT, with some beneficial effects on aerobic fitness in the target population. Trial Registration: ClinicalTrials.gov NCT03477773; https://clinicaltrials.gov/ct2/show/NCT03477773 (Archived by WebCite at http://www.webcitation.org/6yDLgVs35)
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".