At-Home Immersive Virtual Reality Exergames to Reduce Cardiometabolic Risk Among Office Workers: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The worldwide rise in the prevalence of noncommunicable diseases has increased the recognition of the need to identify modifiable risk factors for preventing and managing these diseases. The office worker, as a representative group of physically inactive workers, is exposed to risk factors for metabolic syndrome, which is a primary driver of noncommunicable diseases. The use of virtual reality (VR) exergames may offer a potential solution to the problem of increasing noncommunicable disease prevalence, as it can help individuals increase their physical activity levels while providing a more immersive experience. OBJECTIVE: This exploratory study aims to examine the interventional efficacy of at-home immersive VR exergames on metabolic syndrome biomarkers among office workers. Additionally, it seeks to investigate the impacts of at-home immersive VR exergames on the active and sedentary behaviors of office workers. METHODS: A 3-arm, single-blinded pilot randomized controlled trial will be conducted to examine the therapeutic effects of at-home immersive VR exergames. A total of 120 Chinese office workers, engaging in less than 150 minutes per week of moderate to vigorous intensity physical activity, will be recruited via a convenience sampling method. The participants, who will be tested over a 12-week period, will be randomly assigned to one of three groups: (1) the VR exergame intervention group, (2) the regular physical activity control group, and (3) the nonexercise control group. Throughout the 12-week trial, three categories of variables will be collected across the three groups: clinical risk factors associated with metabolic syndrome, active and sedentary behaviors, and demographics. To analyze variance among the groups, a mixed linear model will be applied to assess the efficacy of each group. Differences in metabolic syndrome clinical risk factors among all groups will be used to evaluate the effects of at-home immersive VR exergames. Changes in active and sedentary behaviors will also be used to determine the impacts of VR exergames on metabolic syndrome. RESULTS: The ethics committee of Guangzhou University, China, approved this study on September 25, 2024. Participant recruitment will begin in early 2025 and continue for approximately 3 months. Data will be analyzed after the 12-week trial is completed, with full results expected to be presented in early 2026. CONCLUSIONS: This study explores an emerging topic by applying an at-home immersive VR exergame intervention, potentially contributing to understanding the effects of an exergame program on metabolic syndrome risk among office workers. TRIAL REGISTRATION: ClinicalTrials.gov NCT06556784; https://clinicaltrials.gov/study/NCT06556784. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/64560.
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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 | 0.022 | 0.019 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.068 | 0.010 |
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".