Effects of Competitive Exergaming–Based Esports on Older Adults in Hong Kong: Nonrandomized Controlled Pilot Study
Bibliographic record
Abstract
Background Hong Kong faces a rapidly aging population, with many older adults not meeting recommended physical-activity levels and struggling to maintain long-term exercise adherence. Exergaming offers an accessible, technology-supported way to promote health conditions while providing immediate feedback and task variability among older adults. Objective This study aimed to evaluate the effects of an 8-week competitive exergaming intervention on functional fitness, cognition, loneliness, physical activity (PA) enjoyment, and quality of life among community-dwelling older adults in Hong Kong. Methods We conducted a pragmatic, nonrandomized, 2-group pilot with community participants allocated to either a competitive exergaming group (EG) or a passive control group (CG). EG attended 16 instructor-led 90-minute sessions playing Fitness Boxing (Nintendo Switch), including head-to-head bouts and a bracketed tournament. Outcomes were assessed at baseline and postintervention. Primary analyses used repeated-measure analysis of covariance (time: pre and post; group: EG and CG) adjusted for age, sex, education, marital status, employment, financial status, and housing. Partial η2 was used to quantify effect sizes. Given the pilot nature, P values are unadjusted for multiplicity and interpreted cautiously. Results A total of 48 older adults completed assessments (EG: n=24; mean age 69.50, SD 4.77 years; CG: n=24; mean age 71.50, SD 6.74 years). Significant group × time interactions favored EG for lower-body strength (30-second chair stand: F1, 48=12.39; P<.001; partial η2=0.22), aerobic endurance (2-minute step: F1, 48=4.89; P=.03; η2=0.10), and PA enjoyment (Physical Activity Enjoyment Scale: F1, 48=9.36; P<.001; η2=0.18). For the Number Comparison Test (processing speed), the group × time interaction was not significant (P=.08); however, an exploratory main effect of group indicated higher performance in EG across time (P=.04). Executive function (Trail Making Test parts A and B), loneliness, and Short Form-36 Health Survey subscales showed no significant effects. Conclusions Competitive exergaming was feasible and produced small to moderate improvements in lower-body strength, aerobic endurance, and enjoyment of PA. Cognitive effects were inconclusive and should not be overinterpreted given the nonrandomized design, passive control, small sample, and multiple outcomes. Future randomized trials with active comparators and longer duration are warranted.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".