Physical and Affective Physical Literacy Domains Improved After a Six-Week Exergame Exercise Program in Older Adults: A Randomized Controlled Clinical Trial
Bibliographic record
Abstract
Introduction: We investigated the effects of an exergames-based exercise program for older adults, and its benefits on their physical literacy (PL) domains, such as physical (mobility skills), affective (motivation and confidence), cognitive (knowledge about physical activity [PA]), and behavioral (daily exertion) when compared with a conventional exercise program and no training (NT) (control). Material and Methods: Forty older adults (mean age 72 years) volunteered and were randomized within three groups—exergame training (ET; n = 15), conventional training (CT; n = 14), and NT ( n = 11). ET group performed training sessions based on a commercially available exergame console, while the CT group enrolled in a convention exercise program (aerobic, strength, balance, and flexibility exercises). The training program was conducted three times a week for 6 weeks. The Timed Up and Go Test (TUG), Exercise Confidence Survey (ECS), Motives for Physical Activity Measure-Revised (MPAM-R), Knowledge and Understanding Questionnaire (K&UQ), and total PA tracking (using wearable technology) were used as the study's outcomes. Outcome variables were measured at preintervention (week 0), postintervention (week 6), and at the time of final follow-up (week 9). Results: We observed a reduction in the ET TUG time at postintervention and follow-up. Also, a significant main effect for group and moment of measurement was observed for the Fitness-Health subscore, derived from MPAM-R. The values demonstrated by ET and CT were statistically different ( P = 0.01) and a within-group comparison revealed significant differences in the ET from preintervention to both postintervention and follow-up (both, P = 0.01). We did not observe any other significant difference. Conclusion: Our results suggest that a 6-week exergame-based training program may have the potential in improving the physical and affective domains of PL in community-dwelling older adults. The topics related to fitness and health seem to be of interest in this population and programs can make use of them to improve the PL domains.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".