Effects of an Exergame Software for Older Adults on Fitness, Activities of Daily Living Performance, and Quality of Life
Bibliographic record
Abstract
Abstract Background: As people become older, the biological process of aging leads to a decline in functional capabilities, which entails difficulties in the performance of daily tasks. Within the “Active and Assisted Living Joint Programme” a consortium from Spain, Germany, and Switzerland developed an interactive Exergame software for older adults to maintain their physical abilities and independence within the daily tasks. Subjects and Methods: An interventional study was conducted to validate the software. For 3 months, Swiss and Spanish seniors used the system at least three times a week for minimum half an hour in their homes. The physical condition in terms of maintaining or increasing strength, balance, safety, and mobility of the seniors was assessed by using the Berg Balance Scale and the Senior Fitness Test. In addition, the effect on independence within the activities of daily living was assessed by using the Canadian Occupational Performance Measure, the Performance Quality Rating Scale, and the Iconographical Falls Efficacy Scale. We used the EQ 5D to evaluate the “quality of life.” Results: Twenty-nine participants (male; n = 14; female; n = 15) completed the study. Scores of endurance (2 minutes step test; P = 0.01, η 2 = 0.3) increased significantly. Moderate effect sizes in quality of life ( r = 0.3), lower body strength (η 2 = 0.08), and large effect sizes in endurance (η 2 = 0.3) were detected. A small effect was evaluated within the gait speed ( r = 0.2), mobility in the lower body ( r = 0.2), and the balance capabilities ( r = 0.2). Conclusion: The results of this study lead us to the conclusion that physical training with activity-focused exergames that are related to the everyday tasks of older adults could help to maintain and improve the individual fitness status.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".