Active Video Games Training for Older Adults: Comparative Study of User Experience, Workload, Pleasure, and Intensity
Bibliographic record
Abstract
Background: Given the appeal of active video games (AVG), many tools are now being used for combined training in older adults. However, there is a lack of comparative data to determine which type of AVG is better suited to older adults. Objective: The purpose of this study was to compare user experience (UX), workload, pleasure, and intensity of three different experiences: (1) an Immersive and Interactive Wall Exergame (I2WE), (2) a consumer device (SWITCH), and (3) a combination of video games and physical stimulation (biking and videogaming, BIKE-VG) for older adults. I2WE and SWITCH are categorized as Moving While Thinking training, meaning that the cognitive task is integrated into the motor or physical task. In contrast, BIKE-VG is categorized as Thinking While Moving training, where the cognitive and motor or physical tasks are not interconnected. The nature of the cognitive, physical, and motor combinations also differentiates them. I2WE is multi-domain training, while BIKE-VG is physical-cognitive training, and SWITCH is motor-cognitive training. Methods: A total of 90 older adults (mean [SD] 69.49 [5.78]) were divided into 3 groups (I2WE, SWITCH, and BIKE-VG). Each participant completed a 45-minute group session and then filled out questionnaires to evaluate UX, workload, pleasure, and intensity. Results: The UX was positive for I2WE and SWITCH, and neutral for BIKE-VG. It was higher for I2WE than for BIKE-VG (t87=2.83; P=.02; d=0.70; 95% CI 0.15-1.69). The workload was moderate across all 3 groups. The intensity was moderate for all groups, ranging between 50% and 70% of the maximum heart rate, and approached high intensity for the I2WE and SWITCH groups. It was significantly higher for I2WE than for BIKE-VG (t66= 2.86; P=.01; d=0.70; 95% CI 1.04-11.43). The perceived pleasure was significantly higher for I2WE (t87=3.63; P=.001; d=0.9;95% CI 2.74-13.23) and SWITCH (t87=3.11; P=.01; d=0.87; 95% CI 1.82-13.69) compared with BIKE-VG. Conclusions: The UX and perceived enjoyment are higher for the Moving While Thinking training compared with the Thinking While Moving training. This indicates that the I2WE and SWITCH training approaches are promising and motivating options for combined training for older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".