People with dementia as exercise video game testers: Gathering end‐user perspectives
Bibliographic record
Abstract
Abstract Background Commercially available exercise video games (‘exergames') can be used by people with dementia with the right (human) prompting and support. However, more information is needed about what makes these systems and games technologically accessible for this population, considering their cognitive difficulties. This study explores what works and doesn’t work for people with dementia when introducing new exergame systems and games to broaden opportunities for physical activity. Methods Thirty‐two people living with dementia (mean Montreal Cognitive Assessment score: 12.75/30) were recruited from four community‐based adult day programs in Canada. Participants were recruited as ‘game testers' once weekly for six weeks at each day program. Participants with dementia tried different exergame systems (e.g., Xbox Kinect, Nintendo Switch) and games (e.g., darts, boxing, dancing, etc.). Concurrently, gameplay video recordings and feedback via the talk‐aloud protocol and audio‐recorded post‐game group debriefs were collected. Data were analyzed descriptively and are currently undergoing analysis using behavioural coding software to examine in‐game prompts and player movements. Results In total, 292 gameplay turns occurred across the sessions. Some participants declined to play certain games after watching their peers experience accessibility challenges. Common reasons for ending a turn (beyond completing the game objective) included boredom, frustration, confusion, fatigue, and soreness. Systems with handheld controllers (e.g., Nintendo Wii) were less accessible for participants than gesture‐based controls due to the need to push buttons and attend to the controller while simultaneously performing physical motions. Additionally, games requiring multiple coordinated movements and those not accommodating additional age‐related impairments (e.g., range of motion impairments, mobility devices) were not widely accessible to this diverse group of participants. Conclusions This study highlights the importance of involving people living with dementia in game development. The findings reveal which elements of current exergames make them accessible or inaccessible for people living with dementia. These findings can help design new exergames to increase access to physical activity for people with dementia. The findings will also interest dementia service providers who want to use exergames to increase physical activity for people with dementia.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".