Feasibility and acceptability of an immersive puzzle-based virtual reality activity for community-dwelling older adults
Bibliographic record
Abstract
Background With the global rise in dementia prevalence, there is a growing interest in accessible, engaging, and preventive interventions for cognitive decline in older adults. Immersive virtual reality (VR) technologies have shown promise for delivering cognitively stimulating activities, yet limited research has examined the feasibility and acceptability of puzzle-based VR interventions among older adults. Objective This study aimed to evaluate the feasibility, usability, and acceptability of an immersive puzzle-based virtual reality (IPVR) intervention using VR Cubism among older adults, including those with mild cognitive impairment (MCI). Methods A single-arm feasibility study was conducted with 14 community-dwelling older adults (mean age = 72.3 years, SD = 5.3; 85.7% female) recruited from senior centers in Texas. Participants completed eight sessions of the IPVR program over 4 weeks. Cognitive screening was conducted using the Montreal Cognitive Assessment (MoCA), with a cutoff score of ≤18 used for exclusion. Usability, acceptability, and technology acceptance were evaluated using the System Usability Scale (SUS), Technology Acceptance and Attitudes Scale (TAAS), and Senior Technology Acceptance Model (STAM), respectively. Results Participants had MoCA scores ranging from 22 to 28 (M = 25.5, SD = 1.9); 50% scored in the normal cognitive range and 50% in the MCI range. The mean SUS score was 71.61 (SD = 15.8), indicating good usability. TAAS scores averaged 5.54/7, reflecting strong acceptability. The mean STAM score was 3.91/5, suggesting moderate to high technology acceptance, although some hesitancy and anxiety were reported. Participants expressed strong interest in using VR for future leisure activities and reported high enjoyment levels during the intervention. Conclusion Findings demonstrate that an immersive puzzle-based VR activity is feasible, usable, and acceptable for community-dwelling older adults, including those with MCI. This study supports the integration of engaging, technology-based interventions to promote cognitive health in aging populations. Practically, VR puzzle programs could be implemented in community centers, senior services, and clinical rehabilitation settings as accessible, enjoyable tools to encourage cognitive stimulation. These results highlight the potential of VR not only as a preventive wellness activity but also as a scalable adjunct to traditional cognitive health programs, warranting further evaluation in larger controlled trials.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".