Impact of Virtual Reality–Based Group Activities on Activity Level and Well-Being Among Older Adults in Nursing Homes: Longitudinal Exploratory Study
Bibliographic record
Abstract
BACKGROUND: In addition to illness, inactivity is a risk factor for high mortality in nursing homes. Using innovative technology, such as virtual reality (VR), for meaningful group activities could provide new opportunities for solving this problem. VR interventions have already been approved as a promising method for enhancing the health of older adults. OBJECTIVE: In this study, we examined whether VR-based group activities can have a positive impact on activity level and group interaction among older adults living in nursing homes. METHODS: We conducted a longitudinal study and provided VR interventions as a group activity once a week for 4 consecutive weeks in nursing homes. Participants were recruited based on the experience of the nursing staff members and the natural decisions of the older adults. Within a virtual cottage, designed according to the needs of the target group, older adults were able to perform daily tasks that they were no longer able to do in real life, such as gardening and making pizza. Overall, 2 psychologists measured the psychosocial capacities, activities of daily life, and well-being before and after the interventions using standardized instruments. RESULTS: The results focus on a total of 84 older adults from 14 nursing homes who completed at least 3 VR interventions. The results indicate that several psychosocial capacities among the older adults improved, including adherence to regulations (P<.001; η²=0.122), flexibility (P<.001; η²=0.109), and group integration (P<.001; η²=0.141). Problems related to competence also showed a slight decrease (P=.04; η²=0.039). In addition, the VR intervention promoted their proactivity (P<.001; η²=0.104) and mobility (P=.04; η²=0.039). During the VR group intervention, older adults' well-being could be maintained at a high level. The results highlight the beneficial effects of VR intervention as a meaningful activity in nursing homes, showcasing the potential of VR applications in this setting. CONCLUSIONS: This study provides a novel and naturalistic perspective, offering new insights into the use of VR in nursing homes. The VR intervention was well accepted and fulfilled the aim of enhancing capacity and well-being. It could be a meaningful group activity in nursing homes to improve social group interaction. To provide stronger evidence, randomized controlled trials are necessary.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".