Older Adults’ Acceptance of a Virtual Reality Group Intervention in Nursing Homes: Pre-Post Study Under Naturalistic Conditions
Bibliographic record
Abstract
Background: Virtual reality (VR) group activities can act as interventions against inactivity and lack of meaningful activities in nursing homes. The acceptance of VR among older adults has been explored from different perspectives. However, research on the impact of older adults' individual characteristics on the acceptance of VR group activities in nursing homes is necessary. Objective: This study investigates the impact of individual characteristics (eg, psychosocial capacities) on VR acceptance among older adults in nursing homes, as well as this group's perceptions of VR after participating in a VR intervention. Methods: In this pre-post study conducted in nursing homes, we applied a VR group intervention with 113 older adult participants. These participants were categorized into two groups based on their naturalistic choice to join the intervention: a higher VR acceptance group (n=90) and a lower VR acceptance group (n=23). We compared the two groups with respect to their sociodemographic characteristics, psychosocial capacities, and attitudes toward new technologies. Additionally, we examined the participants' perceptions of VR. Results: The results show that those with lower acceptance of VR initially reported higher capacities in organizing daily activities and stronger interpersonal relationships compared to older adults with higher VR acceptance. The VR group activity might hold limited significance for the latter group, but it offers the chance to activate older adults with lower proactivity. Openness to new technology was associated with a favorable perception of VR. After the VR intervention, the acceptance of VR remained high. Conclusions: This study investigates the acceptance of VR group events as meaningful activities for older adults in nursing homes under naturalistic conditions. The results indicate that the VR group intervention effectively addressed low proactivity and interpersonal relationship issues among older adults in nursing homes. Older adults should be encouraged to experience VR if the opportunity to participate is offered, potentially facilitated by caregivers or trusted individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".