Virtual reality and well-being in older adults: Results from a pilot implementation of virtual reality in long-term care
Bibliographic record
Abstract
Introduction This paper describes the findings of a pilot implementation project that explored the potential of virtual reality (VR) technology in recreational programming to support the well-being of older adults in long-term care (LTC) homes. Methods 32 Adults in four LTC homes participated in a pilot implementation project where they viewed VR experiences of popular locations in Canada created especially for this project. Data in this paper are based on multiple viewing experiences ( n = 102) over a two-week period. Results VR appeared to be an effective distraction from pain for the participants. Participants of this study found the VR experiences to be enjoyable and were relaxed and happy while viewing them. Most participants were attentive or focused while viewing the VR experiences, and the experiences were found to be a source of reminiscence for some of the participants. Participants related well to others around them during a majority of the experiences and the VR experiences were a point of conversation between the staff and the participants. Conclusion The findings from this pilot implementation reveal that VR shows potential to enhance the physical, emotional, cognitive, and social well-being of older adults living in LTC, including those living with cognitive impairment.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".