Feasibility and Efficacy of Commercial-Off-the-Shelf Virtual Reality Applications for Managing Chronic Pain and Enhancing Well-Being Among Older Adults in the Community: Mixed Methods Pilot Study
Bibliographic record
Abstract
Background: Older adults may experience chronic pain as they age, which can affect their physical and psychological well-being. Virtual reality (VR) is emerging as a novel and nonpharmacological intervention that offers pain relief and mood enhancement through immersive experiences. However, the feasibility and effectiveness of using nonlocalized and commercial VR applications for chronic pain relief and mood enhancement among community-dwelling older adults remain underexplored. Objective: The main objectives of this study were to (1) evaluate the feasibility of using commercial-off-the-shelf VR applications for managing chronic pain among older adults, (2) assess the efficacy of VR in alleviating chronic pain, and (3) examine its impact on the well-being of older adults in a community setting. Methods: The study was a single-arm mixed methods pilot study. It was divided into two stages, including preparation and implementation. A total of 13 older adults (8 with chronic pain and 5 without) were recruited to participate in a 3-week VR intervention. Participants engaged in VR sessions that followed a step-by-step adaptation process. Each session included 360-degree relaxation videos and VR-based boxing exercises via Les Mills BODYCOMBAT, lasting 15 minutes. Pain intensity, pain self-efficacy, well-being, and mood were measured pre- and post-intervention using the Numeric Pain Rating Scale (NPRS), a pain self-efficacy question, the World Health Organization-Five Well-Being Index (WHO-5), and the Mood Assessment Scale (Mood). VR feasibility was evaluated based on completion rates, adverse outcomes, and qualitative feedback from semistructured interviews. Results: Of the 13 participants recruited, 11 completed the intervention (84.6% completion rate). The mean age was 79.2 (SD 9.2) years. The study found a statistically significant 16.32% improvement in the mean mood score, with a mean increase of 2.64 (SD 1.45) points and a large effect size (P<.001; Cohen d=1.82). The median pain self-efficacy score decreased from 3.0 (IQR 1.5-3.0) to 1.0 (IQR 1.0-2.0) (z=-2.236; P=.03). However, no significant changes were observed in pain intensity or overall well-being. The study demonstrated the high feasibility of commercial-off-the-shelf VR technology for older adults. Minor adverse effects were reported, including back pain and headset discomfort. In addition, 90.9% of participants enjoyed the VR experience, and all were willing to join future sessions. Conclusions: The pilot study demonstrated that commercial-off-the-shelf VR applications can effectively enhance mood and pain self-efficacy. Additional procedures, such as prebriefing, real-time interpretation, and a gradual adaptation process, were essential to overcoming barriers such as language, cultural nuances, and the digital literacy of older adults. Despite the lack of significant changes in pain intensity or overall well-being, the psychological benefits suggest that VR could be a valuable adjunct tool in chronic pain management. Future research should focus on larger sample sizes, longer intervention durations, randomized controlled trials, and the development of localized commercial VR applications to further explore their efficacy.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".