Virtual Reality Meditation for Fatigue in Persons With Rheumatoid Arthritis: Mixed Methods Pilot Study
Bibliographic record
Abstract
BACKGROUND: Effective symptom management is crucial to enhancing the quality of life for individuals with chronic diseases. Health care has changed markedly over the past decade as immersive, stand-alone, and wearable technologies including virtual reality have become available. One chronic pain population that could benefit from such an intervention is individuals with rheumatoid arthritis (RA). Recent pharmacologic advances in the management of RA have led to a decrease in inflammatory symptoms (eg, chronic pain) or even disease remission, yet up to 70% of patients with RA still suffer from fatigue. While VR-delivered behavior, meditation, and biofeedback programs show promise for pain and anxiety management, there is little information on the use of virtual reality meditation (VRM) for fatigue management among individuals with RA. OBJECTIVE: This study aims to (1) examine the feasibility of implementing a study protocol that uses VRM, (2) determine the acceptability of using VRM for fatigue management in an outpatient population, and (3) identify barriers and contextual factors that might impact VRM use for fatigue management in outpatients with RA. METHODS: We used a convergent, mixed methods design and enrolled adults aged 18 years or older with a clinical diagnosis of RA. Patient-Reported Outcome Measure Information System (PROMIS) measures of fatigue, depression, anxiety, pain behavior, and physical function were assessed alongside the brief mood introspection scale at baseline and weekly for 4 weeks. VRM use across the 4-week study period was automatically stored on headsets and later extracted for analysis. Semistructured interview questions focused on feedback regarding the participant's experience with RA, previous experience of fatigue, strategies participants use for fatigue management, and the participant's experience using VRM and recommendations for future use. RESULTS: A total of 13 participants completed this study. Most participants completed all study surveys and measures (11/13, 84% and 13/13, 100%, respectively) and were active participants in interviews at the beginning and end of the program. Participants used VRM an average of 8.9 (SD 8.5) times over the course of the 4-week program. Most participants enjoyed VRM, found it relaxing, or recommended its use (12/13, 92%), but 8 (62%) noted barriers and conceptual factors that impacted VRM use. On average, participants saw decreases in PROMIS fatigue (-6.4, SD 5.1), depression (-5.6, SD 5.7), anxiety (-4.5, SD 6), and pain behavior (-3.9, SD 5.3), and improvements in PROMIS physical function (1.5, SD 2.7) and Brief Mood Introspection Scale mood (5.3, SD 6.7) over the course of this 4-week study. CONCLUSIONS: While this study's implementation was feasible, VRM's acceptability as an adjunctive modality for symptom management in RA is contingent on effectively overcoming barriers to use and thoughtfully addressing the contextual factors of those with RA to ensure successful intervention deployment. TRIAL REGISTRATION: ClinicalTrials.gov NCT04804462; https://classic.clinicaltrials.gov/ct2/show/NCT04804462.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".