P099 Attention-based Virtual Reality - A Safe, Acceptable and Potentially Highly Effective Treatment for Fibromyalgia Syndrome: Findings from The VIPA Study
Bibliographic record
Abstract
Abstract Background/Aims Chronic pain is highly prevalent and a leading cause of disability worldwide with a crippling socioeconomic cost. Current non-pharmacological management of conditions including Fibromyalgia Syndrome (FMS) are labour intensive to implement and not widely available. There is an urgent need to develop accessible, innovative treatments for pain cohorts. Virtual reality (VR) is a modern technology that immerses users within a three-dimensional, interactive virtual environment delivered through a head-mounted display. VR is widely used for acute pain, following multiple randomised controlled trials showing efficacy. Despite growing numbers of feasibility studies and a handful of larger clinical trials, robust evidence within chronic pain cohorts including FMS is still limited. Through the VIPA Study, we investigated the impact of different VR characteristics on acceptability and pain using multiple feasibility studies in patients with FMS. Methods Patients with FMS were recruited through outpatient clinics at the Norfolk and Norwich University Hospital. We investigated four VR systems representing the spectrum of commercially available technologies. Participants used each system in a random order for five minutes. The interactive VR program experienced with each headset was co-developed alongside industry partners specifically for patients with chronic pain. Baseline questionnaires included the McGill pain questionnaire short form (MPQ-SF; total score: 0-45), pain visual analogue scale (VAS; 0-10) and Revised Fibromyalgia Impact Questionnaire (FIQR; total score: 0-100). MPQ-SF and VAS data were also collected approximately 15 minutes after use of the fourth headset (post-intervention). Questionnaires collected acceptability data using 7-point Likert scale rating questions (1=strongly disagree to 7=strongly agree). The VR sickness questionnaire (VRSQ) gained side-effect data (total severity score: 0-100). Results 26 participants with FMS were included (mean (SD) age 48 ±14yrs, 88% female). Disease severity ranged from moderate to extreme (mean FIQR 65 ±16). Following use of all headsets, a 40% reduction in mean MPQ-SF total scores from baseline were reported (baseline 24 ±9, post-intervention 15 ±9, p = <0.001). A 24% reduction in mean pain VAS was observed (baseline 5.5 ±1.9, post-intervention 4.0 ±1.9, p = <0.001) with one participant reporting an 80% reduction (change in VAS: 5.9). Participants indicated high levels of acceptability across VR systems when asked about comfort, quality, usability and immersion (mean total headset score ranged from 77-97 out of 105). Side effects were infrequent and mild (mean total VRSQ score across devices: 17 ±12). 100% agreed they would be open to using VR regularly at home for pain management (mean rating 6.5 ±0.6). Conclusion Patients with FMS can experience large reductions in pain following VR, find the technology acceptable with limited side effects, and are open to home use for pain management. VR has enormous potential as an accessible, home-based treatment for chronic pain. VIPA provides strong justification for future RCTs investigating efficacy and dose-response. Disclosure J. Tsigarides: Grants/research support; J.T. has received a small amount of funding from Orbital Global Ltd to support research equipment purchase for The VIPA Study. V. Grove: None. N. Shenker: None. J. Dainty: None. J. Chipping: None. S. Miles: None. S. Sami: None. A. MacGregor: None.
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 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".