Impact of Virtual Reality-Delivered Biofeedback and Yoga on Pediatric Headaches: A Pilot Study
Bibliographic record
Abstract
Objectives: This study assessed the feasibility and acceptability of two types of innovative approaches, namely biofeedback-assisted relaxation in virtual reality ([VR]-delivered biofeedback) and yoga in the management of pediatric headaches. The secondary aim was to evaluate the preliminary efficacy of both interventions. Method: Children were randomized to three conditions: waiting list, yoga, and VR-delivered biofeedback. Feasibility was assessed by applicability to the pain problem, and acceptability by attendance (missed sessions, dropout rate) and the use of learned strategies in everyday life. Preliminary efficacy was evaluated with questionnaires: frequency of headaches, functional disabilities, pain anxiety, and pain catastrophizing. Mean scale scores postintervention and two months afterward were compared with the baseline with repeated-measures analyses of variance and contrast analyses. Results: A total of 46 children were enrolled; 39 completed the questionnaires at the baseline and participated in interventions. Regarding feasibility, the safety of the interventions seems demonstrated by the absence or infrequency of headaches during sessions. Regarding acceptability, compliance with the sessions was excellent for VR-delivered biofeedback condition and satisfactory for yoga. Most of the children reported using the strategies learned in daily life, even after the interventions. Regarding efficacy, participants reported significantly fewer headaches and functional disabilities postintervention and 2 months later. Minimal or no effects were observed on pain anxiety and pain catastrophizing. Conclusion: This pilot study indicates that VR-delivered biofeedback and yoga exercises may be feasible and acceptable interventions for the treatment of pediatric headaches. Implications for Impact Statement This study evaluates the feasibility and preliminary efficacy of two innovative interventions for pediatric headaches: virtual reality-delivered biofeedback and yoga exercises. The findings indicate that these interventions are feasible and applicable (good attendance, limited or no discomfort, and positive evaluation) and show preliminary efficacy (improvements in frequency of headaches and functional disabilities).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".