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Record W4393389670 · doi:10.2196/48959

Use of Biofeedback-Based Virtual Reality in Pediatric Perioperative and Postoperative Settings: Observational Study

2024· article· en· W4393389670 on OpenAlexvenueno aff
Zandantsetseg Orgil, Anitra Karthic, Nora F Bell, Lisa M. Heisterberg, Sara E. Williams, Lili Ding, Susmita Kashikar‐Zuck, Christopher D. King, Vanessa A. Olbrecht

Bibliographic record

VenueJMIR Perioperative Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
FundersNational Center for Complementary and Integrative HealthNational Institutes of Health
KeywordsBiofeedbackVirtual realityAnxietyPreprintPhysical therapyObservational studyPerioperativeMedicinePsychologyPhysical medicine and rehabilitationComputer scienceHuman–computer interactionAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Biofeedback-based virtual reality (VR-BF) is a novel, nonpharmacologic method for teaching patients how to control their breathing, which in turn increases heart rate variability (HRV) and may reduce pain. Unlike traditional forms of biofeedback, VR-BF is delivered through a gamified virtual reality environment, increasing the accessibility of biofeedback. This is the first study to systematically integrate VR-BF use in the pediatric perioperative setting, with the ultimate goal of evaluating the efficacy of VR-BF to reduce pain, anxiety, and opioid consumption once feasibility and acceptability have been established. OBJECTIVES: The primary objective was to develop a clinical trial protocol for VR-BF use in the pediatric perioperative setting, including preoperative education and training, and postoperative application of VR-BF in children undergoing surgery. A secondary objective was to evaluate the patient and parent experience with VR-BF. METHODS: A total of 23 patients (12-18 years of age) scheduled for surgery at Nationwide Children's Hospital were recruited using purposive sampling. Following training, participants independently completed a daily, 10-minute VR-BF session for 7 days before surgery and during their inpatient stay. Participants could use VR-BF up to 2 weeks after hospital discharge. Patient- and session-level data of VR-BF usage and achievement of target HRV parameters were measured to identify the optimal frequency and duration of sessions before and after surgery for this population. Standardized questionnaires and semistructured interviews were conducted to obtain qualitative information about patients' experiences with VR-BF. RESULTS: Patient-level data indicated that the highest odds of achieving 1 session under target HRV parameters was after 4 sessions (odds ratio [OR] 5.1 for 4 vs 3 sessions, 95% CI 1.3-20.6; OR 16.6 for 3 vs 2 sessions, 95% CI 1.2-217.0). Session-level data showed that a session duration of 9 to 10 minutes provided the greatest odds of achieving 1 session under target HRV parameters (OR 1.3 for 9 vs 8 min, 95% CI 1.1-1.7; OR 1.4 for 8 vs 7 min, 95% CI 1.1-1.8; OR 1 for 10 vs 9 min, 95% CI 0.9-1.2). Qualitative data revealed patient satisfaction with the VR-BF technology, particularly in managing perioperative stress (17/20, 85%). Few patients reported VR-BF as beneficial for pain (8/20, 40%). CONCLUSIONS: Children and adolescents undergoing surgery successfully learned behavioral strategies with VR-BF with 10-minute sessions once daily for 5 days. To integrate VR-BF as a therapeutic intervention in a subsequent clinical trial, patients will be instructed to complete three 10-minute sessions a day for 7 days after surgery. TRIAL REGISTRATION: ClinicalTrials NCT04943874; https://clinicaltrials.gov/ct2/show/NCT04943874.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.103
GPT teacher head0.378
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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