Virtual Reality Exposure Therapy and Patient Education for Preoperative Anxiety in Pediatrics: Randomized Controlled Trial
Bibliographic record
Abstract
Background: The perioperative environment is complex and may be challenging for patients and guardians to navigate. The emotional burden and stressors inherent to the perioperative process commonly result in preoperative anxiety. Many studies have demonstrated the usefulness of virtual reality (VR) in various patient populations. Objective: The aim of this study is to evaluate the impact of a VR-based preoperative education tool on anxiety levels in pediatric patients undergoing ambulatory ear, nose, and throat surgery, as well as in their guardians. Methods: We performed a single-center prospective randomized controlled trial including children 6-12 years of age, presenting for ambulatory tonsillectomy and/or adenoidectomy, with or without bilateral ear tube insertion. The patients were randomized to receive VR instruction of the perioperative workflow or standard preoperative experience (non-VR). The primary outcome was patient and guardian preoperative anxiety, as measured by the 6-item State-Trait Anxiety Inventory. Results: The study cohort included 107 patient-guardian dyads-51 in the intervention (VR) group and 56 in the control (non-VR) group. Baseline characteristics between the study and control groups were comparable; however, patients in the control group were more likely to report feeling upset compared to the VR group. The VR intervention was associated with reduced preoperative anxiety in patients and guardians compared to the control group. Patients exposed to the VR intervention had higher odds of feeling calm (OR 4.95, 95% CI 2.32-10.61; P<.001) and lower odds of feeling worried (OR 0.25, 95% CI 0.12-0.53; P<.001) compared to the control group. Similarly, guardians in the VR group had higher odds of feeling calm (OR 3.55, 95% CI 1.69-7.49; P=.001) and lower odds of feeling worried (OR 0.45, 95% CI 0.22-0.93; P=.03) compared to the control group. Both patients and guardians exposed to VR were significantly less likely to have moderate or high levels of preoperative anxiety than the control group (patients: OR 0.15, 95% CI 0.05-0.41, P<.001; guardians: OR 0.14, 95% CI 0.06-0.38, P<.001). Conclusions: VR exposure may be effective in reducing pediatric and guardian anxiety. VR may be a suitable alternative to pharmacologic anxiolysis and future studies should compare the effect to premedication techniques.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".