A Free Virtual Reality Experience to Prepare Pediatric Patients for Magnetic Resonance Imaging: Cross-Sectional Questionnaire Study
Bibliographic record
Abstract
BACKGROUND: A magnetic resonance image (MRI) is a diagnostic test that requires patients to lie still for prolonged periods within a claustrophobic and noisy environment. This can be difficult for children to tolerate, and often general anesthetic (GA) is required at considerable cost and detriment to patient safety. Virtual reality (VR) is a newly emerging technology that can be implemented at low cost within a health care setting. It has been shown to reduce fear associated with a number of high-anxiety situations and medical procedures. OBJECTIVE: The goal of the research was to develop a VR resource to prepare pediatric patients for MRI, helping to reduce anxieties in children undergoing the procedure. METHODS: A freely accessible VR preparation resource was developed to prepare pediatric patients for their upcoming MRI. The resource consists of an app and supporting preparation book and used a series of panoramic 360 degree videos of the entire MRI journey, including footage from within the bore of the scanner. The app, deployed via the Android Play Store and iOS App Store, can be viewed on most mobile phones, allowing a child to experience an MRI in VR using an inexpensive Google Cardboard headset. The app contains 360 degree videos within an animated, interactive VR interface designed for 4 to 12-year-olds. The resource was evaluated as part of a clinical audit on 23 patients (aged 4 to 12 years), and feedback was obtained from 10 staff members. In 5 patients, the resource was evaluated as a tool to prepare patients for an awake MRI who otherwise were booked to have an MRI under GA. RESULTS: The VR preparation resource has been successfully implemented at 3 UK institutions. Of the 23 patients surveyed, on a scale of 1 to 10, the VR resource was rated with a median score of 8.5 for enjoyment, 8 for helpfulness, and 10 for ease of use. All patients agreed that it made them feel more positive about their MRI, and all suggested they would recommend the resource to other children. When considering their experiences using the resource with pediatric patients, on a scale of 1 to 10, the staff members rated the VR resource a median score of 8.5 for enjoyment, 9 for helpfulness, and 9 for ease of use. All staff believed it could help prepare children for an awake MRI, thus avoiding GA. A successful awake MRI was achieved in 4 of the 5 children for whom routine care would have resulted in an MRI under GA. CONCLUSIONS: Our VR resource has the potential to relieve anxieties and better prepare patients for an awake MRI. The resource has potential to avoid GA through educating the child about the MRI process.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".