Comparing a Virtual Reality–Based Simulation App (VR-MRI) With a Standard Preparatory Manual and Child Life Program for Improving Success and Reducing Anxiety During Pediatric Medical Imaging: Randomized Clinical Trial
Bibliographic record
Abstract
Background The experience of undergoing magnetic resonance imaging (MRI) can be anxiety provoking, particularly for pediatric patients and their families. Alternative methods to improve success and experiences without the use of sedation are needed. Objective This study aims to compare the effectiveness of a virtual reality (VR)—based simulation app (VR-MRI) with a standard preparatory manual (SPM) and a hospital-based Child Life Program (CLP) on success and anxiety during a simulated pediatric MRI scan. Our secondary aim is to compare caregivers’ reported anxiety, procedural data, caregiver usability, child satisfaction, and fun. Methods This unblinded, randomized, triple-arm clinical trial involved 92 children aged 4-13 years and their caregivers. Recruitment was conducted through posters, public libraries, community centers, and social media. At a 2-hour session, participants were instructed to prepare for a simulated MRI head scan using one of three randomly assigned preparation materials: the VR-MRI app, SPM, or the CLP. Data were collected before preparation, during a simulated MRI head scan, and after the simulated scan. The primary outcomes were the success of the simulated MRI scan (MoTrak head motion tracking system), and child-reported anxiety (Venham picture test). We secondarily measured caregivers’ reported anxiety (short State-Trait Anxiety Inventory), procedural data (minutes), usability (Usefulness, Satisfaction, and Ease of Use Questionnaire), and child-reported satisfaction and fun (visual analog scales). Results A total of 84 participants were included in the final analysis (VR-MRI: 30/84, 36%; SPM: 24/84, 29%; and CLP: 30/84, 36%). There were no clinically significant differences between the groups in terms of success during the MRI simulation (P=.27) or the children’s reported anxiety at any timepoint (timepoint 1, P=.99; timepoint 2, P=.008; timepoint 3, P=.10). Caregivers reported being significantly more anxious after preparing with the manual than caregivers in the other 2 groups (P<.001). Child and caregiver anxiety had a significant relationship, increasing together with moderate effect (r84=0.421; P<.001). Participants using VR-MRI took the most time to prepare (P<.001) and participants using the manual took the least time (P<.001). No statistically significant relationships were found between time preparing and time completing the simulated assessment (P=.13). There were no differences found in ease of use (P=.99), ease of learning (P=.48), and usefulness (P=.11) between the groups; however, caregivers reported being significantly more satisfied with the VR-MRI app and CLP than SPM (P<.001). Children reported the most satisfaction with the CLP (P<.001). There were no differences in how much fun the preparation materials were perceived to be (P=.37). Conclusions Digital preparation experiences using VR-based media could be a viable solution to improve the success of nonsedated MRI scans, with outcomes comparable with hospital-based in-person preparatory programs. Future research should focus on validating the results in a real MRI setting. Trial Registration Clinicaltrials.gov NCT03931382; https://clinicaltrials.gov/ct2/show/NCT03931382
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.044 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".