The Efficacy of Virtual Reality Game Preparation for Children Scheduled for Magnetic Resonance Imaging Procedures (IMAGINE): Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: It is known that magnetic resonance imaging (MRI) procedures generate fear and anxiety. Children may become restless during scanning, which results in movement artifacts requiring the MRI procedure to be repeated with sedation. Few studies seem to have looked at the effect of immersive virtual reality (IVR) on anxiety in children scheduled for MRI scans and how to identify which children are more responsive. OBJECTIVE: The aims of this study are 3-fold: develop an algorithm of predictability based on biofeedback, address feasibility and acceptability of preprocedural IVR game preparation for anxiety management during MRI procedures, and examine the efficacy of IVR game preparation compared with usual care for the management of procedural anxiety during MRI scans. METHODS: This study will have 2 phases. We will first conduct a field test with 10 participants aged 7 to 17 years to develop a predictive algorithm for biofeedback solution and to address the feasibility and acceptability of the research. After the field test, a randomized controlled trial will be completed using a parallel design with 2 groups: an experimental group (preprocedural IVR game preparation) and a usual care group (standard care as per the radiology department's protocol) in an equal ratio of 49 participants per group for 98 participants. Recruitment will be carried out at a hospital in Quebec, Canada. The experimental group will receive a preprocedural IVR game preparation (IMAGINE) that offers an immersive simulation of the MRI scan. Participants will complete a questionnaire to assess the acceptability, feasibility, and incidence of side effects related to the intervention and the biofeedback device. Data collected will include sociodemographic and clinical characteristics as well as measures of procedure-related anxiety with the French-Canadian version of the State-Trait Anxiety Inventory for Children (score 1-3) and the Children's Fear Scale (score 0-4). Physiological signs will be noted and include heart rate, skin conductance, hand temperature, and muscle tension. Measures of the level of satisfaction of health care professionals, parents, and participants will also be collected. Analyses will be carried out according to the intention-to-treat principle, with a Cronbach α significance level of .05. RESULTS: As of May 10, 2022, no participant was enrolled in the clinical trial. The data collection time frame is projected to be between April 1, 2022, and March 31, 2023. Findings will be disseminated through peer-reviewed publications. CONCLUSIONS: Our study provides an alternative method for anxiety management to better prepare patients for an awake MRI procedure. The biofeedback will help predict which children are more responsive to this type of intervention. This study will guide future medical practice by providing evidence-based knowledge on a nonpharmacological therapeutic modality for anxiety management in children scheduled for an MRI scan. TRIAL REGISTRATION: ClinicalTrials.gov NCT04988516; https://clinicaltrials.gov/ct2/show/NCT04988516. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30616.
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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 | 0.030 | 0.033 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.049 | 0.007 |
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".