Background Virtual reality (VR) has shown promise in reducing children’s pain and anxiety during venipuncture, but studies on VR lack objective observations of pediatric coping. Notably, the process of capturing objective behavioral coping data can be labor- and personnel-intensive. Objective The primary aims of this pilot trial were to assess the feasibility of conducting a trial of VR in a pediatric emergency department and the feasibility of documenting observed coping behaviors during pediatric procedures. Secondarily, this study examined whether VR affects child and caregiver coping and distress during venipuncture in the pediatric emergency department. Methods This stratified, randomized, controlled pilot trial compared coping and distress between child life–supported VR engagement and child life specialist support without VR during painful procedures in children aged 7-22 years in the pediatric emergency department. An external control (reference group) received no standardized support. Primary feasibility outcomes included rates of recruitment, rates of withdrawal from VR, and rates of completed Child Adult Medical Procedure Interaction Scale-Short Form (CAMPIS-SF) observations. Secondary clinical outcomes were applied to venipuncture procedures and included CAMPIS-SF coping and distress (range 0-1.0), pain and anxiety on a visual analog scale (range 0-10), and cybersickness symptoms. Results Overall recruitment was 93% (66/71), VR withdrawal rate was 27% (4/15), and of the completed procedures, 100% (63/63) CAMPIS-SF observations were completed. A total of 55 patients undergoing venipuncture in the pediatric emergency department were included in the analyses of clinical outcomes: 15 patients (15 caregivers) randomized to VR, 20 patients (15 caregivers) randomized to child life specialist support, and 20 patients (17 caregivers) in the reference group. Patient coping differed across groups with higher coping in the VR group and child life specialist group than in the reference group (P=.046). There were no significant differences in the distress and pain ratings for patients and caregivers between the groups. Caregivers rated the lowest perceived anxiety in the child life specialist group (P=.03). There was no apparent change in cybersickness symptoms before and after VR use (P=.37). Conclusions Real-time documentation of observed behaviors in patients and caregivers was feasible during medical procedures in which VR was utilized, particularly with the availability of research staff. VR and child life specialists improved coping in children during venipuncture procedures. Given the high participation rate, future studies to evaluate the efficacy of VR are recommended to determine whether an off-the-shelf VR headset can be a low-cost and low-risk tool to improve children’s coping during venipuncture or other related procedures. Trial Registration ClinicalTrials.gov NCT03686176; https://clinicaltrials.gov/ct2/show/NCT03686176

Ear related concerns and symptoms represent the leading indication for seeking pediatric healthcare attention. Despite the high incidence of such encounters, the diagnostic process of commonly encountered diseases of the middle and external presents a significant challenge. Much of this challenge stems from the lack of cost effective diagnostic testing, which necessitates the presence or absence of ear pathology to be determined clinically. Research has, however, demonstrated considerable variation among clinicians in their ability to accurately diagnose and consequently manage ear pathology. With recent advances in computer vision and machine learning, there is an increasing interest in helping clinicians to accurately diagnose middle and external ear pathology with computer-aided systems. It has been shown that AI has the capacity to analyze a single clinical image captured during the examination of the ear canal and eardrum from which it can determine the likelihood of a pathognomonic pattern for a specific diagnosis being present. The capture of such an image can, however, be challenging especially to inexperienced clinicians. To help mitigate this technical challenge, we have developed and tested a method using video sequences. The videos were collected using a commercially available otoscope smartphone attachment in an urban, tertiary-care pediatric emergency department. We present a two stage method that first, identifies valid frames by detecting and extracting ear drum patches from the video sequence, and second, performs the proposed shift contrastive anomaly detection (SCAD) to flag the otoscopy video sequences as normal or abnormal. Our method achieves an AUROC of 88.0% on the patient level and also outperforms the average of a group of 25 clinicians in a comparative study, which is the largest of such published to date. We conclude that the presented method achieves a promising first step toward the automated analysis of otoscopy video.

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