Awe Inducing Elements in Virtual Reality Applications: A Prospective Study of Hospitalized Children and Caregivers.

Background: Hospitalized pediatric patients and their caregivers often experience anxiety and fear, resulting in withdrawal and aggression. Despite virtual reality (VR) being a safe and effective anxiolytic, it is unknown what software design aspects contribute to its effectiveness. This prospective observational study evaluated which VR application elements increased awe, which is correlated with improved behavior and satisfaction. Methods: Patients aged 6 to 25 years and their caregivers at an academic pediatric hospital interacted with a custom VR application that compared design aspects, including environment, graphics fidelity, and presence of a motivational character. Outcomes investigated self-reported awe, vastness, accommodation, and engagement. Data were analyzed using repeated measure ANOVA tests and correlation analyses. Results: A total of 202 participants were enrolled, and 179 (88 pediatric patients, 91 adult caregivers) were included in the final analysis. A fictional environment was more effective at increasing awe in pediatric patients (P = 0.030) compared with a realistic environment. However, increased graphics fidelity was more effective at increasing awe in caregiver adults (P = 0.023) compared with low resolution graphics. Presence of a motivational character did not influence awe in either patients or caregivers (P = 0.432, P = 0.904, respectively). All measures of awe were positively correlated with application engagement (P < 0.005). Conclusion: In conclusion, when software developers design VR software for pediatric patients and their caregivers, fictional settings and increased graphic fidelity should be considered for pediatric patients and adults, respectively. Future studies will explore other VR elements in gameplay settings.

Improving the Generalizability and Performance of an Ultrasound Deep Learning Model Using Limited Multicenter Data for Lung Sliding Artifact Identification.

Deep learning (DL) models for medical image classification frequently struggle to generalize to data from outside institutions. Additional clinical data are also rarely collected to comprehensively assess and understand model performance amongst subgroups. Following the development of a single-center model to identify the lung sliding artifact on lung ultrasound (LUS), we pursued a validation strategy using external LUS data. As annotated LUS data are relatively scarce-compared to other medical imaging data-we adopted a novel technique to optimize the use of limited external data to improve model generalizability. Externally acquired LUS data from three tertiary care centers, totaling 641 clips from 238 patients, were used to assess the baseline generalizability of our lung sliding model. We then employed our novel Threshold-Aware Accumulative Fine-Tuning (TAAFT) method to fine-tune the baseline model and determine the minimum amount of data required to achieve predefined performance goals. A subgroup analysis was also performed and Grad-CAM++ explanations were examined. The final model was fine-tuned on one-third of the external dataset to achieve 0.917 sensitivity, 0.817 specificity, and 0.920 area under the receiver operator characteristic curve (AUC) on the external validation dataset, exceeding our predefined performance goals. Subgroup analyses identified LUS characteristics that most greatly challenged the model's performance. Grad-CAM++ saliency maps highlighted clinically relevant regions on M-mode images. We report a multicenter study that exploits limited available external data to improve the generalizability and performance of our lung sliding model while identifying poorly performing subgroups to inform future iterative improvements. This approach may contribute to efficiencies for DL researchers working with smaller quantities of external validation data.

Control and recalibration of path integration in place cells using optic flow.

Hippocampal place cells are influenced by both self-motion (idiothetic) signals and external sensory landmarks as an animal navigates its environment. To continuously update a position signal on an internal 'cognitive map', the hippocampal system integrates self-motion signals over time, a process that relies on a finely calibrated path integration gain that relates movement in physical space to movement on the cognitive map. It is unclear whether idiothetic cues alone, such as optic flow, exert sufficient influence on the cognitive map to enable recalibration of path integration, or if polarizing position information provided by landmarks is essential for this recalibration. Here, we demonstrate both recalibration of path integration gain and systematic control of place fields by pure optic flow information in freely moving rats. These findings demonstrate that the brain continuously rebalances the influence of conflicting idiothetic cues to fine-tune the neural dynamics of path integration, and that this recalibration process does not require a top-down, unambiguous position signal from landmarks.

Evidence-based clinical practice guideline for the pharmacologic management of acute dental pain in adolescents, adults, and older adults: A report from the American Dental Association Science and Research Institute, the University of Pittsburgh, and the University of Pennsylvania.

BACKGROUND: A panel convened by the American Dental Association Science and Research Institute, the University of Pittsburgh, and the University of Pennsylvania conducted systematic reviews and meta-analyses and formulated evidence-based recommendations for the pharmacologic management of acute dental pain after simple and surgical tooth extraction(s) and for the temporary management (ie, definitive dental treatment not immediately available) of toothache associated with pulp and periapical diseases in adolescents, adults, and older adults. TYPES OF STUDIES REVIEWED: The panel conducted 4 systematic reviews to determine the effect of opioid and nonopioid analgesics, local anesthetics, corticosteroids, and topical anesthetics on acute dental pain. The panel used the Grading of Recommendations, Assessment, Development and Evaluation approach to assess the certainty of the evidence and the Grading of Recommendations, Assessment, Development and Evaluation Evidence-to-Decision Framework to formulate recommendations. RESULTS: The panel formulated recommendations and good practice statements using the best available evidence. There is a beneficial net balance favoring the use of nonopioid medications compared with opioid medications. In particular, nonsteroidal anti-inflammatory drugs alone or in combination with acetaminophen likely provide superior pain relief with a more favorable safety profile than opioids. CONCLUSIONS AND PRACTICAL IMPLICATIONS: Nonopioid medications are first-line therapy for managing acute dental pain after tooth extraction(s) and the temporary management of toothache. The use of opioids should be reserved for clinical situations when the first-line therapy is insufficient to reduce pain or there is contraindication of nonsteroidal anti-inflammatory drugs. Clinicians should avoid the routine use of just-in-case prescribing of opioids and should exert extreme caution when prescribing opioids to adolescents and young adults.

A prospective, observational validation of HRAD±, a novel pediatric affect and cooperation scale.

STUDY OBJECTIVE: HRAD± was developed to quickly assess pediatric perioperative affect and cooperation. HRAD± represents: Happy, Relaxed, Anxious, Distressed, with a yes/no answer to cooperativity. The primary aim of this study was to investigate the clinical utility of HRAD± as an affect and cooperation assessment tool for inhalational mask induction. Secondary aims examined inter-rater reliability (IRR) of HRAD± and predictive validity of induction HRAD± with emergence delirium. DESIGN: This was a prospective observational investigation. SETTING: We conducted this investigation at Lucile Packard Children's Hospital Stanford, an academic, quaternary care children's hospital in Northern California. PATIENTS: A total of 197 patients were included in this investigation. Children 1-14 years of age, who underwent daytime procedures with inhalational induction of anesthesia and American Society of Anesthesiologists physical status I-III were eligible. INTERVENTIONS: During mask induction, two trained research assistants (RAs) independently scored the patient's affect and cooperation. After extubation, the same investigators observed the patient's emergence. MEASUREMENTS: RAs scored each mask induction using the following scales: HRAD±, modified Yale Preoperative Anxiety Scale (mYPAS), Observation Scale of Behavioral Distress (OSBD), and Induction Compliance Checklist (ICC). Correlations were calculated to HRAD±. IRR of HRAD± between the RAs as well as predictive validity of HRAD± to Pediatric Anesthesia Emergence Delirium (PAED), Watcha and Cravero scales were calculated. MAIN RESULTS: HRAD± scores strongly correlated with mYPAS (r = 0.840, p < 0.0001) with moderate correlation to OSBD (r = 0.685, p < 0.0001) and ICC (-0.663, p < 0.0001). IRR was moderate for the affect and cooperation portion of the HRAD± scale, respectively (κ = 0.595 [p < 0.0001], κ = 0.478 [p < 0.0001]). A weak correlation was observed with PAED (r = 0.134 [p = 0.0597]) vs HRAD±. No correlations were observed between Watcha (r = 0.013 [p = 0.8559]) and Cravero and HRAD± scales (r = 0.002 [p = 0.9767]). CONCLUSIONS: HRAD± is a clinically useful and simple scale for evaluating pediatric affect and cooperation during inhalational mask induction. Results demonstrate correlation with commonly utilized research assessment scales.

Reducing Preoperative Caregiver Anxiety With Virtual Reality: A Pragmatic, Randomized Controlled Study.

Pediatric patients and their caregivers often experience perioperative anxiety. Interventions reduce caregiver anxiety improve cooperation and contribute to an improved patient experience. This study seeks to evaluate the efficacy of virtual reality (VR)-assisted mindfulness on perioperative caregiver anxiety. Participants were randomized into a standard of care (SOC) group, which included snacks but no technology-based distractions, or a VR group, which included snacks and a VR-guided meditation. Caregiver anxiety was measured before and after the intervention using the Visual Analogue Scale for Anxiety (VAS-A). Secondary aims explored participants' baseline anxiety with the State-Trait Anxiety Inventory (STAI). VR group participants completed a satisfaction survey. Linear regression models of VAS-A and STAI were used to compare group differences. Satisfaction survey results were reported with descriptive statistics. 26 participants were included, with 12 randomized to the SOC group and 14 to the VR group. VAS-A scores in the VR group were lower than those in the SOC group (p = .002). The STAI found no change in participants' state of anxiety in the SOC group (p = .7108), compared to a significant reduction (p = .014) in the VR group when controlling for anxiety traits. 12 of 14 caregivers in the VR group expressed satisfaction or strong satisfaction. This study supports the implementation of VR mindfulness as a method to reduce caregiver anxiety. VR use in the pediatric healthcare setting is safe and inexpensive, and the intervention had a high degree of participant satisfaction.