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Review highlights the need for adaptive guidance improvements in pediatric emergency settings, emphasizing cognitive load and performance outcomes.
Purpose of Review Pediatric emergencies in general and community hospitals, where most children are seen, are infrequent and cognitively demanding, and deviation from resuscitation algorithms is common despite certification. This review treats that as a failure of execution under load rather than a knowledge deficit, and reads together two separately developed literatures: head-mounted augmented reality (AR) guidance, which externalizes the algorithm, and real-time physiological sensing, which estimates the clinician’s cognitive state. Recent Findings Controlled trials of head-mounted guidance report improved guideline adherence and fewer dosing errors in simulation, but effects are inconsistent across outcomes, samples are small, endpoints are process measures, and some interventions slow performance or raise workload. Cognitive-state classification is accurate within individuals but generalizes poorly across them, and the signals index arousal and effort rather than load. The adaptive combination has been proposed but never tested. Summary Adaptive guidance needs controlled comparison against static guidance with cognitive load and performance as co-primary outcomes, models that generalize across clinicians, and patient-level rather than simulation-only endpoints.
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Prabhu et al. (2026) studied this question.
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