Rethinking the Design of Adolescent Crisis Stabilization Units: A Mixed-Methods Study Using Physical Mock-Up Simulations and Artificial Intelligence
Jafarifiroozabadi, R.; Zhang, C.; Parker, S.; Pankey, V.; Patel, H.; Gautam, N.; Hsu, C.-C.
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Limited research has examined the use of physical mock-ups and artificial intelligence (AI) to evaluate design features in adolescent mental and behavioral health environments, such as the Crisis Stabilization Unit (CSU). This mixed-methods study investigated caregiver workflows and environmental features in adolescent CSUs (e.g., furniture and open vs. enclosed nursing station designs) through physical mock-up simulations with expert and novice clinicians/designers (N = 17). Participants feedback was obtained using questionnaires and focus groups. Simulations were video-recorded, manually coded, and an AI-driven tool was developed for automatic analysis of videos. Findings revealed that experts rated the enclosed nursing station higher in visibility, whereas novice designers reported significantly higher perceived privacy in the open nursing station (P = 0.036). AI-driven video analyses demonstrated promising, high-accuracy performance in automatic detecting, tracking, and localizing individuals (>80%) when compared with manual data. This study proposed an innovative methodology to enhance safety in future adolescent CSUs.
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