Journal of the American College of Emergency Physicians open · 2025
Trust of Artificial Intelligence-Augmented Point-of-Care Ultrasound Among Pediatric Emergency Physicians.
СтатьяНазвание и аннотация: Перевод в очереди
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Lin-Martore Margaret, Kornblith Aaron, Firnberg Maytal, Haque Adnan, O'Brien Bridget
Аннотация
OBJECTIVES: Artificial intelligence (AI) may improve many aspects of point-of-care ultrasound (POCUS) for physicians. However, adoption of AI relies on physician trust. Our study seeks to understand factors influencing physician trust in AI-augmented POCUS.
METHODS: From November 2023 to April 2024, we conducted semistructured interviews with academic pediatric emergency medicine (PEM) physicians who use POCUS. The interview guide was sensitized by Yang's proposed framework for user trust in AI and explored participants' perspectives on AI-augmented POCUS. We used template analysis to identify themes. Interviews continued until thematic sufficiency was achieved.
RESULTS: We interviewed 14 PEM physicians across career stages with varying POCUS experience. Participants named several specific aspects of POCUS where AI would be beneficial including image acquisition, image interpretation, and workflow enhancement. We identified themes related to 5 factors perceived as influential in physicians' trust in AI-augmented POCUS: (1) technological-AI-augmented POCUS must be reliable, accurate, transparent, and overridable by the physician; (2) contextual-The technology should be generalizable to the clinical population; (3) user-Each physician's clinical experience, comfort with POCUS, and experiences with technology affect their trust; (4) social/organizational-Endorsements by known colleagues, institutions, and national groups can engender trust although the organization or company creating the AI may have variable influence; (5) environmental-AI is everywhere, and there is subconscious use and acceptance.
CONCLUSION: Technological, contextual, user-related, social, organizational, and environmental factors influenced emergency physician trust in AI-augmented POCUS. Understanding these factors is important for developing AI-augmented POCUS tools.
METHODS: From November 2023 to April 2024, we conducted semistructured interviews with academic pediatric emergency medicine (PEM) physicians who use POCUS. The interview guide was sensitized by Yang's proposed framework for user trust in AI and explored participants' perspectives on AI-augmented POCUS. We used template analysis to identify themes. Interviews continued until thematic sufficiency was achieved.
RESULTS: We interviewed 14 PEM physicians across career stages with varying POCUS experience. Participants named several specific aspects of POCUS where AI would be beneficial including image acquisition, image interpretation, and workflow enhancement. We identified themes related to 5 factors perceived as influential in physicians' trust in AI-augmented POCUS: (1) technological-AI-augmented POCUS must be reliable, accurate, transparent, and overridable by the physician; (2) contextual-The technology should be generalizable to the clinical population; (3) user-Each physician's clinical experience, comfort with POCUS, and experiences with technology affect their trust; (4) social/organizational-Endorsements by known colleagues, institutions, and national groups can engender trust although the organization or company creating the AI may have variable influence; (5) environmental-AI is everywhere, and there is subconscious use and acceptance.
CONCLUSION: Technological, contextual, user-related, social, organizational, and environmental factors influenced emergency physician trust in AI-augmented POCUS. Understanding these factors is important for developing AI-augmented POCUS tools.