동의신경정신과학회지 (Journal of Oriental Neuropsychiatry)

  • 제35권2호
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  • Pages.153-162
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  • 2024
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  • 1226-6396(pISSN)
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  • 2234-4942(eISSN)
대한한방신경정신과학회 (The Korean Society of Oriental Neuropsychiatry)
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우울증 환자의 자살 위험 평가의 훈련을 위한 생성형 인공지능 챗봇의 의학적 교육 활용 사례: 일개 한의과대학 학생을 중심으로

Utilization of Generative Artificial Intelligence Chatbot for Training in Suicide Risk Assessment of Depressed Patients: Focusing on Students at a College of Korean Medicine

  • 권찬영 (동의대학교 한의과대학 한방신경정신과)
  • Chan-Young Kwon (Department of Oriental Neuropsychiatry, College of Korean Medicine, Dong-eui University)
  • 투고 : 2024.05.19
  • 심사 : 2024.06.18
  • 발행 : 2024.06.30
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초록

Objectives: Among OECD countries, South Korea has been having the highest suicide rate since 2018, with 24.1 deaths per 100,000 people reported in 2020. The objectie of this study was to examine the use of generative artificial intellicence (AI) chatbots to train third-year Korean medicine (KM) students in conducting suicide risk assessments for patients with depressive disorders to train students for their clinical practice skills. Methods: The Claude 3 Sonnet model was utilized for chatbot simulations. Students performed mock consultations using standardized suicide risk assessment tools including Ask Suicide-Screening Questions (ASQ) tool and ASQ Brief Suicide Safety Assessment. Experiences and attitudes were collected through an anonymous online survey. Responses were rated on a 1~5 Likert scale. Results: Thirty-six students aged 22~30 years participated in this study. Their scores for interest and appropriateness (4.66±0.57), usefulness (4.60±0.61), and overall experience (4.63±0.60) were high. Their evaluation of the usability of artificial intelligence chatbot was also high at 4.58±0.70 points. However, their trust in chatbot responses (Q12) was lower (3.86±0.99). Common issues related to dissatisfaction included conversation disruptions due to token limits and inadequate chatbot responses. Conclusions: This is the first study investigating generative AI chatbots for suicide risk assessment training in KM education. Students reported high satisfaction, although their trust in chatbot accuracy was moderate. Technical limitations affected their experience. These preliminary findings suggest that generative AI chatbots hold promise for clinical training, particularly for education in psychiatry. However, improvements in response accuracy and conversation continuity are needed.

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과제정보

This work was supported by Dong-eui University Grant (grant number: 202401260001) and by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HF22C0039).

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