Korea Journal of Hospital Management (한국병원경영학회지)

Korean Society of Hospital Management (한국병원경영학회)
권호 표지

The association between the social presence and trust of chatbots and the sociodemographic characteristics of artificial intelligence chatbots users in general hospitals : focusing on sex and age

의료기관 인공지능 챗봇 이용자의 인구사회학적 특성과 챗봇의 사회적 실재감 및 신뢰감의 관련성 연구 - 성별과 연령 중심으로

  • Seung Won Jung (Department of Healthcare Management, Eulji University) ;
  • Seo Yeon Hwang (Department of Healthcare Management, Eulji University) ;
  • Gi Eun Choi (Department of Healthcare Management, Eulji University) ;
  • Eun Young Jo (Department of Healthcare Management, Eulji University) ;
  • Jin Wook Lee (Department of Healthcare Management, Eulji University) ;
  • Jin Young Nam (Department of Healthcare Management, Eulji University)
  • 정승원 (을지대학교 의료경영학과) ;
  • 황서연 (을지대학교 의료경영학과) ;
  • 최기은 (을지대학교 의료경영학과) ;
  • 조은영 (을지대학교 의료경영학과) ;
  • 이진욱 (을지대학교 의료경영학과) ;
  • 남진영 (을지대학교 의료경영학과)
  • Received : 2023.07.01
  • Accepted : 2023.09.12
  • Published : 2023.09.30
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Abstract

Objectives: This study explores the impact of age groups on social presence and trust among users of medical artificial intelligence chatbots. Furthermore, we investigate the existence of gender differences within these relationships. Method: We collected data through a survey from people who had interacted with general hospital chatbot services, either by making reservations or seeking consultations. Multiple linear regression analysis was conducted to examine the relationship between general characteristics of study population and social presence and trust of artificial intelligence chatbots. Additionally, we conducted stratified analysis to confirm the presence of gender differences within these relationship. Results: Among 300 participants, those aged 50 and older had higher social presence of artificial intelligence chatbots and greater trust of artificial intelligence chatbots (social presence, 𝛽=0.543, p=0.003; trust, 𝛽=0.787, p=0.000). In stratified by sex, women aged 50 and older had higher social presence and trust of artificial intelligence chatbots compared to those in their 30s age group (social presence, 𝛽 = 0.925, p=0.002; trust, 𝛽=0.645, p=:0.007). However, there was no statistically significant relationship between age and chatbot social presence and trust in men. Conclusion: This study demonstrates that advanced age plays a significant roles in users' social presence and trust in medical artificial intelligence chatbots. Futhermore, our findings reveal gender differences with women aged 50 and older showing the most substantial levels of social presence and trust. Therefore, it is expected that this finding can serve as valuable evidence to enhance the satisfaction of medical institution service users, offering crucial insights into the effective utilization of chatbot services.

Keywords

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