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KMID : 0926620230280030027
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Korean Journal of Hospital Management
2023 Volume.28 No. 3 p.27 ~ p.38
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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
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Jung Seung-Won
Hwang Seo-Yeon
Choi Gi-Eun
Jo Eun-Young
Lee Jin-Wook
Nam Ji-Young
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Abstract
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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.
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KEYWORD
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Artificial Intelligence Chatbots, Social presence of chatbots, Trust of chatbot, age difference, gender difference
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