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Determinants of Intentions to Use Digital Mental Healthcare Content among University Students, Faculty, and Staff: Motivation, Perceived Usefulness, Perceived Ease of Use, and Parasocial Interaction with AI Chatbot

Author

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  • Daniel Y. Park

    (HY Digital Healthcare Center, Hanyang University, Seoul 04763, Republic of Korea)

  • Hyungsook Kim

    (HY Digital Healthcare Center, Hanyang University, Seoul 04763, Republic of Korea
    Department of Cognitive Sciences, School of Intelligence, Hanyang University, Seoul 04763, Republic of Korea
    Graduate School of Public Policy, Hanyang University, Seoul 04763, Republic of Korea)

Abstract

Depression is a worldwide health issue to which various physical, psychological, and social health problems are attributable. To address the issue through the promotion of digital mental healthcare content use, this study examines factors influencing people’s intentions to use the content, guided by the technology acceptance model and uses and gratifications theory. A total of 278 students and faculty/staff members at a Korean university tried using a digital mental healthcare content (e.g., artificial intelligence chatbot content) called MyMentalPocket and completed a survey questionnaire associated with their perceptions of the content. Participants’ depression levels, perceived usefulness, and parasocial interactions emerged as significant and positive factors influencing people’s intentions to use MyMentalPocket. Female gender, younger age, and specific motives for depression-related digital technology use (i.e., communication and emotional support, information- and guidance-seeking, and habitual entertainment-seeking motives) emerged as significant and positive factors influencing parasocial interactions. Parasocial interactions and perceived ease of use emerged as significant and positive factors influencing perceived usefulness. The findings from this study imply the utility of AI chatbots as a way to help people, especially females and younger people with depression and interpersonal difficulties, to utilize and benefit from digital mental healthcare content for depression management.

Suggested Citation

  • Daniel Y. Park & Hyungsook Kim, 2023. "Determinants of Intentions to Use Digital Mental Healthcare Content among University Students, Faculty, and Staff: Motivation, Perceived Usefulness, Perceived Ease of Use, and Parasocial Interaction w," Sustainability, MDPI, vol. 15(1), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:1:p:872-:d:1024101
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    References listed on IDEAS

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    1. Kwang-Hi Park & Hyunlye Kim & Jaehee Kim, 2020. "Moderating Effect of Mindfulness on the Influence of Stress on Depression According to the Level of Stress among University Students in South Korea," IJERPH, MDPI, vol. 17(18), pages 1-11, September.
    2. Porter, Constance Elise & Donthu, Naveen, 2006. "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics," Journal of Business Research, Elsevier, vol. 59(9), pages 999-1007, September.
    3. Ella Zomer & YongJoo Rhee & Danny Liew & Zanfina Ademi, 2021. "The Health and Productivity Burden of Depression in South Korea," Applied Health Economics and Health Policy, Springer, vol. 19(6), pages 941-951, November.
    4. Se Jin Park & Soo Yeon Kim & Eun-Sun Lee & Subin Park, 2020. "Associations among Employment Status, Health Behaviors, and Mental Health in a Representative Sample of South Koreans," IJERPH, MDPI, vol. 17(7), pages 1-12, April.
    5. Sokolova, Karina & Perez, Charles, 2021. "You follow fitness influencers on YouTube. But do you actually exercise? How parasocial relationships, and watching fitness influencers, relate to intentions to exercise," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    6. Alvarez, R. Michael & Atkeson, Lonna Rae & Levin, Ines & Li, Yimeng, 2019. "Paying Attention to Inattentive Survey Respondents," Political Analysis, Cambridge University Press, vol. 27(2), pages 145-162, April.
    7. Conal Twomey & Gary O’Reilly & Oliver Bültmann & Björn Meyer, 2020. "Effectiveness of a tailored, integrative Internet intervention (deprexis) for depression: Updated meta-analysis," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-14, January.
    8. Ying-Kai Liao & Wann-Yih Wu & Trang Quang Le & Thuy Thi Thu Phung, 2022. "The Integration of the Technology Acceptance Model and Value-Based Adoption Model to Study the Adoption of E-Learning: The Moderating Role of e-WOM," Sustainability, MDPI, vol. 14(2), pages 1-16, January.
    9. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
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