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

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.

Exploring Early Perceptions and Experiences of ChatGPT in Pediatric Critical Care: A Qualitative Study Among Healthcare Professionals

“…The consensus on ChatGPT's user-friendliness and its conversational, multi-lingual capabilities illustrate an appreciation of the technology's ergonomic design and accessibility. This aligns with the growing trend of AI integration in healthcare, where ease of use is paramount for widespread adoption [35]. However, the participants' perception of ChatGPT as a "limited" source, primarily due to its dependence on pre-existing datasets and the absence of real-time and accurate data updates, highlights a critical aspect of AI in healthcare: the need for continuous AI models in learning and adaptation to verified yet evolving medical knowledge [36].…”

Development and Validation of the eHealth Literacy and Use Scale (eHLUS) to Measure Medical App Literacy.

“…The primary focus of this literature search was on the determinants of digital health applications and Med-Apps. Based on the determinants identi ed in the literature, the eHLUS should be able to ascertain the following factors: Social and cultural factors, [32][33][34] motivation and interest, [34][35][36][37] and accessibility and availability of technology. [38][39][40] The previous process steps made it possible to generate an item pool with 30 items that operationalized the named factors.…”

“…Determinants related to eHealth literacy that may in uence the use of digital health and Med-Apps are described in the literature. These include social and cultural factors, [32][33][34] motivation and interest, [34][35][36][37] as well as the accessibility and availability of technologies. [38][39][40] It is important to consider factors that can affect the use of Med-Apps and are related to eHealth literacy.…”

Development, piloting and evaluation of an app-supported psychosocial prevention intervention to strengthen participation in working life: a study protocol of a mixed-methods approach

“…It also encompasses skills and knowledge to interact productively with technology-enabled health tools 32 33. Other determinants that influence the utilisation of digital health applications include cultural and social factors,33–35 motivation and interest,32 33 36 37 and the accessibility and availability of technology 38–40. Subsequently, there is evidence of a relationship between DHL and adherence to digital health interventions 41 42…”