Chapter 7: Adoption of AI-Driven Mental Health Apps Among the Younger Generation: An Extended Technology Acceptance Model (TAM) Approach

This study investigates the factors influencing the adoption of Artificial Intelligence (AI)-driven mental health applications among younger generations, focusing on Gen Z and Millennials. By extending the Technology Acceptance Model (TAM) with additional constructs such as trust, social influence (SI), hedonic motivation (HM) and price value, the research provides a deeper understanding of the drivers behind attitudes and intentions toward using these apps. Primary data were gathered through a questionnaire targeting Gen Z and Millennials, and the analysis was conducted using structural equation modelling (SEM). The findings reveal that perceived ease of use, HM and trust significantly enhance attitudes toward using AI-based mental health apps, while perceived usefulness does not directly affect attitudes or intentions. Additionally, attitude serves as a mediator between factors like ease of use and HM and the intention to adopt these applications. The study underscores the critical role of trust and SI in increasing adoption rates. Developers are encouraged to prioritise data privacy and transparency to build user trust. These insights are valuable for app developers, healthcare providers and policymakers aiming to promote the acceptance of AI-based mental health solutions. Future research should expand the demographic scope and employ longitudinal studies to better understand changing user behaviours over time.