An integrated perspective on the continued use of AI-powered mental healthcare platforms: facilitators and barriers

The growing prevalence of mental health challenges has accelerated the adoption of AI-powered mental health care platforms (such as, “wysa”, “ChatGPT Health”), offering scalable, accessible, and personalized support. While initial adoption has been explored, limited research has addressed the factors influencing users’ continued engagement with these platforms. This study investigates both facilitators and barriers that shape users’ sustained use of AI-powered mental health services. By integrating theoretical perspectives from the “Theory of Consumption Values”, and “Status Quo Bias theory”, we formulated a conceptual model addressing cognitive, emotional, and behavioral components. This model was empirically validated using partial least squares structural equation modelling (PLS-SEM) with data collected from 502 respondents in Bangladesh. The findings reveal that platform quality, expediency value, social value, conditional value, and epistemic value significantly promote continuance intention. Conversely, perceived inertia, perceived threat, and regret avoidance significantly hinder continued use. These insights offer critical implications for designers, developers, and policymakers aiming to enhance user retention and mental health outcomes through AI-powered care solutions.