Ongoing shortages of mental health professionals in the USA underscore the need for scalable, technology-mediated supports. Such supports should not only extend access but also preserve core therapeutic ingredients, including human-like conversational scaffolding via AI and immersive, therapy-like contexts via VR. This paper reports on the design and formative pilot evaluation of a low-fidelity prototype for a conceptual AI-based, VR-supported mental health application.
Because the goal was to probe usability and perceptions at an early stage, we used low-fidelity materials to simulate the VR therapy flow and conceptual AI-assisted interactions rather than implementing full AI or VR functionality. Ten young adults with mild to moderately severe depression interacted with the low-fidelity prototype, completed the Usefulness, Satisfaction, and Ease of use questionnaire, and joined semi-structured interviews.
Quantitative ratings indicated that the prototype was learnable and generally acceptable for this population. Thematic analysis of the interviews yielded two broad areas of concern – (1) current mental health care barriers and (2) expectations for AI- and VR-supported therapeutic experiences – which pointed to design needs such as anonymity, culturally sensitive options, lightweight onboarding, and more human-like timing and nonverbal cues. Taken together, these findings suggest that the proposed AI-supported VR concept is understandable and worth further digital prototyping, but future work must move beyond low-fidelity simulations to evaluate real interactions and emotional engagement.
This study demonstrates the feasibility of AI and VR-supported mental health interventions and provides early insights to guide the design of engaging, and accessible digital therapy.
