Development and Evaluation of an AI Avatar Educational Tool for Depression and Anxiety: A Qualitative Pilot Study

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Abstract
Background: Depression and anxiety affect nearly 1 in 4 Canadians. Traditional patient education materials, such as handouts, are often lengthy and difficult to understand, leading to disengagement. Human-like artificial intelligence (AI) avatars offer a novel way to supplement education by delivering consistent, engaging video content that mimics human interaction and is easily accessible online. Objective: This pilot study aimed to develop a human-like, non-generative AI avatar educational video to support education on antidepressants for patients living with depression and anxiety. The secondary objectives were to evaluate participants perceptions of the tool across 3 domains: credibility, satisfaction, and understanding. Methods: The video was developed through 2 Plan-Do-Study-Act (PDSA) cycles, informed by prior research on patient-reported barriers and enablers to antidepressant use. After viewing the video, participants completed a survey assessing the 3 domains. Success was predefined as ≥60% of participants rating each domain ≥4 on a 5-point Likert scale. Open-ended feedback was summarized descriptively to help inform revisions. Results: Fifteen University Health Network (UHN) Patient Partners participated in PDSA Cycle 1, most with lived experience of depression or anxiety and high digital literacy. Success thresholds were achieved for credibility (75%) and satisfaction (67%) but not for understanding (50%). After revisions, 10 participants from the original group completed PDSA Cycle 2, where all domains exceeded thresholds (credibility 90%, satisfaction 85%, understanding 82%). Participants described the tool as trustworthy, clear, and engaging. Conclusion: This pilot study demonstrated that human-like, non-generative AI avatars can be an effective supplementary educational tool to deliver education on antidepressants for individuals with depression and anxiety. The tool demonstrated acceptability across credibility, satisfaction, and perceived understanding, highlighting its potential to enhance patient engagement and access to reliable information. As a scalable and adaptable format, avatar-based education may extend beyond mental health to other conditions, languages, and clinical settings. Future studies should examine its impact on knowledge retention, treatment adherence, and integration into clinical practice.
Funding Information
  • University Health Network Foundation

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