ArticleJournal of primary care & community health
Development and Evaluation of an AI Avatar Educational Tool for Depression and Anxiety: A Qualitative Pilot Study.
Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Regarding: 'qualitative analysis of out-of-hospital self-management capabilities and ongoing care needs in patients with gynecological malignancies and venous thromboembolism'.Annals of medicine · 2026Article
- How can Patient-Facing Artificial Intelligence Reach People Facing Digital Barriers and Mistrust of Healthcare?Journal of primary care & community healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDepression 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.
objectiveThis 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.
methodsThe 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.
resultsFifteen 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.
conclusionThis 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.