Artificial intelligence is increasingly being used to deliver motivational interviewing (MI), a counseling method that helps individuals change health behaviors such as quitting smoking or increasing exercise. While MI has shown effectiveness in healthcare, its use remains limited due to barriers like time constraints and the need for specialized training.
Researchers at Florida Atlantic University’s Charles E. Schmidt College of Medicine have conducted what they describe as the first scoping review of AI-driven systems designed to provide motivational interviewing. Their study, published in the Journal of Medical Internet Research, examined how chatbots, virtual agents, and mobile apps are being used to deliver MI and assessed their usability, acceptability, adherence to MI principles, and reported outcomes.
The review found that most AI tools used for this purpose were chatbots, with some employing advanced language models such as GPT-3.5 and GPT-4. These digital interventions aim to simulate the supportive conversations central to motivational interviewing. However, the quality of evaluation across studies varied significantly. Only a small number addressed safety concerns related to AI-generated content or detailed measures taken against misinformation.
According to Maria Carmenza Mejia, M.D., senior author and professor of population health at Schmidt College of Medicine, “Many digital interventions included motivational ‘elements’ but didn’t clearly show if or how they follow formal MI practices.” She added, “We carefully mapped the specific techniques used – like open-ended questions, affirmations, and reflective listening – and looked at how fidelity was assessed, whether through expert review or study design. This level of detail is essential to understand what these AI tools are actually doing and how well they mirror true motivational interviewing.”
Most studies focused on psychological outcomes such as readiness to change rather than actual behavioral shifts. Long-term impacts remain uncertain due to short or absent follow-up periods.
Mejia noted that while users valued the accessibility and structure offered by AI systems, there were limitations: “Users appreciated the convenience and structure of AI systems but often missed the ‘human touch’ and complex relational dynamics of face-to-face counseling.”
Study participants included a wide range of groups—from general adults and college students to patients with specific health conditions—with smoking cessation being the most common focus area.
“AI-driven systems show exciting potential to deliver motivational interviewing and support meaningful health behavior change,” Mejia said. “These tools are feasible and well-accepted across various health issues, demonstrating key principles like empathy and collaboration. However, few studies have rigorously evaluated their impact on behavior or fidelity. As AI health interventions evolve, future research must focus on robust evaluation, transparency and ethical responsibility. By blending scalable AI technology with proven behavioral frameworks, we can expand access and better support patients facing behavior change challenges.”
Co-authors of the study include FAU medical students Zev Karve, Jacob Caley, Christopher Machado as well as Michelle K. Knecht from FAU Schmidt College of Medicine.
