JMIR Publications

ABSTRACT

Background:

Generative artificial intelligence (GenAI) is increasingly integrated into clinical learning and practice. However, medical students often lack the competencies required for safe and critical use, including prompt design, output verification, and recognition of limitations. Educational interventions that integrate GenAI with clinical reasoning frameworks remain limited.

Objective:

This study evaluated a structured, theory-informed workshop integrating GenAI, prompt engineering, and clinical reasoning education to enhance medical students’ AI literacy and collaborative learning attitudes, and to examine whether patient-centered orientation was preserved following intensive AI exposure.

Methods:

We conducted a pre–post mixed-methods study with fifth-year medical students at an academic medical center. The three-hour workshop comprised six modules integrating clinical reasoning, cognitive bias awareness, verification-oriented GenAI use, and hands-on prompt engineering. Quantitative outcomes included a 20-item AI literacy questionnaire, the Patient-Practitioner Orientation Scale-Short (PPOS-D6), and a modified Collaborative Learning Attitude Scale (CLAS). Qualitative data from interviews and reflective writing were analyzed using reflexive thematic analysis and integrated with quantitative results to generate meta-inferences.

Results:

Among 150 eligible students, 139 (92.7%) completed paired assessments. AI literacy improved significantly across all domains (Cohen d = 0.69–0.98, all P<.001). Collaborative learning attitudes increased substantially (d = 0.94, P<.001), whereas patient-centered orientation showed no significant change. Qualitative analysis (interviews: n=6; reflections: n=17) identified themes describing a shift toward verification-oriented GenAI use: (1) understanding GenAI capabilities and limitations, (2) prompt-engineering skill development, (3) calibrated trust through verification, (4) GenAI-supported communication and collaboration, and (5) ethical considerations. Reflective writings suggested emerging reconceptualization of professional identity in AI-augmented practice.

Conclusions:

A brief educational intervention integrating GenAI with clinical reasoning was associated with medium-to-large improvements in AI literacy and collaborative attitudes, while patient-centered orientation was maintained. Embedding verification practices within clinical reasoning frameworks may offer a scalable approach for preparing physicians for responsible human–AI collaboration. Future studies should incorporate comparative designs, performance-based assessments, and longitudinal follow-up.