A Seven‐Step Framework for Structured ChatGPT‐Assisted Pharmacology Learning: Educational Outcomes and Attitudes Toward Hypothetical AI‐Informed Patients
Jelena Roganović, Igor Končar, Milena BaraćBackground/Objectives
Generative artificial intelligence is increasingly used by health professions students and by patients seeking health information before consultation. This creates two related educational challenges: supporting critical AI use during learning and preparing future clinicians to respond appropriately to hypothetical AI‐informed patients. This study evaluated a teacher‐designed seven‐step ChatGPT‐assisted framework for autonomic pharmacology learning and explored whether principles embedded in the framework were reflected in students’ attitudes toward AI‐informed patients.
Methods
In this matched‐cohort educational study, 104 third‐year dental students were included. Students who voluntarily participated in the seven‐step ChatGPT‐assisted framework ( n = 52) were individually matched with nonusers ( n = 52) by previous academic achievement and digital‐tool familiarity. The primary outcome was performance on a three‐item open‐ended pharmacology quiz assessing mechanistic reasoning, scored independently by two blinded assessors. Framework participants also completed an eight‐item learning‐perception questionnaire and a ten‐item questionnaire addressing hypothetical AI‐informed patients. Exploratory Spearman correlations examined conceptually matched learning‐ and patient‐facing statements.
Results
Framework participants achieved higher postlearning pharmacology scores than matched nonusers (1.77 ± 0.30 vs. 1.45 ± 0.47; p = 0.0003). The largest difference was observed for questions requiring integration of receptor mechanisms and downstream signaling (+28%; p < 0.001), whereas factual drug‐name recall did not differ ( p = 0.47). Students generally recognized both the potential usefulness and limitations of ChatGPT and endorsed professional, nondismissive responses to hypothetical AI‐informed patients. The perceived usefulness of ChatGPT for learning and writing was associated with recognition of the risk of patient overreliance on AI‐generated diagnoses ( ρ = 0.32, p = 0.019), while intention to use ChatGPT for learning was associated with endorsement of a serious and professional approach to patients presenting with ChatGPT‐generated diagnoses ( ρ = 0.40, p = 0.004).
Conclusions
Participation in the structured framework was associated with stronger postlearning mechanistic pharmacology performance. The novel cross‐context analysis identified limited but potentially meaningful alignment between responsible AI use in learning and professional attitudes toward hypothetical AI‐informed patients. These exploratory associations do not demonstrate transfer of clinical communication competence, but suggest that verification, contextualization, risk awareness, and human oversight may provide a shared educational foundation for addressing AI use by both learners and patients.