Academic Journal
A multi-cohort evaluation of a curriculum-aligned, oncology-focused chatbot in pharmacy education.
| Τίτλος: | A multi-cohort evaluation of a curriculum-aligned, oncology-focused chatbot in pharmacy education. |
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| Συγγραφείς: | Halford Z; Union University College of Pharmacy, 1050 Union University Drive, Jackson, TN 38305, United States. Electronic address: zhalford@uu.edu., Heitz N; Jackson-Madison County General Hospital, 620 Skyline Dr, Jackson, TN 38301, United States. |
| Πηγή: | Currents in pharmacy teaching & learning [Curr Pharm Teach Learn] 2026 Aug; Vol. 18 (8), pp. 102659. Date of Electronic Publication: 2026 Apr 16. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Country of Publication: United States NLM ID: 101560815 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1877-1300 (Electronic) Linking ISSN: 18771297 NLM ISO Abbreviation: Curr Pharm Teach Learn Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: New York : Elsevier |
| Ιατρικοί όροι (MeSH): | Curriculum*/standards , Curriculum*/trends , Education, Pharmacy*/methods , Education, Pharmacy*/standards , Education, Pharmacy*/statistics & numerical data , Students, Pharmacy*/statistics & numerical data , Students, Pharmacy*/psychology , Medical Oncology*/methods , Medical Oncology*/education, Humans ; Cohort Studies ; Surveys and Questionnaires ; Generative Artificial Intelligence ; Male ; Female ; Adult |
| Περίληψη: | Introduction: Pharmacy students increasingly rely on generative artificial intelligence (AI) for learning support, yet most available tools remain general-purpose models without domain-specific clinical oversight. This multi-cohort study evaluated whether exposure to an expert-reviewed, curriculum-aligned chatbot influenced pharmacy students' confidence, comfort, and attitudes toward AI-assisted learning. Methods: A pre-post intervention survey was conducted across two consecutive cohorts with third-year pharmacy students enrolled in an oncology pharmacotherapy course. The intervention consisted of "Chemosabe," a custom GPT chatbot configured with course-aligned content and evaluated through structured pre-deployment review by a panel of oncology-trained clinical pharmacists and fourth-year pharmacy students with prior oncology coursework and practice experience. Anonymous pre- and post-intervention surveys captured AI use and perceptions. Seven attitudinal measures, assessed with 5-point Likert-type scales, were common to both surveys and served as the primary pre-post comparison. Results: Across cohorts, 40 pre-intervention and 42 post-intervention surveys were analyzed. In pooled analyses, six of seven attitudinal measures improved from pre to post, with large effects observed for trust in AI accuracy, comfort with AI, and confidence in evaluating AI. Differences were also observed for AI enhancing learning, helping with complex topics, and openness to AI integration. Students reported infrequent experiences with incorrect, misleading, or fabricated information, with 98% encountering such experiences rarely or never. Ninety-three percent would recommend the chatbot to future cohorts. Conclusions: An oncology-focused AI chatbot was associated with replicable improvements in pharmacy students' confidence, comfort, and trust in AI as an educational tool, supporting the potential value of clinician-curated, course-specific tools for strategic AI integration into pharmacy education. (Copyright © 2024. Published by Elsevier Inc.) |
| Competing Interests: | Declaration of competing interest Authors of this paper have the following to disclose concerning possible financial or personal relationships with commercial entities that may have a direct or indirect interest in the subject matter of this paper. Zachery Halford: Nothing to disclose. Nathan Heitz: Nothing to disclose. |
| Contributed Indexing: | Keywords: Artificial intelligence; Curriculum development; Educational technology; Oncology; Pharmacy education |
| Entry Date(s): | Date Created: 20260417 Date Completed: 20260612 Latest Revision: 20260618 |
| Update Code: | 20260619 |
| DOI: | 10.1016/j.cptl.2026.102659 |
| PMID: | 41997099 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1877-1300 |
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| DOI: | 10.1016/j.cptl.2026.102659 |