• Development and evaluation of...

*Result*: Development and evaluation of AI chatbot tool for written communication training in self-care: Experiences of pharmacy students and faculty.

Title:
Development and evaluation of AI chatbot tool for written communication training in self-care: Experiences of pharmacy students and faculty.
Authors:
Bakhaya S; Department of Pharmacy, University of Uppsala, Box 580, 751 23 Uppsala, Sweden., Lehnbom EC; Department of Pharmacy, University of Uppsala, Box 580, 751 23 Uppsala, Sweden. Electronic address: elin.lehnbom@uu.se., de Carvalho Filho MA; Faculty of Medical Sciences, University of Groningen, PO Box 72, 9700 AB Groningen, the Netherlands. Electronic address: m.a.de.carvalho.filho@umcg.nl., Ma KY; Faculty of Medical Sciences, University of Groningen, PO Box 72, 9700 AB Groningen, the Netherlands. Electronic address: k.y.ma@rug.nl., Svensberg K; Department of Pharmacy, University of Uppsala, Box 580, 751 23 Uppsala, Sweden. Electronic address: karin.svensberg@uu.se.
Source:
Currents in pharmacy teaching & learning [Curr Pharm Teach Learn] 2026 Jan; Vol. 18 (1), pp. 102503. Date of Electronic Publication: 2025 Oct 07.
Publication Type:
Case Reports; Journal Article
Language:
English
Journal Info:
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
MeSH Terms:
Artificial Intelligence*/trends , Artificial Intelligence*/standards , Self Care*/methods , Self Care*/psychology , Students, Pharmacy*/psychology , Students, Pharmacy*/statistics & numerical data , Writing*/standards , Communication*, Education, Pharmacy/methods ; Education, Pharmacy/standards ; Adult ; Humans ; Generative Artificial Intelligence ; Qualitative Research
Contributed Indexing:
Keywords: Artificial intelligence; Communication skills; Communication training; Pharmacy education; Simulated patient
Entry Date(s):
Date Created: 20251008 Date Completed: 20251102 Latest Revision: 20251121
Update Code:
20260130
DOI:
10.1016/j.cptl.2025.102503
PMID:
41061515
Database:
MEDLINE

*Further Information*

*Background: Effective communication is crucial in pharmacy practice, particularly in self-care counseling. As online pharmacies and chat-based consultations expand, training in digital written communication is increasingly important. Artificial intelligence (AI) systems based on large language models (LLMs) offer a structured and engaging environment to support skill development through conversational agents. This study explored the use of LLM-based chatbots to train pharmacy students in written synchronous communication for self-care consultations.
Methods: Three chatbot-simulated patients and an LLM-based feedback system were developed to reflect common self-care scenarios and provide communication-focused feedback. Fourteen pharmacy students and faculty interacted with the chatbots and shared their experiences through semi-structured interviews. Thematic analysis was used to identify patterns in the data.
Results: The analysis identified five main themes. Participants emphasized the authenticity of the simulated patient interactions, particularly their emotional realism. The AI-generated feedback was described as structured, detailed, and fair especially valued for its focus on communication skills. Faculty appreciated the consistency of the feedback and highlighted its added value to complement human assessment. Students discussed the cognitive and emotional demands of the experience, suggesting potential to tailor chatbot complexity to learners' needs.
Conclusion: LLM-based chatbots represent a pedagogically grounded and scalable tool for developing pharmacy students' written communication skills in self-care consultations. This approach offers a foundation for building shared virtual patient infrastructures and integrating communication theory into digital education. It holds promise for broad implementation across pharmacy programs adapting to the demands of online and hybrid care.
(Copyright © 2024. Published by Elsevier Inc.)*

*Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.*