Need assessment for history-taking instruction program using chatbot for nursing students: a qualitative study using focus group interviews
Open accessAbstract
Purpose: A comprehensive health history contributes to identifying the most appropriate interventions and care priorities. However, history-taking is challenging to learn and develop for most nursing students. Chatbot was suggested by students to be used in history-taking training. Still, there is a lack of clarity regarding the needs of nursing students in these programs. This study aimed to explore nursing students' needs and essential components of chatbot-based history-taking instruction program. Methods: This was a qualitative study. Four focus groups, with a total of 22 nursing students, were recruited. Colaizzi's phenomenological methodology was used to analyze the qualitative data generated from the focus group discussions. Results: Three main themes and 12 subthemes emerged. The main themes included limitations of clinical practice for history-taking, perceptions of chatbot used in history-taking instruction programs, and the need for history-taking instruction programs using chatbot. Students had limitations in clinical practice for history-taking. When developing chatbot-based history-taking instruction programs, the development should reflect students' needs, including feedback from the chatbot system, diverse clinical situations, chances to practice nontechnical skills, a form of chatbot (i.e., humanoid robots or cyborgs), the role of teachers (i.e., sharing experience and providing advice) and training before the clinical practice. Conclusion: Nursing students had limitations in clinical practice for history-taking and high expectations for chatbot-based history-taking instruction programs.
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A study that applied a chatbot program for history-taking assessment to nursing students showed that the chatbot program allowed students to practice repetitively, providing more opportunities to attempt and learn from mistakes, ultimately boosting their confidence.
“Furthermore, similar to a study that applied a chatbot program for history-taking assessment to nursing students [33], it showed that the chatbot program allowed students to practice repetitively, providing them with more opportunities to attempt and learn from mistakes, ultimately boosting their confidence.”
From Development and effects of a chatbot education program for self-directed learning in nursing students (2025) · cites this paper as [33]
Split into 2 atoms — 0 confirmed, 1 partially supported, 1 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredNursing professionals are challenged to quickly adapt to evolving medical knowledge, make accurate decisions in real-case scenarios, and master complex nursing skills.
“Additionally, with the rapid advancements in nursing research and the advent of new diseases and medications, nursing professionals are challenged to quickly adapt to evolving medical knowledge, make accurate decisions in real-case scenarios, and master complex nursing skills (1, 17, 26–28).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [26]
The Introduction (page not provided) describes history-taking as a difficult-to-master nursing skill that helps nurses make preliminary clinical judgments; it also says students struggle to interview patients in real clinical settings. It does not link these challenges to rapidly changing medical knowledge, new diseases, or medications, or establish a need to adapt quickly to them. (LLM, conf=0.84)
Experimental — accuracy not yet measuredReported growth in behavioral learning gains encompasses self-directed learning, diagnostic skills, clinical practice, engagement, and chatbot usage frequency.
“Reported growth in behavioral learning gains encompasses self-directed learning (16), diagnostic skills (44), clinical practice (26), engagement (19), and chatbot usage frequency (28).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [26]
The Results section (‘Perceptions of chatbot use in history-taking instruction program’; page unavailable) reports that students believed chatbot practice could help them feel more prepared for clinical practice. It does not report observed growth in behavioral learning gains or improved clinical-practice performance; those were anticipated benefits, not measured outcomes. Citation (26) is attached to ‘clinical practice,’ so the other listed outcomes are not assessed here. (LLM, conf=0.84)
Experimental — accuracy not yet measuredAI systems have evolved from early computer-assisted learning and simulation platforms to adaptive learning environments, virtual tutors and generative large language models.
“AI systems, defined as software capable of supporting logical and informed judgments [9], have evolved from early computer-assisted learning and simulation platforms to adaptive learning environments, virtual tutors and generative large language models (LLMs) [10,11].”
From Artificial Intelligence–Enabled Educational Tools and Clinical Reasoning in Undergraduate Nursing Education: A Systematic Review (2026) · cites this paper as [10]
The Discussion contrasts preset virtual-patient and vSIM programs with AI that could learn, and says chatbots could be used for tutoring. It does not describe a progression through adaptive learning environments to generative large language models; that part of the attributed claim is unsupported. (LLM, conf=0.87)
Experimental — accuracy not yet measuredA chatbot-based history-taking training program benefited 22 third-year undergraduate nursing students, providing more opportunities for clinical practice in history-taking.
“Chen et al. (26) employed a qualitative approach using focus group interviews to explore how a chatbot-based history-taking training program benefited 22 third-year undergraduate nursing students, providing more opportunities for clinical practice in history-taking.”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [26]
The Methods (Participants and Data collection; page unavailable) describe focus group interviews with 22 third-year undergraduate nursing students about a program that might be developed. The Results (Perceptions of chatbot use; page unavailable) report that students expected a chatbot to provide more opportunities to practice history-taking, but the study did not test a program or establish that it benefited them. (LLM, conf=0.90)
Experimental — accuracy not yet measured
Assistance provision (n = 3) by AI chatbots has been shown to enhance students' self-directed learning and clinical practice.
“The assistance provision (n = 3) by AI chatbots has been shown to enhance students’ self-directed learning and clinical practice (16, 26).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [26]
The Results ('Feedback') say students believed chatbot feedback might promote self-learning, and the Conclusions say they expected more history-taking practice and confidence before clinical practice. This was a needs-assessment study, not a demonstration that chatbot assistance enhanced self-directed learning or clinical practice; it also does not establish the cited n = 3 count. (LLM, conf=0.87)
Experimental — accuracy not yet measuredHigh-level digital affordances of AI chatbots, particularly assistance provision (n = 7), effectively enhance nurses' learning achievement, critical thinking, and problem solving.
“The high-level digital affordances of AI chatbots, particularly in assistance provision (n = 7), effectively enhance nurses’ learning achievement, critical thinking, problem solving (19, 26).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [26]
The Conclusions (page unavailable) report that nursing students believed a chatbot could offer more opportunities to practise history-taking and help them become confident. The paper does not establish that chatbots effectively improve learning achievement, critical thinking, or problem solving, and it does not report an assistance-provision finding of n = 7. (LLM, conf=0.84)
Experimental — accuracy not yet measured
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- Authors
- Chen, Y., Lin, Q., Chen, X., Liu, T., Ke, Q., Yang, Q., Guan, B., & Ming, W.-K.
- Affiliations
- Jinan University (CN)
- City University of Hong Kong (HK)
- School of Nursing, Jinan University, Guangzhou, China
- First Affiliated Hospital of Jinan University (CN)
- Corresponding author
- Yang, Qiaohong
- Guan, Bingsheng
- Ming, Wai-kit
- Venue
- Digital Health
- Publisher
- SAGE Publications
- Published
- 2023-01
- Volume
- 9
- Pages
- 20552076231185435-20552076231185435
- ISSN
- 2055-2076 (ISSN-L)
- PMC
- PMC10328012
- OpenAlex
- W4382602638
- Cited by
- 24
- References
- 29
- Citations by year
- 2026: 4 · 2025: 13 · 2024: 7
- FWCI
- 0.96
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Digital Health (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- CityU Scholars (submittedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- The research project of teaching method reform of Jinan University (nil)
- SIRG - CityU Strategic Interdisciplinary Research Grant (7020093)
- The Fundamental Research Funds for the Central Universities (21622304)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Physiology › Simulation-Based Education in Healthcare
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Keywords
- health history taking, chatbots, nursing students, nursing education, educational program design, student needs assessment, non-technical skills, humanoid robots, clinical teaching
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