Year: 2025
Type: article
Study design: Clinical Trial
Abstract: Taking patients’ history is a fundamental skill for nursing students, yet opportunities for hands-on practice are often limited, particularly in the early years of training. While AI-powered chatbots have gained attention in healthcare education globally, their specific application in systematic history-taking training for Thai first-year nursing students remains underexplored. This study evaluates the feasibility of a role-play chatbot developed using the ChatGPT platform to enhance history-taking knowledge among first-year nursing students at a nursing college in Bangkok, Thailand. Thirty volunteer students interacted with three clinical scenarios: appendicitis, chronic kidney disease, and non-ST elevation myocardial infarction (NSTEMI), completing at least one session per scenario over a one-week period. A pre-post design was employed to measure knowledge changes, with tests administered before and after the intervention, along with a post-intervention satisfaction survey. The results showed that the post-test knowledge scores (mean = 9.37, SD = 1.25) were significantly higher than the pre-test scores (mean = 8.47, SD = 1.31), p=0.005, with a mean difference of 0.90 (95% CI = 0.31-1.49). Students reported high levels of acceptance across all technology acceptance model dimensions, including perceived usefulness, perceived ease of use, attitude toward using, behavioral intention, and facilitating conditions, with mean scores ranging from 4.35 to 4.58 on a 5-point Likert scale. This indicates that the chatbot was well-accepted as a potential supplementary learning tool. However, this study has several limitations, including a small sample size, a short experimental duration, and its conduction at a single institution. Despite these limitations, the findings provide preliminary evidence of the feasibility and potential of using the ChatGPT chatbot to enhance patient history-taking knowledge among Thai nursing students. Future research should expand to multiple institutions, employ a longer duration, and include long-term evaluation to confirm these findings and establish the sustainable effectiveness of this technology in nursing education.
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7217716200