An AI-Supported Virtual Patient Application Using a Structured Prompting Framework to Develop Mental Status Examination Skills in Psychiatric Nursing Internship Students: An Interventional Mixed-Methods Study

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Chinese explanation / 中文解读

中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

The aim of this study is to evaluate the effect of an artificial intelligence (AI)-powered virtual patient application (ChatGPT) on the development of Mental Status Examination (MSE) skills in psychiatric nursing internship students and to explore how this process is reflected in their experiences. This study employed a sequential explanatory mixed-method design, consisting of a quantitative pre/post-test phase followed by a qualitative phase. In the quantitative phase, the MSE Competency Assessment scores of 27 undergraduate psychiatric nursing internship students were evaluated using a pre-test/post-test model. In the qualitative phase, in-depth individual interviews were conducted with 18 volunteer students. As part of the intervention, students participated in the “AI-Supported Virtual Patient Intervention: Structured Prompting Framework”. The quantitative findings of the study revealed that the mean MSE Competency Assessment scores increased from 42.00 ± 6.43 in the pre-test to 49.57 ± 3.44 in the post-test (Z = −6.266, <i>p</i> &lt; 0.001). Thematic analysis of the qualitative data yielded five main themes: Skill Development, Learning Experience, Impact of AI, Debriefing, and Limitations. Students reported that the application enhanced their MSE examination and communication skills; they also described a unique learning experience through AI, highlighted the importance of guided support.

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