AI-assisted learning: ChatGPT for anamnesis in women’s health education

Abstract

Artificial intelligence (AI) tools such as ChatGPT are rapidly being adopted in medical education, yet evidence regarding their impact on learners' history-taking (anamnesis) skills remains limited. This gap is particularly relevant in women's health education, where high-quality anamnesis is essential for addressing sensitive, context-dependent concerns and for ensuring the safety of two interrelated patients: mother and fetus. METHODS: This study comprised two phases. First, semi-structured virtual interviews were administered to students and faculty to assess their familiarity with ChatGPT and access to digital technologies. Second, an in-person classroom intervention was implemented within the Women's Health discipline, integrating ChatGPT into history-taking instruction. Students' anamnesis performance was evaluated before and after ChatGPT-assisted learning. Additionally, a novel instructional activity was introduced in which ChatGPT generated cases classified as plausible, intermediate, or physiologically impossible, serving as prompts for guided discussion focused on diagnostic pitfalls, critical appraisal, and clinical reasoning. RESULTS: < 0.0001). Students reported increased confidence and perceived enhancement of history-taking quality, and all participants viewed ChatGPT as a valuable educational resource. The AI-generated cases effectively stimulated discussion and reinforced clinical reasoning processes. Findings contributed to the development of a practical guideline for the responsible integration of ChatGPT into Women's Health education. CONCLUSIONS: ChatGPT can enhance anamnesis and promote critical reasoning through structured interaction with AI-generated cases. However, its effective and responsible use depends on targeted faculty development to ensure alignment with pedagogical goals, appropriate oversight, and consistent integration into curriculum.

Ähnliche Arbeiten