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. 2025 May 20:11:e63353.
doi: 10.2196/63353.

Assessing ChatGPT's Capability as a New Age Standardized Patient: Qualitative Study

Joseph Cross #  1 , Tarron Kayalackakom #  2 , Raymond E Robinson  3 , Andrea Vaughans  4 , Roopa Sebastian  4 , Ricardo Hood  2 , Courtney Lewis  2 , Sumanth Devaraju  2 , Prasanna Honnavar  2 , Sheetal Naik  2 , Jillwin Joseph  2 , Nikhilesh Anand  5 , Abdalla Mohammed  6 , Asjah Johnson  6 , Eliran Cohen  6 , Teniola Adeniji  6 , Aisling Nnenna Nnaji  6 , Julia Elizabeth George  6
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Assessing ChatGPT's Capability as a New Age Standardized Patient: Qualitative Study

Joseph Cross et al. JMIR Med Educ. .

Abstract

Background: Standardized patients (SPs) have been crucial in medical education, offering realistic patient interactions to students. Despite their benefits, SP training is resource-intensive and access can be limited. Advances in artificial intelligence (AI), particularly with large language models such as ChatGPT, present new opportunities for virtual SPs, potentially addressing these limitations.

objectives: This study aims to assess medical students' perceptions and experiences of using ChatGPT as an SP and to evaluate ChatGPT's effectiveness in performing as a virtual SP in a medical school setting.

Methods: This qualitative study, approved by the American University of Antigua Institutional Review Board, involved 9 students (5 females and 4 males, aged 22-48 years) from the American University of Antigua College of Medicine. Students were observed during a live role-play, interacting with ChatGPT as an SP using a predetermined prompt. A structured 15-question survey was administered before and after the interaction. Thematic analysis was conducted on the transcribed and coded responses, with inductive category formation.

Results: Thematic analysis identified key themes preinteraction including technology limitations (eg, prompt engineering difficulties), learning efficacy (eg, potential for personalized learning and reduced interview stress), verisimilitude (eg, absence of visual cues), and trust (eg, concerns about AI accuracy). Postinteraction, students noted improvements in prompt engineering, some alignment issues (eg, limited responses on sensitive topics), maintained learning efficacy (eg, convenience and repetition), and continued verisimilitude challenges (eg, lack of empathy and nonverbal cues). No significant trust issues were reported postinteraction. Despite some limitations, students found ChatGPT as a valuable supplement to traditional SPs, enhancing practice flexibility and diagnostic skills.

Conclusions: ChatGPT can effectively augment traditional SPs in medical education, offering accessible, flexible practice opportunities. However, it cannot fully replace human SPs due to limitations in verisimilitude and prompt engineering challenges. Integrating prompt engineering into medical curricula and continuous advancements in AI are recommended to enhance the use of virtual SPs.

Keywords: AI; ChatGPT; LLM; assessment; diagnostic; effectiveness; flexibility; medical education; medical school; qualitative; standardized patient; standardized patients; virtual patient.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1.
Figure 1.. Prompt used in ChatGPT role-play.
Figure 2.
Figure 2.. Screenshot example of ChatGPT standardized patient interaction.
See this image and copyright information in PMC

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