Canonical text (the exact bytes fingerprinted)

TRUVACE RECORD VERSION
record: TRV-2026-0820
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-18T06:04:56.985248Z
status: published
lens: g_space
sector: health
headline: 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
dek: 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…
gain_title: Psychiatric nursing internship students who used the ChatGPT-based virtual patient with a structured prompting framework showed higher MSE competency after the intervention.
problem_title: (none)
trace_subject: (none)
gain_reading: Psychiatric nursing internship students who used the ChatGPT-based virtual patient with a structured prompting framework showed higher MSE competency after the intervention.
gain_evidence: Students reported that the application enhanced their MSE examination and communication skills
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers tested an AI-powered virtual patient application built on ChatGPT to teach Mental Status Examination skills to 27 psychiatric nursing internship students. Using a sequential explanatory mixed-methods design, they measured competency before and after the structured prompting intervention and then interviewed 18 students about their experience.

By the publication date of August 17, 2026, the study reported a measured increase in competency scores and positive student reports of skill development, suggesting a potential training benefit for psychiatric nursing education. It remains uncertain how this small, single-group, internship-student sample would generalize to other programs, whether gains persist in real clinical encounters, and what specific limitations students identified under the Limitations theme.
limitation: Findings are based on a small single-group sample of 27 students with a pre-test/post-test model and no control group, and qualitative insights from 18 volunteers, limiting generalizability.
tag: Evidence-backed gain
key_points: Study used sequential explanatory mixed-method design with quantitative pre/post-test followed by qualitative interviews. | Quantitative phase included 27 undergraduate psychiatric nursing internship students assessed with MSE Competency Assessment. | Qualitative phase included in-depth individual interviews with 18 volunteer students. | Intervention was named "AI-Supported Virtual Patient Intervention: Structured Prompting Framework" using ChatGPT.
rundown: The intervention was delivered as the "AI-Supported Virtual Patient Intervention: Structured Prompting Framework" using ChatGPT. Quantitative assessment used the MSE Competency Assessment in a pre-test/post-test model with 27 students, showing a statistically significant increase reported as Z = -6.266, p < 0.001.

Qualitative thematic analysis produced five main themes: Skill Development, Learning Experience, Impact of AI, Debriefing, and Limitations. Students described enhanced examination and communication skills and highlighted the importance of guided support during the AI-based learning experience.
sources:
- peer_reviewed | Issues in Mental Health Nursing | https://doi.org/10.1080/01612840.2026.2710861 | 2026-08-17
prev: 0000000000000000000000000000000000000000000000000000000000000000

sha256

d30f42be5e51c800c2b854c6c6f495b9d9f4c0af52d37e2a7096db5a768e0152

previous

0000000000000000000000000000000000000000000000000000000000000000