+ HEALTH Aims Intramuscular fat (IMF) is increasingly recognized as a marker of ectopic adiposity and adverse cardiome…+ HEALTH Periapical lesions are challenging to detect on intraoral radiographs because of anatomical superimposition a…± HEALTH Ultrasound imaging is an indispensable diagnostic tool, yet its profound reliance on operator expertise inher…+ HEALTH Objectives We adapted the individualized polysocial risk score (iPsRS), a machine learning model originally d…± HEALTH Melioidosis is a life-threatening infectious disease caused by Burkholderia pseudomallei ( Bp ). Rapid diagno…+ HEALTH Classification is a core machine learning task, and ensemble voting methods are widely used to improve predic…+ CLIMATE Microplastic (MP) pollution poses escalating environmental risks, demanding efficient and reproducible tools…± HEALTH Medicinal chemistry sits at the center of modern drug discovery, yet translating molecular designs into appro…
TruaceTracing the truth around AIWednesday, August 26, 2026
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TRV-2026-0820Certified recordPeer-reviewed

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

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…

Health · G Space — documented gain · certified 2026-08-18 · v1 · article view · machine-readable

Current reading — gain

Psychiatric nursing internship students who used the ChatGPT-based virtual patient with a structured prompting framework showed higher MSE competency after the intervention.

What this doesn’t fix

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.

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Truvace Impact Record TRV-2026-0820, v1: “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.” Truvace, 2026-08-18. /record/TRV-2026-0820 (accessed at citation time). sha256 d30f42be5e51c800…

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