Supplementing Patient Encounter Training for Preservice Nurses: Towards an AI×VR Approach

Abstract

We built an immersive virtual reality environment where preservice nurses practice with generative artificial intelligence-driven virtual standardized patients (AI-VSPs). We ran mixed-methods study (experimental <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n=23$</tex>; control <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n=34$</tex>). Usability score was <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$81.6 / 100$</tex>, indicating excellent usability. A single session increased self-efficacy from 3.74 to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$4.11(t(22)=3.82, p&lt;0.001$</tex>). In the standardized-patient (SP) encounter performance assessment, scores for AI-VSP users did not differ from controls <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(t(55)=-0.134, p=0.894)$</tex>. AI-VSP encounter performance did not relate to engagement, presence, or immersion, although these experience measures were strongly intercorrelated. Interviews highlighted helps and hindrances. Overall, AI-VSPs are a usable, confidence-building supplement to SP encounter preparation. We also outline practical design steps: cap reply length, enable reliable barge-in, improve speech quality and latency, and keep scaffolding minimal.

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