This study aims to evaluate the effect of artificial intelligence (AI)-supported virtual reality (VR) simulation on nursing students' holistic care skills. The study is a randomised controlled trial involving fourth-year nursing students, divided into an experimental and a control group. Whilst the experimental group will receive AI-supported VR simulation training, the control group will receive traditional case-based training. Outcomes to be assessed include decision-making, symptom identification, nursing diagnosis, simulation design and satisfaction with the training methods.
This study will evaluate the effect of an artificial intelligence-supported virtual reality (VR) simulation on nursing students' holistic care skills. The study is designed as a pre-post, parallel-group, randomised controlled trial involving 80 fourth-year nursing students (40 in the experimental group and 40 in the control group). Eligible participants will complete a demographic form and the Melbourne Decision-Making Scale at the outset. Participants will be stratified by overall academic grade point average and prior VR experience, and randomly assigned to groups by an independent statistician. Whilst the intervention group receives AI-supported VR simulation training, the control group will receive traditional case-based training using the same case scenario to ensure comparability. Both the training case and the assessment case, along with the assessment criteria, will be developed based on expert consensus. Two weeks after the intervention, both groups will complete a case study assessment. Data collection will include the Melbourne Decision-Making Scale, nursing diagnosis and symptom identification results, and satisfaction measures. The statistician will be blinded, and appropriate statistical tests will be applied based on the data distribution.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
NONE
Enrollment
80
This intervention consists of an AI-supported virtual reality (VR) simulation designed to improve nursing students' holistic care skills. Participants interact with a virtual patient to perform patient history-taking, identify symptoms, and formulate nursing diagnoses across the dimensions of holistic care (physical, psychological, social, and spiritual). The simulation is delivered using Meta Quest 3 VR headsets and incorporates artificial intelligence to provide dynamic, responsive patient interactions. The intervention includes structured simulation scenarios with high-fidelity graphics and interactive decision-making processes to support skill acquisition.
This intervention consists of traditional case-based training delivered through presentations and question-and-answer discussions. Participants will analyse case scenarios and receive feedback from instructors. This approach provides a practical learning experience without using VR technology.
Gazi University Nursing Faculty
Ankara, Turkey (Türkiye)
Nursing Diagnosis and Symptom Identification within a Holistic Care Framework
Participants' ability to correctly identify patient symptoms and formulate appropriate nursing diagnoses will be evaluated using a structured assessment form. In addition to overall accuracy, performance will be assessed based on the inclusion of multiple dimensions of holistic care (physical, psychological, social, and spiritual). Higher scores will indicate greater diagnostic accuracy in nursing and more comprehensive holistic care assessment.
Time frame: 2 weeks post-intervention (assessment case study)
Melbourne Decision-Making Scale
Used to assess changes in decision-making skills. Higher scores indicate better decision-making performance.The Melbourne Decision-Making Scale consists of two parts. MKVÖ I: This scale is designed to assess self-esteem (self-confidence) in decision-making. The maximum score on the scale is 12. High scores indicate high self-esteem in decision-making. MKVÖ II: The scale measures decision-making styles. In the scoring of MKVÖ II, the following score ranges are used: cautious (0-12), avoidant (0-12), procrastinating (0-10), and panicked (0-10).
Time frame: Baseline (pre-intervention) and 2 weeks post-intervention (assessment case study)
Simulation Design Scale
Assessed using the Simulation Design Scale to evaluate participants' perceptions of the simulation design. Higher scores indicate more positive evaluations. The scale consists of five subscales-"Goals and Knowledge," "Support," "Problem Solving," "Feedback/Guided Reflection," and "Authenticity"-and twenty items. The number of items in each subscale is as follows: the "Goals and Knowledge" subscale has 5 items, the "Support" subscale has 4 items, the "Problem Solving" subscale has 5 items, the "Feedback/Guided Reflection" subscale has 4 items, and the "Degree of Authenticity" subscale has 2 items. The scale, administered in two sections, measures students' opinions on whether the best simulation design elements were implemented in the simulation application in the first section and on the extent to which the simulation application is important to students in the second section.
Time frame: 2 weeks post-intervention
Satisfaction Survey Regarding Teaching Methods
Student satisfaction will be assessed immediately after completion of the VR training to capture participants' perceptions of the training experience. Higher scores indicate greater satisfaction.The survey is scored on a scale of 16 to 80 points.
Time frame: 2 weeks post-intervention
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.