The Effect of an Artificial Intelligence-Supported Virtual Reality Simulation on Nursing Students' Holistic Care Skills

Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
AgeNot listed
SponsorGazi University

About this trial

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.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Voluntary participation in the study,

Having enrolled for the first time in the courses HEM 402 Professional Practice I and HEM 404 Professional Practice II in the Department of Nursing, Faculty of Health Sciences,

Absence of eye conditions affecting depth perception, such as amblyopia (lazy eye), anisometropia(different refractive errors in each eye), and strabismus (squint). (Self- report is accepted.),

Academic performance score between 2.00 and 4.00.,

Disqualifiers

Having received training in holistic care skills in addition to their undergraduate nursing degree,

Having experience with virtual simulation exercises focused on holistic care skills,

Holding a high school, foundation year or undergraduate degree in a health-related field,

Having difficulty understanding and speaking Turkish,

Trial design

Design model

Parallel

Treatments tested in this trial

  • AI-VRS

    Other intervention

    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.

  • Control

    Other intervention

    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.

Treatment groups

80 Participants
are divided into 2 treatment groups
Group A: AI-VRSExperimental treatment 1 intervention
Group B: ControlOther 1 intervention

Trial outcomes

Primary outcomes

1

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)

Secondary outcomes

1

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)
2

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
3

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

Other outcomes

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