The Effect of an Artificial Intelligence-Supported Virtual Reality Simulation on Nursing Students' Holistic Care Skills
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 80
- 试验地点
- 1
- 主要终点
- Nursing Diagnosis and Symptom Identification within a Holistic Care Framework
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 盲法
- None
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.,
排除标准
- •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,
- •Criteria for Exclusion from the Study:
- •The participant has not completed or has incompletely completed the required forms and scales,
- •The participant in the experimental group had not taken part in or completed the AI-supported virtual reality simulation,
- •Students in the control group did not take part in the educational case study,
- •Students in the experimental and control groups did not take part in the assessment case study,
- •The participant wishes to withdraw from the study,
研究组 & 干预措施
AI-VRS
At the start of the study, participants will be asked to complete a demographic questionnaire and the Melbourne Decision-Making Scale. They will then be assigned to research groups based on their overall academic grade point average and their experience with virtual reality (VR) headsets. Before the intervention, participants will be provided with a pre-intervention information guide. The experimental group will undergo training using an AI-supported VR simulation designed to facilitate taking a patient history, identifying symptoms, and determining a nursing diagnosis. Two weeks after the training, concurrently with the control group, they will undertake an assessment case study in which they must analyse the case individually, without instructor support, to identify nursing diagnoses and symptoms. They will then complete the Melbourne Decision-Making Scale, the Simulation Design Scale, and a satisfaction questionnaire regarding the training methods.
干预措施: AI-VRS (Other)
Control
At baseline, participants will complete a demographic questionnaire and the Melbourne Decision-Making Scale. Participants will then be allocated to study groups using a stratified randomisation approach based on academic grade point average and prior experience with VR headsets.
The control group will receive traditional case-based training using written clinical scenarios. Following the training, a two-week interval will be observed. After this period, both the control and experimental groups will complete an assessment case simultaneously. During this assessment, participants will be required to independently analyse the case, identify the patient's symptoms, and formulate appropriate nursing diagnoses without instructor support.
After completing the assessment, participants will again complete the Melbourne Decision-Making Scale as a post-test measure.
干预措施: Control (Other)
结局指标
主要结局
Nursing Diagnosis and Symptom Identification within a Holistic Care Framework
时间窗: 2 weeks post-intervention (assessment case study)
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.
次要结局
- Melbourne Decision-Making Scale(Baseline (pre-intervention) and 2 weeks post-intervention (assessment case study))
- Simulation Design Scale(2 weeks post-intervention)
- Satisfaction Survey Regarding Teaching Methods(2 weeks post-intervention)
研究者
Nurcan Çalışkan
Professor of Nursing
Gazi University