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The goal of this clinical trial is to examine the effect of artificial intelligence-assisted visual case analysis on nursing students' knowledge and attitudes towards pressure injury prevention. The main hypotheses it aims to answer are:
Researchers will compare AI-assisted case analysis to conventional case analysis to see if it affected nursing students' knowledge and attitudes about pressure injury prevention.
Participants,
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Artificial intelligence | Experimental | Nursing students will be provided with pressure injury prevention training using AI-assisted visual case analysis. The cases will be analyzed through an AI-assisted platform, and the students' knowledge and attitude levels were assessed. |
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| Traditional case analysis | Active Comparator | Pressure injury prevention training will be given to nursing students using the traditional case analysis method. Case analysis will be performed using written materials. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-assisted case analysis | Behavioral | Nursing students will perform visual case analyses of pressure injuries using an AI-based platform. The AI system will provide students with case-based feedback. |
| Measure | Description | Time Frame |
|---|---|---|
| The Pressure Ulcer Prevention Knowledge Assessment Instrument (PUPKAI) | The PUPKAI was developed by Beeckman and colleagues. It includes six subscales: etiology and development, classification and monitoring, risk assessment, nutrition, preventive interventions to reduce the amount of pressure/slip, and preventive measures to reduce the duration of pressure/slip. Each question has three answer options, one of which is correct. The total number of correct answers for each subscale and the entire instrument indicates the level of knowledge. The maximum score that can be obtained from the instrument is 26, and the acceptable score for proficiency is ≥ 16 (60%). The validity and reliability of the instrument in the Turkish population was tested by Tulek and colleagues. The content validity index of the instrument was 0.94. The internal consistency reliability for the overall instrument was determined using the Kuder-Richardson test. The Kuder-Richardson-20 value was 0.80. | Day 1 |
| Measure | Description | Time Frame |
|---|---|---|
| Attitude Towards Pressure Ulcer Prevention Device (APuP) | APuP was developed by Beeckman and colleagues from Ghent University in Belgium in 2010 to examine the attitudes of nursing students towards the prevention of pressure injuries. The scale consists of five sub-dimensions and 13 items. The sub-dimensions are "attitude towards personal competence in preventing pressure injuries", "attitude towards the priority of preventing pressure injuries", "attitude towards the impact of pressure injuries", "attitude towards personal responsibility in preventing pressure injuries" and "attitude towards the effectiveness of prevention". Items 3, 5, 7, 8, 9, 10 and 13 are reverse scored. The scores on the scale range from 13 to 52. An average attitude score of more than 75% is considered satisfactory. High total APuP scores indicate positive attitudes. The validity and reliability study of the scale for the Turkish population was conducted by Üstün in 2013. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| GÖZDE ÖZARAS ÖZ | Contact | +905323495280 | gozdeozarasoz@gmail.com.tr |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Cankiri Karatekin University. Faculty of Health Sciences. | Çankırı | Center | 18200 | Turkey (Türkiye) |
Due to participant privacy protection and ethics committee restrictions, IPD sharing is not planned.
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This study will conduct as a single-blind randomized controlled trial according to the CONSORT guideline to evaluate the effect of AI-assisted visual case analysis on nursing students' knowledge and attitudes towards pressure injury prevention.
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| Traditional case analysis | Behavioral | Participants will be present with written case scenarios and a case analysis will conduct with the instructor. The training process will be carried out with group discussions and the instructor's guidance. No technological or artificial intelligence support will be used. |
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| Day 1 |