Artificial Intelligence Assisted Teaching of Structured Nursing Care According to ERAS Protocol

NCT07183202 | Completed DMC

• 1 other identifier: 22.07.2025
• Study Type: interventional
• Target: 70
• Locations: 1 country
• Sites: 1

Brief Summary

This study provides an original contribution to the literature by structuring nursing care for gyneco-oncology patients according to the ERAS protocol and delivering it through AI-assisted, case-based education. This randomized controlled, fully experimental study was conducted in the second semester of the 2024-2025 academic year with third-year students who had successfully completed the Obstetrics and Gynecology Nursing course at the Faculty of Health Sciences, Department of Nursing, at a state university located in western Turkey. Seventy students participated in the study and were assigned to either the AI-assisted case-based education group or the control group using block randomization. Data were collected using the ERAS Protocol Nursing Care Knowledge Test and the Multidimensional 21st Century Skills Scale. All statistical analyses were conducted using IBM SPSS Statistics (Version 27) and the PROCESS macro (Version 4.2) developed by Hayes. Descriptive statistics were used to summarize demographic variables and baseline characteristics. Group equivalence at baseline was assessed using independent samples t-tests for continuous variables and chi-square tests for categorical variables. Effect sizes were calculated using Cohen's d and Cramér's V, as appropriate. To examine the effect of the intervention on 21st-century skills, a mixed-design ANOVA was performed with time (pretest, posttest) as the within-subjects factor and group (intervention, control) as the between-subjects factor. Partial eta squared (η²) was reported as a measure of effect size for within- and between-subjects effects. An independent samples t-test was also used to compare posttest knowledge scores between the groups. To explore the mechanisms underlying the effect of the intervention on knowledge acquisition, mediation and moderation analyses were performed using PROCESS Models 4 and 1, respectively. In the mediation model, the change in 21st-century skills (posttest-pretest difference) was tested as a mediator. In the moderation model, academic achievement was examined as a moderator of the group-knowledge relationship. Both models controlled for academic achievement where applicable. Statistical significance was set at p \< .05, and 95% confidence intervals (CI) were reported for all relevant estimates.

Conditions

AI (Artificial Intelligence); Case-based Learning; Nursing Students; ERAS; Education Nursing

Outcome Measures

Primary Outcomes (2)

• Multidimensional 21st Century Skills Scale

  It is a 5-point Likert-type scale (1- Strongly Disagree to 5- Strongly Agree) consisting of 41 items and five sub-dimensions. The scores of the scale range from 41 to 205, and as the average score increases, the students' 21st century skill levels increase. The Information and Technology Literacy Skills sub-dimension consists of 15 items, and the lowest possible score is 15, and the highest score is 75. As the average score increases, the students' information and technology literacy skill levels increase. The Critical Thinking and Problem Solving Skills sub-dimension consists of 6 items, and the lowest possible score is 6, and the highest score is 30. As the average score increases, the students' critical thinking and problem-solving skill levels increase. The Entrepreneurship and Innovation Skills sub-dimension consists of 10 items, and the score range varies between 10-50. As the average score increases, students' entrepreneurship and innovati

  pre-education and within 1 week after training

• Knowledge Test

  Developed by researchers based on the ERAS gynecologic oncology care protocol, this 10-question multiple-choice test measures students' knowledge of the ERAS protocol.

  within 1 week after education

Study Arms (2)

AIG

EXPERIMENTAL

During the training session, students were given a detailed explanation of an artificial intelligence (AI)-assisted case presentation structured according to the ERAS protocol. They were briefed on the data collection tools they would need to complete before and after the session. A convenient time was set, considering all participants' accessibility, and students were provided a link they could access from their mobile phones, tablets, or computers. Students participated in the AI-assisted case session online using this link. During the training process, a case scenario developed by the researchers and optimized with AI was presented to students on a digital platform. The case encompassed the entire patient care process, from diagnosis to discharge, simulating a real-life clinical environment. On the AI-assisted platform, students followed the case flow step by step, actively participating by entering their own responses at each stage of the clinical decision-making process. The pla

Other: Case-based learning (CBL)

CG

NO INTERVENTION

Students in the control group received no additional interventions or AI-supported case training throughout the study. The control group was limited to theoretical and practical courses within the faculty's existing curriculum, conducted using traditional methods. Students in this group received no additional training through case-based learning, AI-supported visual materials, or digital platforms; they only utilized standard course content and routine lectures from their instructors. Thus, it was evaluated whether the differences between the experimental and control groups were due to the AI-supported case training and visual materials applied.

Interventions

Case-based learning (CBL) OTHER

During the training session, students were given a detailed explanation of an artificial intelligence (AI)-assisted case presentation structured according to the ERAS protocol. They were briefed on the data collection tools they would need to complete before and after the session. A convenient time was set, considering all participants' accessibility, and students were provided a link they could access from their mobile phones, tablets, or computers. Students participated in the AI-assisted case session online using this link. During the training process, a case scenario developed by the researchers and optimized with AI was presented to students on a digital platform. The case encompassed the entire patient care process, from diagnosis to discharge, simulating a real-life clinical environment. On the AI-assisted platform, students followed the case flow step by step, actively participating by entering their own responses at each stage of the clinical decision-making process. The plat

AIG

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• a) Successfully passing the Obstetrics and Gynecology Nursing course, b) not having verbal or written communication problems, c) being an exchange student, d) having a mobile phone with internet connection, and e) being willing to give written informed consent before participating in the study.

Sponsors & Collaborators

• Sakarya University: lead

Study Sites (1)

Sakarya University

Adapazarı, Sakarya, 54050, Turkey (Türkiye)

Location

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD

Study Record Dates

• First Submitted: August 31, 2025
• First Posted: September 19, 2025
• Study Start: June 27, 2025
• Primary Completion: July 10, 2025
• Study Completion: July 22, 2025
• Last Updated: September 19, 2025

Record last verified: 2025-09

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)