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: 76
• Locations: 1 country
• Sites: 1

Brief Summary

This study evaluates an AI-supported case-based educational approach for teaching nursing care of gynecologic oncology patients according to the Enhanced Recovery After Surgery (ERAS) protocol. This single-center, parallel-group randomized controlled trial was conducted during the second semester of the 2024-2025 academic year with third-year undergraduate nursing students who had successfully completed the Obstetrics and Gynecology Nursing course and its related clinical practice at a public university in western Türkiye. A total of 76 students were randomized in equal proportions to the AI-supported case-simulation group or the control group using block randomization. Six participants were lost to follow-up because of withdrawal or incomplete data collection forms, and the final analyses included 70 students (35 in each group). Data were collected before and after the intervention using the researcher-developed ERAS Protocol Nursing Care Knowledge Test and the Multidimensional 21st Century Skills Scale. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize participant characteristics and study variables. Baseline characteristics were examined using independent-samples t-tests for continuous variables and chi-square tests for categorical variables. Intervention effects were evaluated using 2 × 2 mixed-design analysis of variance (ANOVA), with time (pretest and posttest) as the within-subjects factor and group (AI-supported intervention and control) as the between-subjects factor. The principal effect of interest was the Time × Group interaction, indicating whether changes from pretest to posttest differed between groups. The same analytical approach was applied to ERAS knowledge, the total 21st-century skills score, and its subdimensions. Effect sizes were reported using partial eta squared (partial η²), and statistical significance was set at p \< .05.

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

OTHER

Participants in the control group received a 35-40-minute instructor-led online educational session based on the same ERAS-based gynecologic oncology case. The session was delivered using PowerPoint and question-and-answer discussion. The control condition did not include access to the AI-supported simulation, AI-generated feedback, or AI-generated visual materials.

Other: case-based education

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

case-based education OTHER

Participants in the control group received a 35-40-minute instructor-led online educational session based on the same ERAS-based gynecologic oncology case. The session was delivered using PowerPoint and question-and-answer discussion. The control condition did not include access to the AI-supported simulation, AI-generated feedback, or AI-generated visual materials.

CG

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) not 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 22, 2025
• Study Completion: July 22, 2025
• Last Updated: September 21, 2026

Record last verified: 2026-09

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)