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

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.

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Key information

Conditions

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

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Sakarya University

Adapazarı, Sakarya, 54050, Turkey (Türkiye)

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

The sample for this study consisted of third-year nursing students. Third-year students were selected because they took the Obstetrics and Gynecology Nursing course in their first semester and were also involved in clinical practice.

Inclusion criteria

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.

Exclusion criteria

Not meeting the inclusion criteria

Treatment and study plan

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

Primary outcomes

Multidimensional 21st Century Skills Scale

Time frame: pre-education and within 1 week after training

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
Knowledge Test

Time frame: within 1 week after education

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

Sponsors and collaborators

Lead sponsor

Sakarya University

Other

Registry information

Official study title

Artificial Intelligence Assisted Teaching of Structured Nursing Care According to ERAS Protocol: A Randomised Controlled Trial

Important dates

Study start: 2025
Primary completion: 2025
Study completion: 2025
First posted: Sep 19, 2025
Registry last updated: Aug 24, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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