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

Sakarya University

Status: Completed

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

Treatments: Other: Case-based learning (CBL)

Study type: Interventional

Funder types: Other

Identifiers

NCT07183202

22.07.2025

Details and patient eligibility

About

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.

Enrollment: 70 patients

Sex: All

Volunteers: Accepts Healthy Volunteers

Inclusion and exclusion criteria

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) 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

Trial design

Primary purpose: Other

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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70 participants in 2 patient groups

AIG

Experimental group

Description:

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

Treatment:

Other: Case-based learning (CBL)

CG

No Intervention group

Description:

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.