AI-Based Clinical Orientation for Nursing Students

NCT07564544 | Not Yet Recruiting DMC

• 1 other identifier: SU-Clinic Orient
• Study Type: interventional
• Target: 90
• Locations: 1 country
• Sites: 2

Brief Summary

Aim: This experimental study aims to investigate the impact of an Artificial Intelligence (AI)-based orientation program on the clinical orientation process of nursing students during their pediatric nursing clinical practice.Materials and Methods: The study population will consist of 186 third-year nursing students enrolled in the spring semester at a state university. The sample will include 90 students (45 intervention, 45 control) who meet the study criteria and volunteer to participate. Students in the intervention group will receive an AI-based clinical orientation program, while the control group will receive no additional intervention beyond the standard faculty and hospital orientation. Data will be collected between February and March 2026 using a "Descriptive Information Form," the "Clinical Adaptation Scale for Student Nurses," and the "Therapeutic Communication Skills Scale for Nursing Students" in a pre-test/post-test design.Statistical Analysis: Data will be analyzed using SPSS 25.0. Descriptive statistics (frequency, percentage, mean, and standard deviation) will be used. Normality will be assessed via Kolmogorov-Smirnov/Shapiro-Wilk tests. For group comparisons, Chi-square, ANOVA, independent samples t-test, Mann-Whitney U, and Wilcoxon tests will be utilized. The statistical significance level will be set at $p \< 0.05$.Ethical Considerations: Ethical committee approval and necessary permissions from scale authors will be obtained before the study begins. Informed consent will be collected from all participants after explaining the study objectives.Keywords: Orientation training, nursing, student, artificial intelligence, clinical practice.

Conditions

Orientation; Clinical

Outcome Measures

Primary Outcomes (1)

• Introductory Information Form

  The form was developed by the researchers in line with the relevant literature (Günerigök et al., 2020; Yılmaz et al., 2021; Demiray \& İlaslan, 2021; Saydamlı et al., 2025; Baysan Arabacı et al., 2014). The form consists of 3 sections and 8 questions: descriptive characteristics (age, gender, grade point average), information related to clinical adaptation (difficulty in adapting when first starting the clinical environment, difficulty in communicating with patients/families during clinical practice, and experiencing anxiety-stress before clinical practice), and information related to artificial intelligence (use of artificial intelligence programs and willingness to learn and use technological developments such as artificial intelligence).

  Pre-test (before the AI-supported orientation training), post-test (2 weeks after the AI-supported orientation training), and follow-up test (2 months later).

Secondary Outcomes (1)

• Clinical Adaptation Scale for Student Nurses

  Pre-test (before the AI-supported orientation training), post-test (2 weeks after the AI-supported orientation training), and follow-up test (2 months later).

Other Outcomes (1)

• Therapeutic Communication Skills Scale for Nursing Students

  Pre-test (before the AI-supported orientation training), post-test (2 weeks after the AI-supported orientation training), and follow-up test (2 months later).

Study Arms (2)

Control Group

NO INTERVENTION

Students who do not receive AI-supported orientation training.

Intervention Group

EXPERIMENTAL

Students receiving AI-supported orientation training

Other: Artificial Intelligence-Based Clinical Orientation Program

Interventions

Artificial Intelligence-Based Clinical Orientation Program OTHER

The program was implemented via a researcher-developed website featuring seven modules: Therapeutic Communication, Patient Safety, Medical Equipment, Infection Control, Care Plans, Ethics/Privacy, and Stress Management. AI was utilized to develop scenarios, create audiovisual materials, and simulate realistic clinical environments. Each 5-minute video used no real patient data. A sequential progression was enforced, requiring completion of one module to start the next. Knowledge was assessed after each module via 5-10 Kahoot questions. A gamified approach was used where the fastest, most accurate students earned digital badges, with the top three overall being recognized as winners. Content validity was ensured through expert opinions from pediatric nursing faculty, and necessary adjustments were made based on their feedback.

Also known as: Intervention Group

Intervention Group

Eligibility Criteria

• Age: 19 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Being enrolled in the Pediatric Nursing course for the first time.
• Being a third-year nursing student.
• Providing voluntary informed consent to participate in the study.

You may not qualify if:

• Being absent during the course of the study.
• Currently being employed as a healthcare professional.
• Having a frozen enrollment status.

Sponsors & Collaborators

• Selcuk University: lead

Study Sites (2)

Selcuk University

Konya, Konya, 42250, Turkey (Türkiye)

Location

Selcuk University

Konya, Selçuklu, 42060, Turkey (Türkiye)

Location

Related Links

• Related Info

MeSH Terms

Conditions

Orientation, Spatial

Condition Hierarchy (Ancestors)

Spatial Behavior; Behavior

Study Officials

• Fatma Tas Arslan

  Selcuk University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Fatma Tas Arslan, Prof. Dr.

CONTACT

+905058013067; fatmatas61@hotmail.com

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: Professor

Study Record Dates

• First Submitted: April 16, 2026
• First Posted: May 4, 2026
• Study Start: April 30, 2026
• Primary Completion (Estimated): May 11, 2026
• Study Completion (Estimated): June 11, 2026
• Last Updated: May 4, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

TU (2)