AI Role-Play Coaching for Breastfeeding Counseling

NCT07670247 | Completed

• 1 other identifier: Breastfeeding-AI-2026
• Study Type: interventional
• Target: 80
• Locations: 1 country
• Sites: 1

Brief Summary

Breastfeeding counseling is critically important for both maintaining the mother's motivation to breastfeed and ensuring the baby's healthy nutrition. Artificial intelligence (AI)-based role-playing coaching is an innovative teaching approach that allows students to experience the counseling process through digital scenarios, identify and correct their mistakes in a risk-free environment, and receive instant feedback based on their performance. In this context, this study aims to examine the effect of AI-assisted role-playing coaching on breastfeeding counseling skills in nursing students using a randomized controlled experimental design. The study was conducted in the Nursing Laboratory of a university's Nursing Department between March 2026 and July 2026. Participants were divided into three groups: Peer role-playing group, Classical theoretical training (control) group, and AI-assisted role-playing group. Data were collected using a personal information form, the Self-Efficacy Scale for Supporting Breastfeeding Mothers, and the Breastfeeding Counseling Role-Playing Assessment Rubric. The findings show that the peer role-playing group has a higher ability to establish open, supportive, and empathetic communication with the mother, while the AI-assisted role-playing group has a higher ability to collect, evaluate, and provide feedback on data. Furthermore, breastfeeding self-efficacy was found to be higher in the AI-assisted role-playing group. The data obtained have the potential to generate evidence for the use of next-generation learning technologies in nursing education and contribute to training graduate nurses ready for clinical practice. It will also provide a scientific basis for developing training strategies aimed at improving the quality of breastfeeding support services.

Conditions

Artificial Intelligence (AI); Breastfeeding Self-Efficacy; Breastfeeding; Role Playing

Outcome Measures

Primary Outcomes (2)

• Self-Efficacy Scale for Supporting Breastfeeding Mothers

  Developed by Dennis (2003) for use with breastfeeding mothers, the scale was revised by Blackman et al. and validated in Turkish by Bayri Bingöl et al. (2025). The scale is a 4-point Likert-type measure consisting of 37 items with response options of "Very easy," "Easy," "Difficult," and "Very difficult." Higher scores on the scale indicate higher self-efficacy in breastfeeding counseling. In the Turkish validity and reliability study of the scale, the total Cronbach's alpha value was 0.97. Permission to use the scale in our study was obtained from Assoc. Prof. Dr. Fadime BAYRI BİNGÖL.

  half an hour after the intervention

• Breastfeeding Counseling Role-Play Assessment Rubric

  This assessment tool is a structured rubric developed to measure nursing students' breastfeeding counseling skills. The rubric aims to comprehensively evaluate students' cognitive, affective, and psychomotor competencies during role-play exercises based on a mastitis case scenario. The criteria cover seven key dimensions: communication and empathy, data collection and clinical assessment, educational role, problem-solving and guidance, professional attitude, time management, and reflection. Each dimension is scored using three-level behavioral indicators (high=3, moderate=2, low=1) that qualitatively describe the student's performance. The total score obtained in the rubric reflects the student's overall competence regarding the breastfeeding counseling process (High level: 18-21, moderate level: 13-17, low level: ≤12). In determining the criteria, clinical skill and communication-based assessment tools found in the nursing education literature were taken into consideration. The rubri

  half an hour after the intervention

Study Arms (3)

AI-powered role-playing group

EXPERIMENTAL

The students in this group worked with a Turkish chatbot based on a large language model (such as ChatGPT). The chatbot was positioned as a virtual patient assuming the role of "mother" in the training scenario. Thus, students conducted the counseling session by engaging in a natural dialogue with an AI. By generating context-sensitive responses and providing appropriate reactions to the counseling messages the students sent, the AI enabled students to practice their communication and counseling skills in a realistic setting.

Other: AI-powered role-playing intervention

Peer role-play group

EXPERIMENTAL

In this group, students formed small pairs or trios to act out the scenarios. By taking turns switching roles, they played the role of "mother" one time and the role of "counselor" the next. This allowed them to both practice their counseling skills and view the counseling process from the "mother's" perspective.

Other: Peer role play intervention

Traditional theoretical training (control) group

NO INTERVENTION

In this group, students learned about the same topics through brief instructional presentations, case studies, and question-and-answer sessions. However, this training did not include practical role-playing exercises or one-on-one coaching. Consequently, a traditional training method focused primarily on knowledge transfer was applied to this group.

Interventions

AI-powered role-playing intervention OTHER

The students in this group worked with a Turkish chatbot based on a large language model (such as ChatGPT). The chatbot was positioned as a virtual patient assuming the role of "mother" in the training scenario. Thus, students conducted the counseling session by engaging in a natural dialogue with an AI. By generating context-sensitive responses and providing appropriate reactions to the counseling messages the students sent, the AI enabled students to practice their communication and counseling skills in a realistic setting.

AI-powered role-playing group

Peer role play intervention OTHER

In this group, students formed small pairs or trios to act out the scenarios. By taking turns switching roles, they played the role of "mother" one time and the role of "counselor" the next. This allowed them to both practice their counseling skills and view the counseling process from the "mother's" perspective.

Peer role-play group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Proficient in computer use
• Fluent in Turkish
• Willing to participate in the study
• A third-year nursing student currently taking the "Obstetrics and Gynecology Nursing" course

You may not qualify if:

• Those who do not agree to participate in the study
• Those who do not have sufficient knowledge of Turkish

Sponsors & Collaborators

• Bilecik Seyh Edebali Universitesi: lead

Study Sites (1)

Bilecik Şeyh Edebali University

Bilecik, 11230, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Breast Feeding

Condition Hierarchy (Ancestors)

Feeding Behavior; Behavior

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD

Model Details: Participants were divided into 3 groups (AI-assisted role-playing, peer role-playing, and classical theoretical training). Random assignment was performed by an external statistician, who had no prior contact with participants who met the inclusion criteria and agreed to participate in the study, using the 'Research Randomizer' website (www.randomizer.org). This tool generated a total of 80 different numbers and randomly assigned participants to the 3 groups. These numbers were then placed in a box, and students were assigned to a group according to the number they chose.

Study Record Dates

• First Submitted: June 16, 2026
• First Posted: June 26, 2026
• Study Start: March 9, 2026
• Primary Completion: May 4, 2026
• Study Completion: June 1, 2026
• Last Updated: June 26, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)