Abstract
Introduction: Effective communication is critical for patient safety and quality nursing care. The SBAR (Situation, Background, Assessment, Recommendation) model offers a standardized framework for communication in healthcare. However, traditional SBAR training often lacks opportunities for practical application and timely feedback. While nursing practice involves frequent handoffs among nurses, fewer opportunities exist for practicing communication with physicians or other professionals, despite the importance of interprofessional collaboration.
Purpose: This pilot study aimed to assess the impact of an AI-based SBAR training program on nursing students' competency in SBAR communication with healthcare professionals.
Methods: A convenience sample of 10 nursing students participated in a single-arm pre-post design study. The AI-based SBAR training program integrated educational materials with practical sessions utilizing generative AI. The program included remote screen-sharing interactions with the investigator and direct teaching sessions. Assessments of participants' SBAR knowledge and attitudes were conducted before and after the training.
Results: All 10 students completed the three-week AI-based SBAR training. The program resulted in a statistically significant improvement in SBAR communication skills, with pre-training scores of 11.6 ± 2.0 increasing to 16.6 ± 2.2 post-training (t = 4.54, p = .009). However, no significant change was observed in students' attitudes toward SBAR use, with pre-training scores of 27.9 ± 3.1 and post-training scores of 27.8 ± 2.9 (t = 0.13, p = .903).
Limitations: As a pilot study with a small sample size, the findings are not generalizable. While the use of generative AI provided personalized feedback, it also posed risks of incorrect information, requiring participant oversight to manage feedback effectively.
Conclusions and Implications: The AI-based SBAR training program effectively improved nursing students' communication skills with healthcare professionals, demonstrating the potential of real-time feedback and personalized learning. However, the minimal impact on students' attitudes suggests that AI-based training should be complemented with other educational strategies. Future research should explore diverse teaching methods to foster meaningful changes in perception while refining AI-based systems for accuracy and reliability.
Notes
References:
Savellon, M., Baybayan, S., & Asiri, M. (2024). Learning satisfaction with the use of ChatGPT among nursing students in selected higher education institutions in Sulu. Journal of Education and Academic Settings, 1(1), 1-16.
Lata, K., & Kudi, S. R. (2024). Role of ChatGPT in nursing: Brief communication. Asian Journal of Nursing Education and Research, 14(1), 70-72.
Sigma Membership
Non-member
Type
Poster
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Pilot/Exploratory Study
Keywords:
Continuing Education, Virtual Learning, Mentoring and Coaching, SBAR, Nursing Students, Communication Skills
Recommended Citation
Kwon, Hyunjeong; Park, Gyoeun; Kim, Sebin; Nam, Minjae; and Kim, Jungin, "Effect of AI-Based SBAR Communication Program on Communication Competence of Nursing Students" (2025). International Nursing Research Congress (INRC). 36.
https://www.sigmarepository.org/inrc/2025/posters_2025/36
Conference Name
36th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Seattle, Washington, USA
Conference Year
2025
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Effect of AI-Based SBAR Communication Program on Communication Competence of Nursing Students
Seattle, Washington, USA
Introduction: Effective communication is critical for patient safety and quality nursing care. The SBAR (Situation, Background, Assessment, Recommendation) model offers a standardized framework for communication in healthcare. However, traditional SBAR training often lacks opportunities for practical application and timely feedback. While nursing practice involves frequent handoffs among nurses, fewer opportunities exist for practicing communication with physicians or other professionals, despite the importance of interprofessional collaboration.
Purpose: This pilot study aimed to assess the impact of an AI-based SBAR training program on nursing students' competency in SBAR communication with healthcare professionals.
Methods: A convenience sample of 10 nursing students participated in a single-arm pre-post design study. The AI-based SBAR training program integrated educational materials with practical sessions utilizing generative AI. The program included remote screen-sharing interactions with the investigator and direct teaching sessions. Assessments of participants' SBAR knowledge and attitudes were conducted before and after the training.
Results: All 10 students completed the three-week AI-based SBAR training. The program resulted in a statistically significant improvement in SBAR communication skills, with pre-training scores of 11.6 ± 2.0 increasing to 16.6 ± 2.2 post-training (t = 4.54, p = .009). However, no significant change was observed in students' attitudes toward SBAR use, with pre-training scores of 27.9 ± 3.1 and post-training scores of 27.8 ± 2.9 (t = 0.13, p = .903).
Limitations: As a pilot study with a small sample size, the findings are not generalizable. While the use of generative AI provided personalized feedback, it also posed risks of incorrect information, requiring participant oversight to manage feedback effectively.
Conclusions and Implications: The AI-based SBAR training program effectively improved nursing students' communication skills with healthcare professionals, demonstrating the potential of real-time feedback and personalized learning. However, the minimal impact on students' attitudes suggests that AI-based training should be complemented with other educational strategies. Future research should explore diverse teaching methods to foster meaningful changes in perception while refining AI-based systems for accuracy and reliability.
Description
Effective communication is essential for patient safety, but traditional SBAR training lacks practical feedback. This study examined an AI-based SBAR program with ten nursing students in a pre-post design. While the program improved SBAR skills, students' attitudes remained unchanged. The small sample size limits generalizability, and AI feedback requires careful management. Complementary teaching methods are recommended to better influence students' attitudes toward SBAR.