Abstract
Background: After liver transplantation, patients must engage in effective self-management. Current care guidance needs to be more personalized, accessible, and continuous.
Objective: To explore the effects of an AI chatbot on the self-efficacy, self-management, and quality of life of liver transplant patients.
Subjects and Methods: This study employs a single-group pre- and post-test design. A chatbot was developed and implemented in March 2025, with data collection conducted during pre-testing, the first month, and the third month.
Results: This study presents the data analysis results for the 44 participants who used the AI chatbot. The average age of the 44 patients was 55.4 (SD = 9.3). The mean self-efficacy scores at pretest, first, and third months were 44.36, 45.76, and 46.2, respectively. The mean self-management scores at the three time points were 93.48, 98.09, and 98.08, respectively. When assessed using the full possible score, the average self-efficacy scores were 85%, 88%, and 89%; self-management behaviors were 87%, 91%, and 91% respectively. The physiological aspects of quality of life were 59.5, 63.85, and 63.57 in the pretest, first month, and third month, respectively; the psychological aspects were 56.63, 61.87, and 63.5, respectively; the social relationship aspects were 65.34, 64.39, and 66.0, respectively; and the environmental aspects were 68.75, 70.27, and 71.38, respectively. Comparisons of self-efficacy, self-management behaviors, and various aspects of quality of life across the three time points (only the sample with three waves of data was analyzed in this section). While scores showed a trend toward improvement (mean score increase), only the psychological aspect reached statistical significance (F=3.436, p=0.04).
Conclusion: Participants in this study demonstrated good self-efficacy and self-management behaviors, with significant improvement in the psychological aspect of quality of life, while the other three aspects remained stable.
Notes
References:
Ko, D., Bratzke, L. C., Muehrer, R. J., & Brown, R. L. (2019). Self-management in liver transplantation. Applied Nursing Research, 45, 30-38. doi: 10.1016/j.apnr.2018.11.002.
Nadarzynski T, Knights N, Husbands D, Graham CA, Llewellyn CD, Buchanan T, et al. Achieving health equity through conversational AI: A roadmap for design and implementation of inclusive chatbots in healthcare. PLOS Digit Health. 2024;3(5):e0000492. https://doi.org:10.1371/journal.pdig.0000492
da Silva Lima Roque G, Roque de Souza R, Araújo do Nascimento JW, de Campos Filho AS, de Melo Queiroz SR, Ramos Vieira Santos IC. Content validation and usability of a chatbot of guidelines for wound dressing. Int J Med Inform. 2021;151:104473. https://doi.org/10.1016/j.ijmedinf.2021.104473
Sigma Membership
Lambda Beta at-Large
Type
Poster
Format Type
Text-based Document
Study Design/Type
Pretest-Posttest
Research Approach
Quantitative Research
Keywords:
Acute Care, Artificial Intelligence, AI, Liver Transplantation, Transplant Recipients, Quality of Life, Self-Management, Self Care
Recommended Citation
Weng, Li-Chueh; Shieh, Wann-Yun; Lee, Wei-Chen; Tsai, Yu-Hsia; and Cheng, Ssu-Min, "Effect of Chatbot-SMLT on Self-Management and Quality of Life Among Liver Transplant Recipients" (2026). International Nursing Research Congress (INRC). 28.
https://www.sigmarepository.org/inrc/2026/posters_2026/28
Conference Name
37th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Toronto, Ontario, Canada
Conference Year
2026
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. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2026-07-25
Effect of Chatbot-SMLT on Self-Management and Quality of Life Among Liver Transplant Recipients
Toronto, Ontario, Canada
Background: After liver transplantation, patients must engage in effective self-management. Current care guidance needs to be more personalized, accessible, and continuous.
Objective: To explore the effects of an AI chatbot on the self-efficacy, self-management, and quality of life of liver transplant patients.
Subjects and Methods: This study employs a single-group pre- and post-test design. A chatbot was developed and implemented in March 2025, with data collection conducted during pre-testing, the first month, and the third month.
Results: This study presents the data analysis results for the 44 participants who used the AI chatbot. The average age of the 44 patients was 55.4 (SD = 9.3). The mean self-efficacy scores at pretest, first, and third months were 44.36, 45.76, and 46.2, respectively. The mean self-management scores at the three time points were 93.48, 98.09, and 98.08, respectively. When assessed using the full possible score, the average self-efficacy scores were 85%, 88%, and 89%; self-management behaviors were 87%, 91%, and 91% respectively. The physiological aspects of quality of life were 59.5, 63.85, and 63.57 in the pretest, first month, and third month, respectively; the psychological aspects were 56.63, 61.87, and 63.5, respectively; the social relationship aspects were 65.34, 64.39, and 66.0, respectively; and the environmental aspects were 68.75, 70.27, and 71.38, respectively. Comparisons of self-efficacy, self-management behaviors, and various aspects of quality of life across the three time points (only the sample with three waves of data was analyzed in this section). While scores showed a trend toward improvement (mean score increase), only the psychological aspect reached statistical significance (F=3.436, p=0.04).
Conclusion: Participants in this study demonstrated good self-efficacy and self-management behaviors, with significant improvement in the psychological aspect of quality of life, while the other three aspects remained stable.
Description
This study developed an AI-based chatbot to enhance self-management and quality of life among liver transplant recipients. Among 44 participants, self-efficacy increased from 85% to 89%, and self-management behaviors from 87% to 91%. The quality of life improved across all domains, with a significant enhancement in the psychological aspect (p = 0.04). The AI-chatbot showed potential to improve psychological well-being and support self-management after liver transplantation.