ChatGPT Virtual Assistant for Breast Reconstruction: Assessing Preferences for a Traditional Chatbot versus a Human AI VideoBot.
Autor: | Kim TS; From the Division of Plastic and Reconstructive Surgery, Stanford University Medical Center, Stanford, Calif., Yu CT; Division of Plastic & Reconstructive Surgery, Yale School of Medicine, New Haven, Conn., Hinson C; Plastic and Reconstructive Surgery Clinic, Frederick P. Whiddon College of Medicine, University of South Alabama, Ala., Fung E; Norton College of Medicine, Upstate Medical University, Syracuse, N.Y., Allam O; Division of Plastic & Reconstructive Surgery, Yale School of Medicine, New Haven, Conn., Nazerali RS; From the Division of Plastic and Reconstructive Surgery, Stanford University Medical Center, Stanford, Calif., Ayyala HS; Division of Plastic & Reconstructive Surgery, Yale School of Medicine, New Haven, Conn. |
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Jazyk: | angličtina |
Zdroj: | Plastic and reconstructive surgery. Global open [Plast Reconstr Surg Glob Open] 2024 Oct 01; Vol. 12 (10), pp. e6202. Date of Electronic Publication: 2024 Oct 01 (Print Publication: 2024). |
DOI: | 10.1097/GOX.0000000000006202 |
Abstrakt: | Background: Recent advancements in artificial intelligence (AI) have reshaped telehealth, with AI chatbots like Chat Generative Pretrained Transformer (ChatGPT) showing promise in various medical applications. ChatGPT is capable of offering basic patient education on procedures in plastic and reconstructive surgery (PRS), yet the preference between human AI VideoBots and traditional chatbots in plastic and reconstructive surgery remains unexplored. Methods: We developed a VideoBot by integrating ChatGPT with Synthesia, a human AI avatar video platform. The VideoBot was then integrated into Tolstoy to create an interactive experience that answered four of the most asked questions related to breast reconstruction. We used Zapier to develop a ChatGPT-integrated chatbot. A 16-item survey adapted from the 2005 validated measurement of online trust by Corritore et al was distributed online to female participants via Amazon Mechanical Turk. Results: A total of 396 responses were gathered. Participants were 18 to 64 years old. Perceptions of truthfulness, believability, content expertise, ease of use, and safety were similar between the VideoBot and chatbot. Most participants preferred the VideoBot compared with the traditional chatbot (63.5% versus 28.1%), as they found it more captivating than the text-based chatbot. Of the participants, 77% would have preferred to see someone who they identified with in terms of gender and race. Conclusions: Both the VideoBot and text-based chatbot show comparable effectiveness, usability, and trust. Nonetheless, the VideoBot's human-like qualities enhance interactivity. Future research should explore the impact of race and gender concordance in telehealth to provide a more personalized experience for patients. Competing Interests: Dr. Nazerali serves as a speaker/consultant/advisor to Mentor, MTF, and Telabio. All the other authors have no financial interest to declare in relation to the content of this article. (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons.) |
Databáze: | MEDLINE |
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