Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Background: Recent advancements in artificial intelligence (AI) like ChatGPT have expanded possibilities for patient education, yet its impact on perioperative anxiety in total knee arthroplasty (TKA) patients remains unexplored.
Methods: In this single-blind, randomized controlled pilot study from April to July 2023, 60 patients were randomly allocated using sealed envelopes to either ChatGPT-assisted or traditional surgeon-led informed consent groups. In the ChatGPT group, physicians used ChatGPT 4.0 to provide standardized, comprehensive responses to patient queries during the consent process, while maintaining their role in interpreting and contextualizing the information. Outcomes were measured using Hospital Anxiety and Depression Scales (HADS), Perioperative Apprehension Scale-7 (PAS-7), Visual Analogue Scales for Anxiety and Pain (VAS-A, VAS-P), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and satisfaction questionnaires.
Results: Of 55 patients completing the study, the ChatGPT group showed significantly lower anxiety scores after informed consent (HADS-A: 10.48 ± 3.84 vs 12.75 ± 4.12, P = .04, Power = .67; PAS-7: 12.44 ± 3.70 vs 14.64 ± 2.11, P = .01, Power = .85; VAS-A: 5.40 ± 1.89 vs 6.71 ± 2.27, P = .02, Power = .75) and on the fifth postoperative day (HADS-A: 8.33 ± 3.20 vs 10.71 ± 3.83, P = .01, Power = .79; VAS-A: 3.41 ± 1.58 vs 4.64 ± 1.70, P = .008, Power = .85). The ChatGPT group also reported higher satisfaction with preoperative education (4.22 ± 0.51 vs 3.43 ± 0.84, P <.001, Power = .99) and overall hospitalization experience (4.11 ± 0.65 vs 3.46 ± 0.69, P = .001, Power = .97). No significant differences were found in depression scores, knee function, or pain levels.
Conclusions: ChatGPT-assisted informed consent effectively reduced perioperative anxiety and improved patient satisfaction in TKA patients. While these preliminary findings are promising, larger studies are needed to validate these results and explore broader applications of AI in preoperative patient education.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12372728 | PMC |
| http://dx.doi.org/10.1097/JS9.0000000000002223 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Effectiveness, Usability, and Acceptability of ChatGPT With Retrieval-Augmented Generation (SIV-ChatGPT) in Increasing Seasonal Influenza Vaccination Uptake Among Older Adults: Quasi-Experimental Study.
J Med Internet Res
September 2025
School of Governance and Policy Science, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong).
Background: Older adults are more vulnerable to severe consequences caused by seasonal influenza. Although seasonal influenza vaccination (SIV) is effective and free vaccines are available, the SIV uptake rate remained inadequate among people aged 65 years or older in Hong Kong, China. There was a lack of studies evaluating ChatGPT in promoting vaccination uptake among older adults.
View Article and Find Full Text PDFA Study of Academics' Perceptions of Ethical Implications of Generative Artificial Intelligence on Scientific Research and Publishing.
J Empir Res Hum Res Ethics
September 2025
TOBB ETU School of Medicine, History of Medicine and Ethics Department, Ankara, Turkey.
This study investigates how scientists, educators, and ethics committee members in Türkiye perceive the opportunities and risks posed by generative AI and the ethical implications for science and education. This study uses a 22-question survey developed by the EOSC-Future and RDA AIDV Working Group. The responses were gathered from 62 universities across 208 universities in Türkiye, with a completion rate of 98.
View Article and Find Full Text PDFSurvey on sampling conditioned brain images and imaging measures with generative models.
Biomed Eng Lett
September 2025
Computer Science and Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro. Nam-Gu, Pohang, Gyeongbuk 37673 Korea.
Generative models have become innovative tools across various domains, including neuroscience, where they enable the synthesis of realistic brain imaging data that captures complex anatomical and functional patterns. These models, such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and diffusion models, leverage deep learning to generate high-quality brain images while maintaining biological and clinical relevance. These models address critical challenges in brain imaging, e.
View Article and Find Full Text PDFInterpreting BI-RADS-Free Breast MRI Reports Using a Large Language Model: Automated BI-RADS Classification From Narrative Reports Using ChatGPT.
Acad Radiol
September 2025
Department of Radiology, Başakşehir Çam and Sakura City Hospital, Istanbul, Turkey (E.E.).
Purpose: This study aimed to evaluate the performance of ChatGPT (GPT-4o) in interpreting free-text breast magnetic resonance imaging (MRI) reports by assigning BI-RADS categories and recommending appropriate clinical management steps in the absence of explicitly stated BI-RADS classifications.
Methods: In this retrospective, single-center study, a total of 352 documented full-text breast MRI reports of at least one identifiable breast lesion with descriptive imaging findings between January 2024 and June 2025 were included in the study. Incomplete reports due to technical limitations, reports describing only normal findings, and MRI examinations performed at external institutions were excluded from the study.
The effect of chatbot-supported instruction on nursing students' history-taking questioning skills and stress level: A randomized controlled study.
J Prof Nurs
September 2025
Kocaeli University of Health and Technology, Information Systems Engineering Deparment, Kocaeli, Turkey; Wefi Games Software Company, Goller Bolgesi Teknokenti, Isparta, Turkey.
Background: Comprehensive history-taking is crucial for patient assessment, prioritisation of care, and planning of care. While direct instruction methods effectively explain history-taking processes and components, they provide insufficient opportunities for practice, necessitating the implementation of supplementary teaching strategies.
Objective: This study aimed to examine the effects of AI chatbot-supported history-taking training on nursing students' questioning skills and clinical stress levels.