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Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment
OBJECTIVE: At the time of informed consent (IC) for coronary angiography (CAG), patients’ knowledge of the process is inadequate. Time constraints and a lack of personalization of consent are the primary causes of inadequate information. This procedure can be enhanced by obtaining IC using a chatbot...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693205/ https://www.ncbi.nlm.nih.gov/pubmed/38047164 http://dx.doi.org/10.1177/20552076231218141 |
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author | Aydin, Fatih Yildirim, Özge Turgay Aydin, Ayse Huseyinoglu Murat, Bektas Basaran, Cem Hakan |
author_facet | Aydin, Fatih Yildirim, Özge Turgay Aydin, Ayse Huseyinoglu Murat, Bektas Basaran, Cem Hakan |
author_sort | Aydin, Fatih |
collection | PubMed |
description | OBJECTIVE: At the time of informed consent (IC) for coronary angiography (CAG), patients’ knowledge of the process is inadequate. Time constraints and a lack of personalization of consent are the primary causes of inadequate information. This procedure can be enhanced by obtaining IC using a chatbot powered by artificial intelligence (AI). METHODS: In the study, patients who will undergo CAG for the first time were randomly divided into two groups, and IC was given to one group using the conventional method and the other group using an AI-supported chatbot, chatGPT3. They were then evaluated with two distinct questionnaires measuring their satisfaction and capacity to understand CAG risks. RESULTS: While the satisfaction questionnaire was equal between the two groups (p = 0.581), the correct understanding of CAG risk questionnaire was found to be significantly higher in the AI group (<0.001). CONCLUSIONS: AI can be trained to support clinicians in giving IC before CAG. In this way, the workload of healthcare professionals can be reduced while providing a better IC. |
format | Online Article Text |
id | pubmed-10693205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-106932052023-12-03 Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment Aydin, Fatih Yildirim, Özge Turgay Aydin, Ayse Huseyinoglu Murat, Bektas Basaran, Cem Hakan Digit Health Original Research OBJECTIVE: At the time of informed consent (IC) for coronary angiography (CAG), patients’ knowledge of the process is inadequate. Time constraints and a lack of personalization of consent are the primary causes of inadequate information. This procedure can be enhanced by obtaining IC using a chatbot powered by artificial intelligence (AI). METHODS: In the study, patients who will undergo CAG for the first time were randomly divided into two groups, and IC was given to one group using the conventional method and the other group using an AI-supported chatbot, chatGPT3. They were then evaluated with two distinct questionnaires measuring their satisfaction and capacity to understand CAG risks. RESULTS: While the satisfaction questionnaire was equal between the two groups (p = 0.581), the correct understanding of CAG risk questionnaire was found to be significantly higher in the AI group (<0.001). CONCLUSIONS: AI can be trained to support clinicians in giving IC before CAG. In this way, the workload of healthcare professionals can be reduced while providing a better IC. SAGE Publications 2023-11-30 /pmc/articles/PMC10693205/ /pubmed/38047164 http://dx.doi.org/10.1177/20552076231218141 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Aydin, Fatih Yildirim, Özge Turgay Aydin, Ayse Huseyinoglu Murat, Bektas Basaran, Cem Hakan Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment |
title | Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment |
title_full | Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment |
title_fullStr | Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment |
title_full_unstemmed | Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment |
title_short | Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment |
title_sort | comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: medical competence and ethical assessment |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693205/ https://www.ncbi.nlm.nih.gov/pubmed/38047164 http://dx.doi.org/10.1177/20552076231218141 |
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