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The Use of Chatbots in Oncological Care: A Narrative Review

BACKGROUND: Few reports have investigated chatbots in patient care. We aimed to assess the current applications, limitations, and challenges in the literature on chatbots employed in oncological care. METHODS: We queried the PubMed database through April 2022 and included studies that investigated t...

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Autores principales: Wang, Alexander, Qian, Zhiyu, Briggs, Logan, Cole, Alexander P, Reis, Leonardo O, Trinh, Quoc-Dien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10162388/
https://www.ncbi.nlm.nih.gov/pubmed/37152273
http://dx.doi.org/10.2147/IJGM.S408208
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author Wang, Alexander
Qian, Zhiyu
Briggs, Logan
Cole, Alexander P
Reis, Leonardo O
Trinh, Quoc-Dien
author_facet Wang, Alexander
Qian, Zhiyu
Briggs, Logan
Cole, Alexander P
Reis, Leonardo O
Trinh, Quoc-Dien
author_sort Wang, Alexander
collection PubMed
description BACKGROUND: Few reports have investigated chatbots in patient care. We aimed to assess the current applications, limitations, and challenges in the literature on chatbots employed in oncological care. METHODS: We queried the PubMed database through April 2022 and included studies that investigated the use of chatbots in different phases of oncological care. The search used five different combinations of the specific terms “chatbot”, “cancer”, “oncology”, and “conversational agent”. Inclusion criteria were chatbot use in any aspect of oncological care—prevention, patient education, treatment, and surveillance. RESULTS: The initial search yielded 196 records, 21 of which met inclusion criteria. The identified chatbots mostly focused on breast and ovarian cancer (n=8), with the second most common being cervical cancer (n=3). Good patient satisfaction was reported among 14 of 21 chatbots. The most reported chatbot applications were cancer screening, prevention, risk stratification, treatment, monitoring, and management. Of 12 studies examining efficacy of care via chatbot, 9 demonstrated improvements compared to standard care. CONCLUSION: Chatbots used for oncological care to date demonstrate high user satisfaction, and many have shown efficacy in improving patient-centered communication, accessibility to cancer-related information, and access to care. Currently, chatbots are primarily limited by the need for extensive user-testing and iterative improvement before widespread implementation.
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spelling pubmed-101623882023-05-06 The Use of Chatbots in Oncological Care: A Narrative Review Wang, Alexander Qian, Zhiyu Briggs, Logan Cole, Alexander P Reis, Leonardo O Trinh, Quoc-Dien Int J Gen Med Review BACKGROUND: Few reports have investigated chatbots in patient care. We aimed to assess the current applications, limitations, and challenges in the literature on chatbots employed in oncological care. METHODS: We queried the PubMed database through April 2022 and included studies that investigated the use of chatbots in different phases of oncological care. The search used five different combinations of the specific terms “chatbot”, “cancer”, “oncology”, and “conversational agent”. Inclusion criteria were chatbot use in any aspect of oncological care—prevention, patient education, treatment, and surveillance. RESULTS: The initial search yielded 196 records, 21 of which met inclusion criteria. The identified chatbots mostly focused on breast and ovarian cancer (n=8), with the second most common being cervical cancer (n=3). Good patient satisfaction was reported among 14 of 21 chatbots. The most reported chatbot applications were cancer screening, prevention, risk stratification, treatment, monitoring, and management. Of 12 studies examining efficacy of care via chatbot, 9 demonstrated improvements compared to standard care. CONCLUSION: Chatbots used for oncological care to date demonstrate high user satisfaction, and many have shown efficacy in improving patient-centered communication, accessibility to cancer-related information, and access to care. Currently, chatbots are primarily limited by the need for extensive user-testing and iterative improvement before widespread implementation. Dove 2023-05-01 /pmc/articles/PMC10162388/ /pubmed/37152273 http://dx.doi.org/10.2147/IJGM.S408208 Text en © 2023 Wang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Review
Wang, Alexander
Qian, Zhiyu
Briggs, Logan
Cole, Alexander P
Reis, Leonardo O
Trinh, Quoc-Dien
The Use of Chatbots in Oncological Care: A Narrative Review
title The Use of Chatbots in Oncological Care: A Narrative Review
title_full The Use of Chatbots in Oncological Care: A Narrative Review
title_fullStr The Use of Chatbots in Oncological Care: A Narrative Review
title_full_unstemmed The Use of Chatbots in Oncological Care: A Narrative Review
title_short The Use of Chatbots in Oncological Care: A Narrative Review
title_sort use of chatbots in oncological care: a narrative review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10162388/
https://www.ncbi.nlm.nih.gov/pubmed/37152273
http://dx.doi.org/10.2147/IJGM.S408208
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