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Health-focused conversational agents in person-centered care: a review of apps
Health-focused apps with chatbots (“healthbots”) have a critical role in addressing gaps in quality healthcare. There is limited evidence on how such healthbots are developed and applied in practice. Our review of healthbots aims to classify types of healthbots, contexts of use, and their natural la...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8854396/ https://www.ncbi.nlm.nih.gov/pubmed/35177772 http://dx.doi.org/10.1038/s41746-022-00560-6 |
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author | Parmar, Pritika Ryu, Jina Pandya, Shivani Sedoc, João Agarwal, Smisha |
author_facet | Parmar, Pritika Ryu, Jina Pandya, Shivani Sedoc, João Agarwal, Smisha |
author_sort | Parmar, Pritika |
collection | PubMed |
description | Health-focused apps with chatbots (“healthbots”) have a critical role in addressing gaps in quality healthcare. There is limited evidence on how such healthbots are developed and applied in practice. Our review of healthbots aims to classify types of healthbots, contexts of use, and their natural language processing capabilities. Eligible apps were those that were health-related, had an embedded text-based conversational agent, available in English, and were available for free download through the Google Play or Apple iOS store. Apps were identified using 42Matters software, a mobile app search engine. Apps were assessed using an evaluation framework addressing chatbot characteristics and natural language processing features. The review suggests uptake across 33 low- and high-income countries. Most healthbots are patient-facing, available on a mobile interface and provide a range of functions including health education and counselling support, assessment of symptoms, and assistance with tasks such as scheduling. Most of the 78 apps reviewed focus on primary care and mental health, only 6 (7.59%) had a theoretical underpinning, and 10 (12.35%) complied with health information privacy regulations. Our assessment indicated that only a few apps use machine learning and natural language processing approaches, despite such marketing claims. Most apps allowed for a finite-state input, where the dialogue is led by the system and follows a predetermined algorithm. Healthbots are potentially transformative in centering care around the user; however, they are in a nascent state of development and require further research on development, automation and adoption for a population-level health impact. |
format | Online Article Text |
id | pubmed-8854396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88543962022-03-04 Health-focused conversational agents in person-centered care: a review of apps Parmar, Pritika Ryu, Jina Pandya, Shivani Sedoc, João Agarwal, Smisha NPJ Digit Med Review Article Health-focused apps with chatbots (“healthbots”) have a critical role in addressing gaps in quality healthcare. There is limited evidence on how such healthbots are developed and applied in practice. Our review of healthbots aims to classify types of healthbots, contexts of use, and their natural language processing capabilities. Eligible apps were those that were health-related, had an embedded text-based conversational agent, available in English, and were available for free download through the Google Play or Apple iOS store. Apps were identified using 42Matters software, a mobile app search engine. Apps were assessed using an evaluation framework addressing chatbot characteristics and natural language processing features. The review suggests uptake across 33 low- and high-income countries. Most healthbots are patient-facing, available on a mobile interface and provide a range of functions including health education and counselling support, assessment of symptoms, and assistance with tasks such as scheduling. Most of the 78 apps reviewed focus on primary care and mental health, only 6 (7.59%) had a theoretical underpinning, and 10 (12.35%) complied with health information privacy regulations. Our assessment indicated that only a few apps use machine learning and natural language processing approaches, despite such marketing claims. Most apps allowed for a finite-state input, where the dialogue is led by the system and follows a predetermined algorithm. Healthbots are potentially transformative in centering care around the user; however, they are in a nascent state of development and require further research on development, automation and adoption for a population-level health impact. Nature Publishing Group UK 2022-02-17 /pmc/articles/PMC8854396/ /pubmed/35177772 http://dx.doi.org/10.1038/s41746-022-00560-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Parmar, Pritika Ryu, Jina Pandya, Shivani Sedoc, João Agarwal, Smisha Health-focused conversational agents in person-centered care: a review of apps |
title | Health-focused conversational agents in person-centered care: a review of apps |
title_full | Health-focused conversational agents in person-centered care: a review of apps |
title_fullStr | Health-focused conversational agents in person-centered care: a review of apps |
title_full_unstemmed | Health-focused conversational agents in person-centered care: a review of apps |
title_short | Health-focused conversational agents in person-centered care: a review of apps |
title_sort | health-focused conversational agents in person-centered care: a review of apps |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8854396/ https://www.ncbi.nlm.nih.gov/pubmed/35177772 http://dx.doi.org/10.1038/s41746-022-00560-6 |
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