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Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey

BACKGROUND: Healthcare is expected to increasingly integrate technologies enabled by artificial intelligence (AI) into patient care. Understanding perceptions of these tools is essential to successful development and adoption. This exploratory study gauged participants’ level of openness, concern, a...

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Autores principales: Antes, Alison L., Burrous, Sara, Sisk, Bryan A., Schuelke, Matthew J., Keune, Jason D., DuBois, James M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293482/
https://www.ncbi.nlm.nih.gov/pubmed/34284756
http://dx.doi.org/10.1186/s12911-021-01586-8
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author Antes, Alison L.
Burrous, Sara
Sisk, Bryan A.
Schuelke, Matthew J.
Keune, Jason D.
DuBois, James M.
author_facet Antes, Alison L.
Burrous, Sara
Sisk, Bryan A.
Schuelke, Matthew J.
Keune, Jason D.
DuBois, James M.
author_sort Antes, Alison L.
collection PubMed
description BACKGROUND: Healthcare is expected to increasingly integrate technologies enabled by artificial intelligence (AI) into patient care. Understanding perceptions of these tools is essential to successful development and adoption. This exploratory study gauged participants’ level of openness, concern, and perceived benefit associated with AI-driven healthcare technologies. We also explored socio-demographic, health-related, and psychosocial correlates of these perceptions. METHODS: We developed a measure depicting six AI-driven technologies that either diagnose, predict, or suggest treatment. We administered the measure via an online survey to adults (N = 936) in the United States using MTurk, a crowdsourcing platform. Participants indicated their level of openness to using the AI technology in the healthcare scenario. Items reflecting potential concerns and benefits associated with each technology accompanied the scenarios. Participants rated the extent that the statements of concerns and benefits influenced their perception of favorability toward the technology. Participants completed measures of socio-demographics, health variables, and psychosocial variables such as trust in the healthcare system and trust in technology. Exploratory and confirmatory factor analyses of the concern and benefit items identified two factors representing overall level of concern and perceived benefit. Descriptive analyses examined levels of openness, concern, and perceived benefit. Correlational analyses explored associations of socio-demographic, health, and psychosocial variables with openness, concern, and benefit scores while multivariable regression models examined these relationships concurrently. RESULTS: Participants were moderately open to AI-driven healthcare technologies (M = 3.1/5.0 ± 0.9), but there was variation depending on the type of application, and the statements of concerns and benefits swayed views. Trust in the healthcare system and trust in technology were the strongest, most consistent correlates of openness, concern, and perceived benefit. Most other socio-demographic, health-related, and psychosocial variables were less strongly, or not, associated, but multivariable models indicated some personality characteristics (e.g., conscientiousness and agreeableness) and socio-demographics (e.g., full-time employment, age, sex, and race) were modestly related to perceptions. CONCLUSIONS: Participants’ openness appears tenuous, suggesting early promotion strategies and experiences with novel AI technologies may strongly influence views, especially if implementation of AI technologies increases or undermines trust. The exploratory nature of these findings warrants additional research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-021-01586-8.
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spelling pubmed-82934822021-07-21 Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey Antes, Alison L. Burrous, Sara Sisk, Bryan A. Schuelke, Matthew J. Keune, Jason D. DuBois, James M. BMC Med Inform Decis Mak Research BACKGROUND: Healthcare is expected to increasingly integrate technologies enabled by artificial intelligence (AI) into patient care. Understanding perceptions of these tools is essential to successful development and adoption. This exploratory study gauged participants’ level of openness, concern, and perceived benefit associated with AI-driven healthcare technologies. We also explored socio-demographic, health-related, and psychosocial correlates of these perceptions. METHODS: We developed a measure depicting six AI-driven technologies that either diagnose, predict, or suggest treatment. We administered the measure via an online survey to adults (N = 936) in the United States using MTurk, a crowdsourcing platform. Participants indicated their level of openness to using the AI technology in the healthcare scenario. Items reflecting potential concerns and benefits associated with each technology accompanied the scenarios. Participants rated the extent that the statements of concerns and benefits influenced their perception of favorability toward the technology. Participants completed measures of socio-demographics, health variables, and psychosocial variables such as trust in the healthcare system and trust in technology. Exploratory and confirmatory factor analyses of the concern and benefit items identified two factors representing overall level of concern and perceived benefit. Descriptive analyses examined levels of openness, concern, and perceived benefit. Correlational analyses explored associations of socio-demographic, health, and psychosocial variables with openness, concern, and benefit scores while multivariable regression models examined these relationships concurrently. RESULTS: Participants were moderately open to AI-driven healthcare technologies (M = 3.1/5.0 ± 0.9), but there was variation depending on the type of application, and the statements of concerns and benefits swayed views. Trust in the healthcare system and trust in technology were the strongest, most consistent correlates of openness, concern, and perceived benefit. Most other socio-demographic, health-related, and psychosocial variables were less strongly, or not, associated, but multivariable models indicated some personality characteristics (e.g., conscientiousness and agreeableness) and socio-demographics (e.g., full-time employment, age, sex, and race) were modestly related to perceptions. CONCLUSIONS: Participants’ openness appears tenuous, suggesting early promotion strategies and experiences with novel AI technologies may strongly influence views, especially if implementation of AI technologies increases or undermines trust. The exploratory nature of these findings warrants additional research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-021-01586-8. BioMed Central 2021-07-20 /pmc/articles/PMC8293482/ /pubmed/34284756 http://dx.doi.org/10.1186/s12911-021-01586-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Antes, Alison L.
Burrous, Sara
Sisk, Bryan A.
Schuelke, Matthew J.
Keune, Jason D.
DuBois, James M.
Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
title Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
title_full Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
title_fullStr Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
title_full_unstemmed Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
title_short Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
title_sort exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293482/
https://www.ncbi.nlm.nih.gov/pubmed/34284756
http://dx.doi.org/10.1186/s12911-021-01586-8
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