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Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey
BACKGROUND: Conversational agents (CAs) have been developed in outpatient departments to improve physician-patient communication efficiency. As end users, patients’ continuance intention is essential for the sustainable development of CAs. OBJECTIVE: The aim of this study was to facilitate the succe...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679947/ https://www.ncbi.nlm.nih.gov/pubmed/36342768 http://dx.doi.org/10.2196/40681 |
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author | Li, Xingyi Xie, Shirong Ye, Zhengqiang Ma, Shishi Yu, Guangjun |
author_facet | Li, Xingyi Xie, Shirong Ye, Zhengqiang Ma, Shishi Yu, Guangjun |
author_sort | Li, Xingyi |
collection | PubMed |
description | BACKGROUND: Conversational agents (CAs) have been developed in outpatient departments to improve physician-patient communication efficiency. As end users, patients’ continuance intention is essential for the sustainable development of CAs. OBJECTIVE: The aim of this study was to facilitate the successful usage of CAs by identifying key factors influencing patients’ continuance intention and proposing corresponding managerial implications. METHODS: This study proposed an extended expectation-confirmation model and empirically tested the model via a cross-sectional field survey. The questionnaire included demographic characteristics, multiple-item scales, and an optional open-ended question on patients’ specific expectations for CAs. Partial least squares structural equation modeling was applied to assess the model and hypotheses. The qualitative data were analyzed via thematic analysis. RESULTS: A total of 172 completed questionaries were received, with a 100% (172/172) response rate. The proposed model explained 75.5% of the variance in continuance intention. Both satisfaction (β=.68; P<.001) and perceived usefulness (β=.221; P=.004) were significant predictors of continuance intention. Patients' extent of confirmation significantly and positively affected both perceived usefulness (β=.817; P<.001) and satisfaction (β=.61; P<.001). Contrary to expectations, perceived ease of use had no significant impact on perceived usefulness (β=.048; P=.37), satisfaction (β=−.004; P=.63), and continuance intention (β=.026; P=.91). The following three themes were extracted from the 74 answers to the open-ended question: personalized interaction, effective utilization, and clear illustrations. CONCLUSIONS: This study identified key factors influencing patients’ continuance intention toward CAs. Satisfaction and perceived usefulness were significant predictors of continuance intention (P<.001 and P<.004, respectively) and were significantly affected by patients’ extent of confirmation (P<.001 and P<.001, respectively). Developing a better understanding of patients’ continuance intention can help administrators figure out how to facilitate the effective implementation of CAs. Efforts should be made toward improving the aspects that patients reasonably expect CAs to have, which include personalized interactions, effective utilization, and clear illustrations. |
format | Online Article Text |
id | pubmed-9679947 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-96799472022-11-23 Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey Li, Xingyi Xie, Shirong Ye, Zhengqiang Ma, Shishi Yu, Guangjun J Med Internet Res Original Paper BACKGROUND: Conversational agents (CAs) have been developed in outpatient departments to improve physician-patient communication efficiency. As end users, patients’ continuance intention is essential for the sustainable development of CAs. OBJECTIVE: The aim of this study was to facilitate the successful usage of CAs by identifying key factors influencing patients’ continuance intention and proposing corresponding managerial implications. METHODS: This study proposed an extended expectation-confirmation model and empirically tested the model via a cross-sectional field survey. The questionnaire included demographic characteristics, multiple-item scales, and an optional open-ended question on patients’ specific expectations for CAs. Partial least squares structural equation modeling was applied to assess the model and hypotheses. The qualitative data were analyzed via thematic analysis. RESULTS: A total of 172 completed questionaries were received, with a 100% (172/172) response rate. The proposed model explained 75.5% of the variance in continuance intention. Both satisfaction (β=.68; P<.001) and perceived usefulness (β=.221; P=.004) were significant predictors of continuance intention. Patients' extent of confirmation significantly and positively affected both perceived usefulness (β=.817; P<.001) and satisfaction (β=.61; P<.001). Contrary to expectations, perceived ease of use had no significant impact on perceived usefulness (β=.048; P=.37), satisfaction (β=−.004; P=.63), and continuance intention (β=.026; P=.91). The following three themes were extracted from the 74 answers to the open-ended question: personalized interaction, effective utilization, and clear illustrations. CONCLUSIONS: This study identified key factors influencing patients’ continuance intention toward CAs. Satisfaction and perceived usefulness were significant predictors of continuance intention (P<.001 and P<.004, respectively) and were significantly affected by patients’ extent of confirmation (P<.001 and P<.001, respectively). Developing a better understanding of patients’ continuance intention can help administrators figure out how to facilitate the effective implementation of CAs. Efforts should be made toward improving the aspects that patients reasonably expect CAs to have, which include personalized interactions, effective utilization, and clear illustrations. JMIR Publications 2022-11-07 /pmc/articles/PMC9679947/ /pubmed/36342768 http://dx.doi.org/10.2196/40681 Text en ©Xingyi Li, Shirong Xie, Zhengqiang Ye, Shishi Ma, Guangjun Yu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 07.11.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Li, Xingyi Xie, Shirong Ye, Zhengqiang Ma, Shishi Yu, Guangjun Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey |
title | Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey |
title_full | Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey |
title_fullStr | Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey |
title_full_unstemmed | Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey |
title_short | Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey |
title_sort | investigating patients' continuance intention toward conversational agents in outpatient departments: cross-sectional field survey |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679947/ https://www.ncbi.nlm.nih.gov/pubmed/36342768 http://dx.doi.org/10.2196/40681 |
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