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Patient learning choices in an online health infomediary.

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Title: Patient learning choices in an online health infomediary.
Authors: Yim, Dobin1 (AUTHOR), Khuntia, Jiban2 (AUTHOR) jiban.khuntia@ucdenver.edu, Duan, Wenjing3 (AUTHOR)
Source: European Journal of Information Systems. Apr2025, Vol. 34 Issue 2, p277-322. 46p.
Abstract: Health infomediaries are online interactive platforms where patients learn about diseases, procedures, and treatments, but how the learning dynamics evolve to help patients make decisions is unknown. Investigating patient learning in health information is essential to enabling patient empowerment using these platforms. In this study, we theoretically anchor patients' learning processes in a health infomediary to Nonaka-Takeuchi's Socialization, Externalization, Combination, and Internalization (SECI) learning dynamics model, with the infomediary as the ba or collaborative space for learning. We posit that questions reflect externalization for a focal learning patient, while reviews and comments reflect socialization, driving patients' knowledge internalization. Learning with more information aids patients in health-relevant choices and actions such as a doctor consultation in a health infomediary. Three hypotheses about continued learning choices are presented and tested using data from 8,900 reconstructive surgery health infomediary users, using a multichoice mixed logit model with panel estimations. Findings show patients continue to review and comment more than questions to learn about trendy surgeries, which is counterintuitive to existing insights, whereas questions lead to learning sentiment-laden information. Exploratory analyses suggest that learning through reviews regarding post-procedural services may deter, but other learning modes motivate patients to consult a doctor. We discuss the theoretical contributions and implications for infomediary design and research. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Information Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Patient learning choices in an online health infomediary.
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  Data: <searchLink fieldCode="AR" term="%22Yim%2C+Dobin%22">Yim, Dobin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khuntia%2C+Jiban%22">Khuntia, Jiban</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jiban.khuntia@ucdenver.edu</i><br /><searchLink fieldCode="AR" term="%22Duan%2C+Wenjing%22">Duan, Wenjing</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Information+Systems%22">European Journal of Information Systems</searchLink>. Apr2025, Vol. 34 Issue 2, p277-322. 46p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Health infomediaries are online interactive platforms where patients learn about diseases, procedures, and treatments, but how the learning dynamics evolve to help patients make decisions is unknown. Investigating patient learning in health information is essential to enabling patient empowerment using these platforms. In this study, we theoretically anchor patients' learning processes in a health infomediary to Nonaka-Takeuchi's Socialization, Externalization, Combination, and Internalization (SECI) learning dynamics model, with the infomediary as the ba or collaborative space for learning. We posit that questions reflect externalization for a focal learning patient, while reviews and comments reflect socialization, driving patients' knowledge internalization. Learning with more information aids patients in health-relevant choices and actions such as a doctor consultation in a health infomediary. Three hypotheses about continued learning choices are presented and tested using data from 8,900 reconstructive surgery health infomediary users, using a multichoice mixed logit model with panel estimations. Findings show patients continue to review and comment more than questions to learn about trendy surgeries, which is counterintuitive to existing insights, whereas questions lead to learning sentiment-laden information. Exploratory analyses suggest that learning through reviews regarding post-procedural services may deter, but other learning modes motivate patients to consult a doctor. We discuss the theoretical contributions and implications for infomediary design and research. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of European Journal of Information Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1080/0960085X.2024.2389803
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      – TitleFull: Patient learning choices in an online health infomediary.
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            NameFull: Yim, Dobin
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              Text: Apr2025
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              Y: 2025
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