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Understanding and Designing Computing Technologies that Convey Concerning Health News

Authors: Choe, Eun Kyoung; Duarte, Marisa E.; Kientz, Julie A.;

Understanding and Designing Computing Technologies that Convey Concerning Health News

Abstract

As people receiving health information through computing technology increases, there is a potential loss of the human element that occurs during face-to-face doctor-patient dialogue. Technologies that convey health information have the potential to cause unnecessary anxiety and worry or cause avoidance of a serious problem. The purpose of this study is to make recommendations on how to reduce the discomfort of patients by re-examining the design of health information technologies and focusing on the ways information is presented to the users. We report on a literature survey of health information technologies and results from interviews with patients, clinicians, and patients’ family members on how they communicate and accept concerning health news. We identify strategies clinicians use when giving a diagnosis, including building a partnership of trust with patients, being honest and giving hope, presenting information simply, acknowledging physical and emotional discomfort, and communicating through non-verbal means. Based on the findings, we discuss design considerations for technologies that convey concerning health news to help people assimilate the information better and make informed decisions.

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Keywords

doctor-patient interaction, Health, communication, empathy, health informatics

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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