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Proceedings of the Association for Information Science and Technology
Article . 2021 . Peer-reviewed
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Predicting Surrogates' Health Information Seeking Behavior via Information Source and Information Evaluation

Authors: Yung-Sheng Chang; Yan Zhang 0005; Jacek Gwizdka;

Predicting Surrogates' Health Information Seeking Behavior via Information Source and Information Evaluation

Abstract

AbstractThis study investigates surrogates' health information sharing behavior through information sources and information evaluation. A lab‐based experiment was conducted. Twenty‐five participants read five scenarios, each with three preselected webpages from a government, a commercial, and an online forum source. Participants had to decide whether to share the information with an imaginary friend of theirs and provide rationales (an indication of information evaluation). Content analysis and mixed effects logistic regression models were performed. Government websites were recommended for sharing the most, followed by commercial and online forum sources. Criteria predicting participants' intention to share information were different for each information source. The content's usefulness and trustworthiness were two criteria predicting participants' intention to share commercial websites. Source's trustworthiness and individual relevant criterion were two significant predictors for government sources. Source's trustworthiness had negative effects on sharing information from online forums. 13.3% of the information evaluation involved using both positive and negative criteria.

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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!
4
Top 10%
Average
Top 10%
gold