Literature DB >> 27911096

Evaluating Health Advice in a Web 2.0 Environment: The Impact of Multiple User-Generated Factors on HIV Advice Perceptions.

Joseph B Walther1, Jeong-Woo Jang2, Ashley A Hanna Edwards3.   

Abstract

Unlike traditional media, social media systems often present information of different types from different kinds of contributors within a single message pane, a juxtaposition of potential influences that challenges traditional health communication processing. One type of social media system, question-and-answer advice systems, provides peers' answers to health-related questions, which yet other peers read and rate. Responses may appear good or bad, responders may claim expertise, and others' aggregated evaluations of an answer's usefulness may affect readers' judgments. An experiment explored how answer feasibility, expertise claims, and user-generated ratings affected readers' assessments of advice about anonymous HIV testing. Results extend the heuristic-systematic model of persuasion (Chaiken, 1980) and warranting theory (Walther & Parks, 2002). Information that is generally associated with both systematic and heuristic processes influenced readers' evaluations. Moreover, content-level cues affected judgments about message sources unexpectedly. When conflicting cues were present, cues with greater warranting value (consensus user-generated ratings) had greater influence on outcomes than less warranted cues (self-promoted expertise). Findings present a challenge to health professionals' concerns about the reliability of online health information systems.

Mesh:

Year:  2016        PMID: 27911096     DOI: 10.1080/10410236.2016.1242036

Source DB:  PubMed          Journal:  Health Commun        ISSN: 1041-0236


  2 in total

1.  Science by social media: Attitudes towards climate change are mediated by perceived social consensus.

Authors:  Stephan Lewandowsky; John Cook; Nicolas Fay; Gilles E Gignac
Journal:  Mem Cognit       Date:  2019-11

2.  Effects of personalization and source expertise on users' health beliefs and usage intention toward health chatbots: Evidence from an online experiment.

Authors:  Yu-Li Liu; Wenjia Yan; Bo Hu; Zhuoyang Li; Yik Ling Lai
Journal:  Digit Health       Date:  2022-10-02
  2 in total

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