Skip to main navigation Skip to search Skip to main content

Breaking Bias: Enhancing Healthcare Information Diagnosticity

Yi-Chen Lee*, Chih-Hung Peng, Choon-Ling Sia

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

The rising challenges of health misinformation on social media pose a critical concern, as the persistence and proliferation of inaccurate health news make it difficult for individuals to distinguish between true and false information. This research examines the alignment of perspectives between individuals and health issues, focusing on how this alignment affects the diagnosticity of health information. Two moderators, platform types and health threat impacts, are explored to deepen understanding of their effects. This research underscores the impact of information evaluations when dealing with multi-platform confirmation. Additionally, it addresses the effect of health threats on perspective alignment and their influences. Two experimental studies are proposed to enhance healthcare evaluations, recommending incorporating multiple platforms and deeper reflection on higher-risk health issues to overcome confirmation bias. The guidelines strive to contribute to a more informed and health-conscious society, mitigating the impact of misinformation and enabling informed evaluations based on accurate health information.
Original languageEnglish
Title of host publicationPACIS 2024 Proceedings
PublisherAssociation for Information Systems
Number of pages9
ISBN (Print)978-1-958200-12-4
Publication statusPublished - 2024
Event2024 Pacific Asia Conference on Information Systems (PACIS 2024): Preparing The Next Generation For The IT-Driven Future - Ho Chi Minh City, Viet Nam
Duration: 1 Jul 20245 Jul 2024
https://pacis2024.aisconferences.org/
https://aisel.aisnet.org/pacis2024/

Conference

Conference2024 Pacific Asia Conference on Information Systems (PACIS 2024)
PlaceViet Nam
CityHo Chi Minh City
Period1/07/245/07/24
Internet address

Funding

This research is partially supported by the NSTC grant 110-2410-H-002-006-MY3, NSTC grant 110-2628- H-002 -010 -MY2, NSTC grant 111-2423-H-002 -010 -MY4, NSTC grant 113-2811-H-002 -014, and Hong Kong Research Grants Council and City University of Hong Kong (Project No. CityU 11509223).

Research Keywords

  • IS healthcare
  • confirmation bias
  • perspective alignment
  • information diagnosticity
  • health threat

RGC Funding Information

  • RGC-funded

Fingerprint

Dive into the research topics of 'Breaking Bias: Enhancing Healthcare Information Diagnosticity'. Together they form a unique fingerprint.

Cite this