{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T02:12:36Z","timestamp":1776996756030,"version":"3.51.4"},"reference-count":56,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T00:00:00Z","timestamp":1725408000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["OIR"],"published-print":{"date-parts":[[2025,3,7]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>Unverified information avoidance behavior refers to the conscious effort made by individuals to avoid consuming information that has not been verified by credible sources. This behavior is essential in preventing the spread of misinformation that can hinder effective public health responses. While previous studies have examined information avoidance behavior in general, there is a lack of research specifically focusing on the avoidance of unverified information during health crises. This study aims to fill this gap by exploring factors that lead to social media users\u2019 unverified information avoidance behavior during health crises, providing novel insights into the determinants of this protective behavior.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>We based our research model on the health belief model and validated it using data collected from 424 individuals who use social media. The proposed model was tested by using the partial least squares structural equation modeling (PLS-SEM) approach.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>Our results indicate that individuals\u2019 government social media participation (following accounts and joining groups) affects their health beliefs (perceived severity and benefits of information avoidance), which in turn trigger their unverified information avoidance behavior.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>Our study contributes to the current literature of social media crisis management and information avoidance behavior. The implications of these findings for policymakers, social media platforms and theory are further discussed.<\/jats:p><\/jats:sec>","DOI":"10.1108\/oir-02-2024-0074","type":"journal-article","created":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T23:02:41Z","timestamp":1725404561000},"page":"269-289","source":"Crossref","is-referenced-by-count":6,"title":["Understanding the impact of government social media on citizens\u2019 unverified information avoidance behavior during health crises: the health belief model"],"prefix":"10.1108","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5356-4980","authenticated-orcid":false,"given":"Xueyan","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7612-9631","authenticated-orcid":false,"given":"Zhenya","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1671-6479","authenticated-orcid":false,"given":"Houcai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2024,9,4]]},"reference":[{"issue":"3","key":"key2025030709303439200_ref001","doi-asserted-by":"publisher","first-page":"613","DOI":"10.2307\/25750694","article-title":"Practicing safe computing: a multimedia empirical examination of home computer user security behavioral intentions","volume":"34","year":"2010","journal-title":"MIS Quarterly"},{"issue":"2","key":"key2025030709303439200_ref053","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1037\/0033-295X.84.2.191","article-title":"Self-efficacy: toward a unifying theory of behavioral change","volume":"84","year":"1977","journal-title":"Psychological Review"},{"issue":"2","key":"key2025030709303439200_ref002","doi-asserted-by":"publisher","DOI":"10.1016\/j.im.2019.05.003","article-title":"How to perform and report an impactful analysis using partial least squares: guidelines for confirmatory and explanatory IS research","volume":"57","year":"2020","journal-title":"Information and Management"},{"issue":"1","key":"key2025030709303439200_ref003","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.giq.2011.04.004","article-title":"The impact of polices on government social media usage: issues, challenges, and recommendations","volume":"29","year":"2012","journal-title":"Government Information Quarterly"},{"issue":"3","key":"key2025030709303439200_ref004","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1177\/135910457000100301","article-title":"Back-translation for cross-cultural research","volume":"1","year":"1970","journal-title":"Journal of Cross-Cultural Psychology"},{"issue":"3","key":"key2025030709303439200_ref005","first-page":"iii","article-title":"Towards scholarly flourishing in the IS field: stories, reflection, and actions in an emotional time","volume":"45","year":"2021","journal-title":"MIS Quarterly"},{"issue":"8","key":"key2025030709303439200_ref006","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1080\/10410236.2010.521906","article-title":"A meta-analysis of the effectiveness of health belief model variables in predicting behavior","volume":"25","year":"2010","journal-title":"Health Communication"},{"issue":"2","key":"key2025030709303439200_ref007","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1016\/j.im.2018.09.002","article-title":"How do product recommendations affect impulse buying? 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