Literature DB >> 31266661

Twitter message types, health beliefs, and vaccine attitudes during the 2015 measles outbreak in California.

Cui Zhang Meadows1, Lu Tang2, Wenlin Liu3.   

Abstract

BACKGROUND: Social media not only provide platforms for the public to obtain information about a disease but also allow them to share their opinions and experiences about it.
METHODS: This study analyzed 3000 tweets systematically selected from over 1 million tweets posted during the 2015 California measles outbreak.
RESULTS: News updates were the most tweeted messages (41.4%), followed by personal opinions (33.7%), resources (19.4%), personal experiences (2.5%), and questions (1.6%). Susceptibility was the most discussed health belief (21.8%), followed by cues to action (18.9%) and severity (13.0%). Individuals were significantly more likely to discuss severity. Nonprofit organizations were significantly more likely to offer cues to action than other user types, and media were less likely to include cues to action than other user types. Pro-vaccine tweets were more likely to contain links to traditional mainstream media sources such as newspapers and magazines, and anti-vaccine tweets were more likely to link to emerging news websites.
CONCLUSIONS: Understanding who posts what on social media during an infectious disease outbreak allows public health agencies to better assess the public's attitudes, sentiments, and needs in order to provide timely and effective information.
Copyright © 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Health Belief Model; Measles outbreak crisis; Media sources; Social media; Vaccination

Year:  2019        PMID: 31266661     DOI: 10.1016/j.ajic.2019.05.007

Source DB:  PubMed          Journal:  Am J Infect Control        ISSN: 0196-6553            Impact factor:   2.918


  8 in total

Review 1.  Revisiting the 2014-15 Disneyland measles outbreak and its influence on pediatric vaccinations.

Authors:  Margaret K Doll; John W Correira
Journal:  Hum Vaccin Immunother       Date:  2021-09-08       Impact factor: 4.526

2.  Analyzing COVID-19 disinformation on Twitter using the hashtags #scamdemic and #plandemic: Retrospective study.

Authors:  Heather D Lanier; Marlon I Diaz; Sameh N Saleh; Christoph U Lehmann; Richard J Medford
Journal:  PLoS One       Date:  2022-06-22       Impact factor: 3.752

3.  Vaccination Refusal Debate on Social Media in Turkey: A Content Analysis of the Comments on Instagram Blogs.

Authors:  Deniz Sümeyye Yorulmaz; Havva Karadeniz
Journal:  Iran J Public Health       Date:  2022-03       Impact factor: 1.479

4.  Should vaccination be mandated? Individuals' perceptions on mandatory vaccination in Greece.

Authors:  Theodoros V Giannouchos; Evaggelia Steletou; Maria Saridi; Kyriakos Souliotis
Journal:  J Eval Clin Pract       Date:  2021-03-29       Impact factor: 2.336

5.  Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis.

Authors:  Yahya Albalawi; Nikola S Nikolov; Jim Buckley
Journal:  J Med Internet Res       Date:  2019-10-08       Impact factor: 5.428

6.  Conflicting attitudes: Analyzing social media data to understand the early discourse on COVID-19 passports.

Authors:  M Laeeq Khan; A Malik; U Ruhi; A Al-Busaidi
Journal:  Technol Soc       Date:  2021-12-08

7.  COVID-19 Echo Chambers: Examining the Impact of Conservative and Liberal News Sources on Risk Perception and Response.

Authors:  Kenneth A Lachlan; Emily Hutter; Christine Gilbert
Journal:  Health Secur       Date:  2021-01-19

8.  How News Agencies' Twitter Posts on COVID-19 Vaccines Attract Audiences' Twitter Engagement: A Content Analysis.

Authors:  Di Wang; Jiahui Lu
Journal:  Int J Environ Res Public Health       Date:  2022-02-25       Impact factor: 3.390

  8 in total

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