Literature DB >> 22134096

Epilepsy in the Twitter era: a need to re-tweet the way we think about seizures.

K McNeil1, P M Brna, K E Gordon.   

Abstract

Seizures have long been associated with misconceptions and stigma. Exponential growth in Internet use has seen the rapid expansion of social media, such as Twitter, for health promotion. In view of the popularity of Twitter, we sought to explore how seizures are being portrayed on this social networking website and to consider its potential for information dissemination. A 48-hour Twitter search was used as a preliminary data set to determine an appropriate classification scheme of "seizure"-related posts ("tweets"). Analysis was then conducted using "seizure" tweets from a 7-consecutive day sample period. Tweets were analyzed and coded by two independent reviewers. Predominant categories were Metaphorical (32%), Personal Accounts (31%), Informative (12%), and Ridicule/Joke (9%). This study supports the notion that stigmatization associated with seizures continues to flourish, as 41% of "seizure" tweets were derogatory in nature. Although Twitter could be used to disseminate accurate information on seizures and epilepsy, this study suggests that it is currently propagating negative attitudes toward seizures with potential for fueling stigma. In recent years there have been significant advancements in technology offering many new methods of sharing information. Social networking sites allow real-time communication while providing the opportunity for exchange of information and opinions. Twitter, a website launched in 2006, allows users to communicate through "tweets" limited to 140 characters. Twitter's popularity has drastically increased since its inception, with approximately 110 million tweets per day from 200 million users worldwide, as of January 2011 (http://blogs.forbes.com/oliverchiang/2011/01/19/twitter-hits-nearly-200m-users-110m-tweets-per-day-focuses-on-global-expansion/). Such social media facilitate communication about an array of health-related topics including seizures and epilepsy.
Copyright © 2011 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 22134096     DOI: 10.1016/j.yebeh.2011.10.020

Source DB:  PubMed          Journal:  Epilepsy Behav        ISSN: 1525-5050            Impact factor:   2.937


  14 in total

1.  Mining Social Media Data for Biomedical Signals and Health-Related Behavior.

Authors:  Rion Brattig Correia; Ian B Wood; Johan Bollen; Luis M Rocha
Journal:  Annu Rev Biomed Data Sci       Date:  2020-05-04

2.  Leveraging social networks for toxicovigilance.

Authors:  Michael Chary; Nicholas Genes; Andrew McKenzie; Alex F Manini
Journal:  J Med Toxicol       Date:  2013-06

3.  #PrayForDad: Learning the Semantics Behind Why Social Media Users Disclose Health Information.

Authors:  Zhijun Yin; You Chen; Daniel Fabbri; Jimeng Sun; Bradley Malin
Journal:  Proc Int AAAI Conf Weblogs Soc Media       Date:  2016-05

Review 4.  Stigma in epilepsy.

Authors:  Kirsten M Fiest; Gretchen L Birbeck; Ann Jacoby; Nathalie Jette
Journal:  Curr Neurol Neurosci Rep       Date:  2014-05       Impact factor: 5.081

Review 5.  Epilepsy misconceptions and stigma reduction: Current status in Western countries.

Authors:  Lynn K Herrmann; Elisabeth Welter; Anne T Berg; Adam T Perzynski; Jamie R Van Doren; Martha Sajatovic
Journal:  Epilepsy Behav       Date:  2016-05-18       Impact factor: 2.937

6.  The painful tweet: text, sentiment, and community structure analyses of tweets pertaining to pain.

Authors:  Patrick J Tighe; Ryan C Goldsmith; Michael Gravenstein; H Russell Bernard; Roger B Fillingim
Journal:  J Med Internet Res       Date:  2015-04-02       Impact factor: 5.428

7.  How Twitter Is Studied in the Medical Professions: A Classification of Twitter Papers Indexed in PubMed.

Authors:  Shirley Ann Williams; Melissa Terras; Claire Warwick
Journal:  Med 2 0       Date:  2013-07-18

8.  Patterns of Treatment Switching in Multiple Sclerosis Therapies in US Patients Active on Social Media: Application of Social Media Content Analysis to Health Outcomes Research.

Authors:  Valéry Risson; Deepanshu Saini; Ian Bonzani; Alice Huisman; Melvin Olson
Journal:  J Med Internet Res       Date:  2016-03-17       Impact factor: 5.428

9.  Using Twitter to Measure Public Discussion of Diseases: A Case Study.

Authors:  Christopher Weeg; H Andrew Schwartz; Shawndra Hill; Raina M Merchant; Catalina Arango; Lyle Ungar
Journal:  JMIR Public Health Surveill       Date:  2015-06-26

Review 10.  Toward a Mixed-Methods Research Approach to Content Analysis in The Digital Age: The Combined Content-Analysis Model and its Applications to Health Care Twitter Feeds.

Authors:  Eradah O Hamad; Marie Y Savundranayagam; Jeffrey D Holmes; Elizabeth Anne Kinsella; Andrew M Johnson
Journal:  J Med Internet Res       Date:  2016-03-08       Impact factor: 5.428

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