Analysis of Tweets Containing Information Related to Rheumatological Diseases on Twitter

Adrian Abbasi-Perez, Miguel Angel Alvarez-Mon, Carolina Donat-Vargas, Miguel A. Ortega, Jorge Monserrat, Ana Perez-Gomez, Ignacio Sanz and Melchor Alvarez-Mon
Additional contact information
Adrian Abbasi-Perez: Service of Internal Medicine and Rheumatology, Autoimmune Diseases University Hospital “Principe de Asturias”, 28805 Alcala de Henares, Spain
Miguel Angel Alvarez-Mon: Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcala, 28805 Alcala de Henares, Spain
Carolina Donat-Vargas: Carol Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, 17177 Stockholm, Sweden
Miguel A. Ortega: Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcala, 28805 Alcala de Henares, Spain
Jorge Monserrat: Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcala, 28805 Alcala de Henares, Spain
Ana Perez-Gomez: Service of Internal Medicine and Rheumatology, Autoimmune Diseases University Hospital “Principe de Asturias”, 28805 Alcala de Henares, Spain
Ignacio Sanz: Division of Immunology and Rheumatology, Department of Medicine, Emory University, Atlanta, GA 30322, USA
Melchor Alvarez-Mon: Service of Internal Medicine and Rheumatology, Autoimmune Diseases University Hospital “Principe de Asturias”, 28805 Alcala de Henares, Spain

IJERPH, 2021, vol. 18, issue 17, 1-15

Abstract: Background: Tweets often indicate the interests of Twitter users. Data from Twitter could be used to better understand the interest in and perceptions of a variety of diseases and medical conditions, including rheumatological diseases which have increased in prevalence over the past several decades. The aim of this study was to perform a content analysis of tweets referring to rheumatological diseases. Methods: The content of each tweet was rated as medical (including a reference to diagnosis, treatment, or other aspects of the disease) or non-medical (such as requesting help). The type of user and the suitability of the medical content (appropriate content or, on the contrary, fake content if it was medically inappropriate according to the current medical knowledge) were also evaluated. The number of retweets and likes generated were also investigated. Results: We analyzed a total of 1514 tweets: 1093 classified as medical and 421 as non-medical. The diseases with more tweets were the most prevalent. Within the medical tweets, the content of these varied according to the disease (some more focused on diagnosis and others on treatment). The fake content came from unidentified users and mostly referred to the treatment of diseases. Conclusions: According to our results, the analysis of content posted on Twitter in regard to rheumatological diseases may be useful for investigating the public’s prevailing areas of interest, concerns and opinions. Thus, it could facilitate communication between health care professionals and patients, and ultimately improve the doctor–patient relationship. Due to the interest shown in medical issues it seems desirable to have healthcare institutions and healthcare workers involved in Twitter.

Keywords: Twitter; rheumatology; social media; public health; health communication (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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