Open AccessAreas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter
Author(s) -
Miguel Angel Álvarez-Mon,
María Llavero-Valero,
Rodrigo Sánchez-Bayona,
Víctor Pereira-Sánchez,
María Vallejo-Valdivielso,
Jorge Monserrat,
Guillermo Lahera,
Ángel Asúnsolo del Barco,
Melchor ÁlvarezMon
Publication year - 2019
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/14110
Subject(s) - pejorative , psychosis , medicine , content analysis , public health , thematic analysis , psychology , psychiatry , social media , family medicine , qualitative research , pathology , computer science , social science , sociology , world wide web , philosophy , linguistics
Background Twitter is an indicator of real-world performance, thus, is an appropriate arena to assess the social consideration and attitudes toward psychosis. Objective The aim of this study was to perform a mixed-methods study of the content and key metrics of tweets referring to psychosis in comparison with tweets referring to control diseases (breast cancer, diabetes, Alzheimer, and human immunodeficiency virus). Methods Each tweet’s content was rated as nonmedical (NM: testimonies, health care products, solidarity or awareness and misuse) or medical (M: included a reference to the illness’s diagnosis, treatment, prognosis, or prevention). NM tweets were classified as positive or pejorative. We assessed the appropriateness of the medical content. The number of retweets generated and the potential reach and impact of the hashtags analyzed was also investigated. Results We analyzed a total of 15,443 tweets: 8055 classified as NM and 7287 as M. Psychosis-related tweets (PRT) had a significantly higher frequency of misuse 33.3% (212/636) vs 1.15% (853/7419; P <.001) and pejorative content 36.2% (231/636) vs 11.33% (840/7419; P <.001). The medical content of the PRT showed the highest scientific appropriateness 100% (391/391) vs 93.66% (6030/6439; P <.001) and had a higher frequency of content about disease prevention. The potential reach and impact of the tweets related to psychosis were low, but they had a high retweet-to-tweet ratio. Conclusions We show a reduced number and a different pattern of contents in tweets about psychosis compared with control diseases. PRT showed a predominance of nonmedical content with increased frequencies of misuse and pejorative tone. However, the medical content of PRT showed high scientific appropriateness aimed toward prevention.