Cargando…

Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter

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 com...

Descripción completa

Detalles Bibliográficos
Autores principales: Alvarez-Mon, Miguel Angel, Llavero-Valero, María, Sánchez-Bayona, Rodrigo, Pereira-Sanchez, Victor, Vallejo-Valdivielso, Maria, Monserrat, Jorge, Lahera, Guillermo, Asunsolo del Barco, Angel, Alvarez-Mon, Melchor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658306/
https://www.ncbi.nlm.nih.gov/pubmed/31140438
http://dx.doi.org/10.2196/14110
_version_ 1783438944137904128
author Alvarez-Mon, Miguel Angel
Llavero-Valero, María
Sánchez-Bayona, Rodrigo
Pereira-Sanchez, Victor
Vallejo-Valdivielso, Maria
Monserrat, Jorge
Lahera, Guillermo
Asunsolo del Barco, Angel
Alvarez-Mon, Melchor
author_facet Alvarez-Mon, Miguel Angel
Llavero-Valero, María
Sánchez-Bayona, Rodrigo
Pereira-Sanchez, Victor
Vallejo-Valdivielso, Maria
Monserrat, Jorge
Lahera, Guillermo
Asunsolo del Barco, Angel
Alvarez-Mon, Melchor
author_sort Alvarez-Mon, Miguel Angel
collection PubMed
description 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.
format Online
Article
Text
id pubmed-6658306
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-66583062019-07-31 Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter Alvarez-Mon, Miguel Angel Llavero-Valero, María Sánchez-Bayona, Rodrigo Pereira-Sanchez, Victor Vallejo-Valdivielso, Maria Monserrat, Jorge Lahera, Guillermo Asunsolo del Barco, Angel Alvarez-Mon, Melchor J Med Internet Res Original Paper 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. JMIR Publications 2019-05-28 /pmc/articles/PMC6658306/ /pubmed/31140438 http://dx.doi.org/10.2196/14110 Text en ©Miguel Angel Alvarez-Mon, María Llavero-Valero, Rodrigo Sánchez-Bayona, Victor Pereira-Sanchez, Maria Vallejo-Valdivielso, Jorge Monserrat, Guillermo Lahera, Angel Asunsolo del Barco, Melchor Alvarez-Mon. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.05.2019. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Alvarez-Mon, Miguel Angel
Llavero-Valero, María
Sánchez-Bayona, Rodrigo
Pereira-Sanchez, Victor
Vallejo-Valdivielso, Maria
Monserrat, Jorge
Lahera, Guillermo
Asunsolo del Barco, Angel
Alvarez-Mon, Melchor
Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter
title Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter
title_full Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter
title_fullStr Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter
title_full_unstemmed Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter
title_short Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter
title_sort areas of interest and stigmatic attitudes of the general public in five relevant medical conditions: thematic and quantitative analysis using twitter
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658306/
https://www.ncbi.nlm.nih.gov/pubmed/31140438
http://dx.doi.org/10.2196/14110
work_keys_str_mv AT alvarezmonmiguelangel areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT llaverovaleromaria areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT sanchezbayonarodrigo areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT pereirasanchezvictor areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT vallejovaldivielsomaria areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT monserratjorge areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT laheraguillermo areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT asunsolodelbarcoangel areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter
AT alvarezmonmelchor areasofinterestandstigmaticattitudesofthegeneralpublicinfiverelevantmedicalconditionsthematicandquantitativeanalysisusingtwitter