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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 22, 2019
Open Peer Review Period: Mar 25, 2019 - Mar 29, 2019
Date Accepted: Apr 30, 2019
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

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

Alvarez-Mon MA, Llavero-Valero M, Sánchez-Bayona R, Pereira-Sanchez V, Vallejo-Valdivielso M, Monserrat J, Lahera G, Asunsolo del Barco A, Alvarez-Mon M

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

J Med Internet Res 2019;21(5):e14110

DOI: 10.2196/14110

PMID: 31140438

PMCID: 6658306

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

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

  • 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

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.


 Citation

Please cite as:

Alvarez-Mon MA, Llavero-Valero M, Sánchez-Bayona R, Pereira-Sanchez V, Vallejo-Valdivielso M, Monserrat J, Lahera G, Asunsolo del Barco A, Alvarez-Mon M

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

J Med Internet Res 2019;21(5):e14110

DOI: 10.2196/14110

PMID: 31140438

PMCID: 6658306

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