ArticleJournal of medical Internet research2019
Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter.
Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.
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- Exploring Pain on Social Media: Observational Study on Perceptions and Discussions of Chronic Pain Conditions.JMIR infodemiology · 2025Observational
- Stigma of Dementia on Social Media During World Alzheimer's Awareness Month: Thematic Analysis of Posts.JMIR formative research · 2025Article
- Understanding the online landscape of cannabis discourse: a Twitter analysis.Frontiers in public health · 2025Article
- Navigating Awareness and Strategies to Support Dementia Advocacy on Social Media During World Alzheimer's Month: Infodemiology Study.JMIR infodemiology · 2024Article
- Analysis of the hikikomori phenomenon - an international infodemiology study of Twitter data in Portuguese.BMC public health · 2024Article
- Regional insights on tobacco-related tweets: unveiling user opinions and usage patterns.Frontiers in public health · 2024Article
- Social networks use in the context of Schizophrenia: a review of the literature.Frontiers in psychiatry · 2024Review
- Analyzing public discourse of dementia from Spanish and English tweets: a comparative analysis with other neurological disorders.Frontiers in neurology · 2024Article
- Exploring Perceptions About Paracetamol, Tramadol, and Codeine on Twitter Using Machine Learning: Quantitative and Qualitative Observational Study.Journal of medical Internet research · 2023Observational
- Understanding Public Perceptions and Discussions on Opioids Through Twitter: Cross-Sectional Infodemiology Study.Journal of medical Internet research · 2023Article
- Assessment of beliefs and attitudes about electroconvulsive therapy posted on Twitter: An observational study.European psychiatry : the journal of the Association of European Psychiatrists · 2023Observational
- Qualitative and Artificial Intelligence-Based Sentiment Analysis of Turkish Tweets Related to Schizophrenia.Turk psikiyatri dergisi = Turkish journal of psychiatry · 2023Article
- Psychiatry on Twitter: Content Analysis of the Use of Psychiatric Terms in French.JMIR formative research · 2022Article
- Areas of Interest and Social Consideration of Antidepressants on English Tweets: A Natural Language Processing Classification Study.Journal of personalized medicine · 2022Article
- Mediterranean Diet Social Network Impact along 11 Years in the Major US Media Outlets: Thematic and Quantitative Analysis Using Twitter.International journal of environmental research and public health · 2022Article
- Examining Tweet Content and Engagement of Users With Tweets About Hikikomori in Japanese: Mixed Methods Study of Social Withdrawal.Journal of medical Internet research · 2022Article
- Analyzing Psychotherapy on Twitter: An 11-Year Analysis of Tweets From Major U.S. Media Outlets.Frontiers in psychiatry · 2022Article
- Dementia Research on Facebook and Twitter: Current Practice and Challenges.Journal of Alzheimer's disease : JAD · 2022Review
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTwitter is an indicator of real-world performance, thus, is an appropriate arena to assess the social consideration and attitudes toward psychosis.
objectiveThe 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).
methodsEach 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.
resultsWe 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.
conclusionsWe 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.