Mental illness (MI), and particularly, bipolar disorder (BD), are highly stigmatized. However, it is unknown if this stigma is also represented on social media. Characterize Twitter-based stigma and social support messaging ("tweets") about mental health/illness (MH)/MI and BD and determine which tweets garnered retweets. We collected tweets about MH/MI and BD during a three-month period and analyzed tweets from dates with the most tweets ("spikes"), an indicator of topic interest. A sample was manually content analyzed, and the remainder were classified using machine learning (logistic regression) by topic, stigma, and social support messaging. We compared stigma and support toward MH/MI versus BD and used logistic regression to quantify tweet features associated with retweets, to assess tweet reach. Of the 1,270,902 tweets analyzed, 94.7% discussed MH/MI and 5.3% discussed BD. Spikes coincided with a celebrity's death and a MH awareness campaign. Although the sample contained more support than stigma messaging, BD tweets contained more stigma and less support than MH/MI tweets. However, stigma messaging was infrequently retweeted, and users often retweeted personal MH experiences. These findings demonstrate opportunities for social media advocacy to reduce stigma and increase displays of social support towards people living with BD.
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http://dx.doi.org/10.1080/09638237.2019.1677878 | DOI Listing |
J Nurs Adm
December 2024
Author Affiliations: Assistant Professor (Dr Prothero) and Nurse (Sorhus and Huefner), College of Nursing, Brigham Young University, Provo, Utah.
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Proc Natl Acad Sci U S A
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UK Health Security Agency, London, United Kingdom.
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New College of Florida, Sarasota, FL, United States.
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