Mental illness and bipolar disorder on Twitter: implications for stigma and social support
Mental illness and bipolar disorder on Twitter: implications for stigma and social support
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DOI：
10.1080/09638237.2019.1677878
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发表时间：
2019-11-06
影响因子：
3.3
通讯作者：
Massey, Philip
中科院分区：
文献类型：
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作者：
Budenz, Alexandra;Klassen, Ann;Massey, Philip
背景：精神疾病（MI），特别是双相情感障碍（BD），受到高度污名化。然而，尚不清楚这种耻辱是否也出现在社交媒体上。目标：描述基于 Twitter 的关于心理健康/疾病 (MH)/MI 和 BD 的耻辱和社会支持消息（“推文”），并确定哪些推文获得转发。方法：我们收集了三个月内有关 MH/MI 和 BD 的推文，并分析了推文最多（“峰值”）日期的推文，这是主题兴趣的指标。对样本进行手动内容分析，其余样本使用机器学习（逻辑回归）按主题、耻辱和社交支持消息进行分类。我们比较了 MH/MI 与 BD 的耻辱和支持，并使用逻辑回归来量化与转发相关的推文特征，以评估推文的覆盖范围。结果：在分析的 1,270,902 条推文中，94.7% 讨论 MH/MI，5.3% 讨论 BD。尖峰事件与一位名人的去世和 MH 宣传活动同时发生。尽管样本包含比污名消息更多的支持，但 BD 推文比 MH/MI 推文包含更多污名和更少的支持。然而，污名信息很少被转发，用户经常转发个人的 MH 经历。结论：这些发现表明社交媒体宣传有机会减少耻辱并增加对双相情感障碍患者的社会支持。
Background: Mental illness (MI), and particularly, bipolar disorder (BD), are highly stigmatized. However, it is unknown if this stigma is also represented on social media. Aims: Characterize Twitter-based stigma and social support messaging ("tweets") about mental health/illness (MH)/MI and BD and determine which tweets garnered retweets. Methods: 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. Results: 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. Conclusions: These findings demonstrate opportunities for social media advocacy to reduce stigma and increase displays of social support towards people living with BD.