Framing Mental Health on TikTok: Stigma and Anti-Stigma Narratives in the Global South

Mental disorders are a global concern, a!ecting millions of people worldwide. From a sociological perspective, Go!man’s framing theory explains how media shape public perceptions and influence societal attitudes. Media framing plays a crucial role in shaping how mental disorders are viewed, often reinforcing social norms. Negative portrayals in traditional media can perpetuate stigma and marginalization, while positive frames can support destigmatization by emphasizing recovery, treatment, and normalization. While much research has focused on traditional media, little attention has been paid to how user-generated platforms like TikTok frame mental disorders, particularly in the Global South. With the rise of short video platforms, social media now plays a significant role in shaping societal attitudes toward mental health. This study will conduct a content analysis of TikTok videos about mental disorders, using China as an example to explore how mental health is framed in
the digital space of the Global South. Given that China has one of the largest populations in the world, the portrayal of mental disorders in Chinese new media significantly influences public perceptions and contributes to the stigma surrounding mental illness, a critical public health concern.
This study aims to analyze popular TikTok videos related to mental disorders using keywords such as “精神病” (mental disorders), “焦虑症” (anxiety disorders), “抑郁症” (depression), “躁郁症” (bipolar disorders), “PTSD” (post-traumatic stress disorder), “精神分裂” (schizophrenia), “厌食症” (eating disorders), “破坏性⾏为和社交障碍” (disruptive behavior and dissocial disorders), and “神经发育障碍 (neurodevelopmental disorders). A sample of 500 videos will be selected based on the number of likes each video receives. The coding units for social media framing of mental disorders will be developed using Slopen et al.’s (2007) framework, which categorizes media representations into four frames: (1) “dangerousness and crime,” (2) “treatment and recovery,” (3) “causation,” and (4) “mental health
system issues.” Additionally, this study will employ an inductive approach to refine these coding units specifically for social media content in China. Ultimately, the analysis will classify content as stigmatizing or non-stigmatizing to assess whether mental disorders are depicted positively or negatively on social media platforms.
By examining both stigmatizing and anti-stigma content, the research will contribute to understanding how mental health is socially constructed in this context. It will also expand framing theory by analyzing its relevance in the age of social media, where content is no longer controlled by mainstream institutions. Additionally, this study provides practical insights for leveraging platforms like TikTok in stigma reduction e!orts. The findings will inform policy recommendations for designing
e!ective anti-stigma campaigns, o!ering strategies for incorporating positive framing and inclusive messaging to promote mental health awareness and reduce stigma in the Global South.