Navigating the Maze of Social Media Disinformation on Psychiatric Illness and Charting Paths to Reliable Information for Mental Health Professionals: Observational Study of TikTok Videos

Abstract

Background: Disinformation on social media can seriously affect mental health by spreading false information, increasing anxiety, stress, and confusion in vulnerable individuals, as well as perpetuating stigma. This flood of misleading content can undermine trust in reliable sources and heighten feelings of isolation and helplessness among users.

Objective: This study aimed to explore the phenomenon of disinformation about mental health on social media and provide recommendations to mental health professionals that would use social media platforms to create educational videos about mental health topics.

Methods: A comprehensive analysis conducted on 1000 TikTok videos from more than 16 countries, available in English, French, and Spanish, covering 26 mental health topics. The data collection was conducted using a framework on disinformation and social media. A multilayered perceptron algorithm was used to identify factors predicting disinformation. Recommendations to health professionals about the creation of informative mental health videos were designed as per the data collected.

Results: Disinformation was predominantly found in videos about neurodevelopment, mental health, personality disorders, suicide, psychotic disorders, and treatment. A machine learning model identified weak predictors of disinformation, such as an initial perceived intent to disinform and content aimed at the general public rather than a specific audience. Other factors, including content presented by licensed professionals such as a counseling resident, an ear-nose-throat surgeon, or a therapist, and country-specific variables from Ireland, Colombia, and the Philippines, as well as topics such as adjustment disorder, addiction, eating disorders, and impulse control disorders, showed a weak negative association with disinformation. In terms of engagement, only the number of favorites was significantly associated with a reduction in disinformation. Five recommendations were made to enhance the quality of educational videos about mental health on social media platforms.

Conclusions: This study is the first to provide specific, data-driven recommendations to mental health providers globally, addressing the current state of disinformation on social media. Further research is needed to assess the implementation of these recommendations by health professionals, their impact on patient health, and the quality of mental health information on social networks.

Keywords: TikTok; algorithm; artificial intelligence; disinformation; educational video; mental health; mental illness; misinformation; observational analysis; phenomenon; professional; psychiatry; psychoeducation; psychology; psychotherapy; social media; stigma.