Anxiety management strategies on TikTok: a discourse analysis of collective coping mechanisms.

Abstract

Background: This study investigates the discourse on anxiety management strategies within the TikTok platform, analyzing a substantial dataset of 45,639 comments collected over a year.

Aims: The primary aim is to explore the various strategies users employ to manage anxiety, focusing on how these strategies are discussed and shared on TikTok.

Methods: A mixed-method approach was utilized, combining Latent Dirichlet Allocation (LDA) for topic modeling with qualitative analysis. This methodology allowed for the identification of nine distinct topics, which were further grouped into three main categories: Self-Empowerment and Coping Strategies, Community Support and Social Connectivity, and Recognizing and Navigating Triggers.

Results: The analysis revealed a diverse range of strategies users employ to manage anxiety, spanning personal coping mechanisms, social support networks, and the recognition and mitigation of triggers. These findings underscore TikTok's role as a dynamic space for sharing, exploring, and validating experiences related to anxiety management.

Conclusions: TikTok offers unique opportunities for identity construction and community support amidst the challenges of anxiety. However, the study acknowledges limitations, such as potential biases in keyword-based data collection and the complexity of capturing multimodal discourse on the platform. The conclusion emphasizes the need for further refinement of digital mental health platforms, calling for sophisticated algorithmic solutions to enhance user support and content relevance.