"Do You Ladies Relate?": Experiences of Gender Diverse People in Online Eating Disorder Communities
Jessica L. Feuston, Michael Ann DeVito, Morgan Klaus Scheuerman, Katy Weathington, Marianna Benitez, Bianca Z. Perez, Lucy Sondheim, Jed R. Brubaker
Abstract
The study of eating disorders online has a long tradition within CSCW and HCI scholarship. Research within this body of work highlights the types of content people with eating disorders post as well as the ways in which individuals use online spaces for acceptance, connection, and support. However, despite nearly a decade of research, online eating disorder scholarship in CSCW and HCI rarely accounts for the ways gender shapes online engagement. In this paper, we present empirical results from interviews with 14 trans people with eating disorders. Our findings illustrate how working with gender as an analytic lens allowed us to produce new knowledge about the embodiment of participation in online eating disorder spaces. We show how trans people with eating disorders use online eating disorder content to inform and set goals for their bodies and how, as gender minorities within online eating disorder spaces, trans people occupy marginal positions that make them more susceptible to harms, such as threats to eating disorder validity and gender authenticity. In our discussion, we consider life transitions in the context of gender and eating disorders and address how online eating disorder spaces operate as social transition machinery. We also call attention to the labor associated with online participation as a gender minority within online eating disorder spaces, outlining several design recommendations for supporting the ways trans people with eating disorders use online spaces. CONTENT WARNING: This paper is about the online experiences of trans people with eating disorders. We discuss eating disorders, related content (e.g., thinspiration) and practices (e.g., binge eating, restriction), and gender dysphoria. Please read with caution.
CCS Concepts: • Human-centered computing → Empirical studies in collaborative and social computing.
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