Eating disorders are among the most impairing mental health conditions, yet most people who need treatment never receive it, and those who are marginalized or disadvantaged are least likely to get care. That gap is what motivates my work.
I use intensive longitudinal methods (e.g., ecological momentary assessment) and advanced statistical approaches to understand the processes that drive eating disorders and other common mental health conditions (e.g., depression, anxiety) in adults and adolescents.
I also develop and test scalable, technology-enabled mental health interventions (e.g., apps, websites), evaluate what works and for whom, and work to increase access through implementation in real-world settings inside and outside of the healthcare system (e.g., schools, mental health clinics, online spaces).
Understanding what keeps eating disorders going
Using intensive longitudinal methods and advanced statistics to study the psychological mechanisms (e.g., mood, social experiences) that drive disordered eating.
View projectsGetting effective care to the people who need it
Developing and testing digital interventions, studying who they reach and benefit, and embedding them in the settings where people can actually access them.
View projectsTheme 1 — Understanding mechanisms
Dynamic Relations Between Interpersonal Stressors, Affective States, and Binge Eating in Adolescent Girls
My NIMH F31-funded dissertation used EMA and dynamic structural equation modeling to examine whether interpersonal stressors trigger negative affect that, in turn, drives binge eating in adolescent girls with binge-spectrum eating disorders. Findings have direct implications for just-in-time adaptive interventions that deliver support when and where risk is elevated.
Disentangling Dietary Restraint and Restriction as Predictors of Loss-of-Control Eating
Using EMA, this study distinguished between attempts to restrict eating and actual restriction, finding that the attempt (regardless of whether it succeeded) predicted subsequent loss-of-control eating, while actual restriction did not. (D'Adamo, Sonnenblick, Juarascio, & Manasse, 2023, Eating Behaviors)
Related work
Theme 2 — Access & intervention
Adolescent Perspectives on Digital Mental Health Tools
A qualitative interview study with adolescents with eating disorders exploring how they understand their own eating patterns and what they want from digital mental health supports, including their thoughts/experiences with AI and mental health help-seeking. Findings will directly inform a future co-designed intervention.
Online Platform for Provider Training in CBT Guided Self-Help for Eating Disorders
I led the mixed methods analysis and write-up of a project that developed and usability-tested an "all in one" platform for training non-specialist providers in CBT guided self-help for eating disorders and supporting implementation of this treatment with patients. Using a human-centered design approach, we tested and iteratively refined the platform based on feedback from providers and patients primarily in community mental health settings. (D'Adamo, Laboe, Goldberg, Howe, et al., 2025, BMC Digital Health)
Chatbot Intervention to Promote Eating Disorder Services Use: Examining Uptake and Predictors and Moderators of Effectiveness
Contributing to NIH-funded work developing and optimizing a chatbot to promote mental health services use among individuals who screen positive for eating disorders on an online screen. I have led two secondary projects examining 1) rates and correlates of chatbot uptake and 2) predictors and moderators of its effects on help-seeking and related outcomes. (D'Adamo et al., 2024, Eur Eat Disord Rev; D'Adamo et al., under review)
Related work