The purpose of this study is to test an eating disorders prevention digital chatbot program in a diverse group of adolescents.
Eating disorders (EDs) are impacting youth at extreme rates, with up to 22% of adolescents reporting ED symptoms, and are associated with very high psychiatric comorbidity. Since adolescence is a critical period for the onset of eating disorders, prevention during this stage is essential to reducing lifetime prevalence. Interventions have been developed to prevent the onset of these devastating disorders, but these programs are generally not publicly available and rarely offer support for addressing comorbidity or the unique needs of vulnerable subpopulations (e.g., low-income populations, sexual and gender minorities, racial/ethnic minorities, those from rural areas), who are even less likely to have access to high-quality care. One scalable, engaging, easy-to use, and convenient approach to increasing access to evidence-based EDs prevention for underserved groups involves using a chatbot. This project will adapt our team's existing EDs prevention chatbot for use with adolescents, including those from diverse backgrounds, and evaluate its effectiveness. Our deep industry and non-profit partnerships will ensure scalability and ultimate real-world impact.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
400
Wysa is a digital rules-based chatbot program platform offering cognitive-behavioral therapy-based guided self-help modules, including five modules for eating and body image developed by our team. Participants in this arm will engage with the digital chatbot program daily for three months to complete all five modules.
Washington University in St. Louis
St Louis, Missouri, United States
RECRUITINGED risk factors; Weight Concerns Scale
Weight concerns scale as found in the Stanford Washington Eating Disorder (SWED) screen is a 5-item validated self-report questionnaire which measures concern with weight and dieting. Each item is scored on a 5-100 scale, then an average is computed across all 5 items for a 0-100 score.
Time frame: 6 - months
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