The purpose of this study is to identify the independent and combined effects of two types of self-monitoring and two types of micro-interventions when combined with standard cognitive behavioral treatment for bulimia nervosa (BN) and binge eating disorder (BED). The primary aims of this study are (1) to evaluate the optimal complexity of Self-Monitoring and Micro-Interventions on eating pathology (at post-treatment and at 6 and 12-month follow-ups and (2) to test the hypotheses that the optimal complexity level of each component is moderated by baseline deficits in self-regulation. The secondary aim will be to test target engagement for each level of complexity for each component, i.e., to test whether higher complexity of each technological components is associated with better rates of therapeutic skill use and acquisition and that improvements in skill use and acquisition are associated with improvements in outcomes. A final exploratory aim will be to quantify the component interaction effects, which may be partially additive (because components overlap and/or there is diminishing return), fully additive, or synergistic (in that component complexities may partially depend on each other).
Bulimia Nervosa, Bulimia, Binge Eating, Binge-Eating Disorder
The purpose of this study is to identify the independent and combined effects of two types of self-monitoring and two types of micro-interventions when combined with standard cognitive behavioral treatment for bulimia nervosa (BN) and binge eating disorder (BED). The primary aims of this study are (1) to evaluate the optimal complexity of Self-Monitoring and Micro-Interventions on eating pathology (at post-treatment and at 6 and 12-month follow-ups and (2) to test the hypotheses that the optimal complexity level of each component is moderated by baseline deficits in self-regulation. The secondary aim will be to test target engagement for each level of complexity for each component, i.e., to test whether higher complexity of each technological components is associated with better rates of therapeutic skill use and acquisition and that improvements in skill use and acquisition are associated with improvements in outcomes. A final exploratory aim will be to quantify the component interaction effects, which may be partially additive (because components overlap and/or there is diminishing return), fully additive, or synergistic (in that component complexities may partially depend on each other).
Optimizing Digital Health Technology Interventions to Increase Skill Acquisition and Utilization
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Drexel University, Stratton Hall, Philadelphia, Pennsylvania, United States, 19104
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
For general information about clinical research, read Learn About Studies.
18 Years to 70 Years
ALL
No
Drexel University,
Adrienne S Juarascio, Ph.D., PRINCIPAL_INVESTIGATOR, Drexel University
2026-03