Identifying Effective Technological-based Augmentations to Enhance Outcomes From Self-help Cognitive Behavior Therapy for Binge Eating

The purpose of this study is to test the feasibility, acceptability and efficacy of two technology-based intervention systems (including an Advanced Digital Data Sharing (ADDS) with Coaches or a smartphone-based just-in-time, adaptive interventions (JITAIs) system) for improving treatment adherence, skills utilization and binge eating when used in conjunction with a self-help cognitive behavior therapy \[CBT\] delivered via a smartphone application \[app\]). The study is being conducted to test a novel approach to providing evidence-based treatment for binge eating without clinician support in a routine clinical setting.

Self-help cognitive behavior therapies (CBTs) for binge eating are maximally effective when paired with periodic contact with expert clinicians. Clinicians likely improve outcomes because they are trained to utilize specific behavior change techniques for facilitating treatment adherence and skills utilization during self-help CBT programs. Given the limited availability of expert clinicians, it is critical to understand how to enhance outcomes from self-help CBTs without clinician involvement. Technological innovations such as Advanced Digital Data Sharing with Coaches and Just-in-time adaptive interventions (JITAIs) can potentially emulate some of the behavior change techniques used by expert clinicians and improve treatment targets.

The current study will use a 2 x 2 full factorial design in which 76 individuals with bulimia nervosa (BN) or binge eating disorders (BED) are assigned to one of four treatment conditions, i.e., representing each permutation of Advanced DDS with Coaches (Advanced DDS with Coaches ON vs. Advanced DDS with Coaches OFF) and JITAIs (JITAIs ON vs. JITAIs OFF) as an augmentation to self-help CBT program. Self-help CBT will deliver an evidence-based program based on Dr. Chris Fairburn's Overcoming Binge Eating self-help book via a smartphone app without clinician involvement. This app will constitute 12 treatment modules and an electronic self-monitoring form to record eating and eating disorder behaviors for use over 12 weeks without clinician involvement. The primary aims of the study will be to (1) Test target engagement, i.e., that each factor including Advanced DDS with Coach and JITAIs produces greater improvements in treatment adherence and skills utilization, (2) Test the feasibility and acceptability of two intervention factors as adjuncts to self-guided CBT program for binge eating; (3) Test the initial efficacy, i.e., that each factor including Advanced DDS with Coach and JITAIs will produce greater improvements in binge eating frequency at post-treatment, and 3 months follow-up; and (4) Test target validation, i.e., that improvements in treatment adherence and skills utilization will be associated with reductions in binge eating. The exploratory aim will be to quantify the intervention factors' interaction effects, which may be partially additive (because intervention factors overlap and/or there is diminishing return), fully additive, or synergistic (in that intervention factors may partially depend on each other).

Eligibility Criteria:
Inclusion Criteria:

1. Have experienced 12 or more loss of control episodes within the previous 3 months
2. Have a BMI at or above 18.5
3. Are located in the US and willing/able to participate in treatment and assessments
4. Are able to give consent

Exclusion Criteria:

1. Are unable to fluently speak, write and read English
2. Have a BMI below 18.5
3. Are already receiving treatment for an eating disorder
4. Require immediate treatment for medical complications as a result of eating disorder symptoms
5. Have a mental handicap, or are experiencing other severe psychopathology that would limit the participants' ability to comply with the demands of the current study (e.g. severe depression with suicidal intent, active psychotic disorder, severe substance use)
6. Are pregnant or are planning to become pregnant