Eating disorders (EDs) are a critical concern on college campuses. Moreover, since the COVID-19 pandemic, ED prevalence has increased by 62% in university women and 140% in university men. Resources are inadequate to meet demand, leading to delays in students' access to treatment. Untreated (or poorly treated) EDs result in greater healthcare utilization and costs to students, as well as lower academic achievement and increased psychiatric disability and mortality, suggesting a critical need for quality ED treatment on university campuses and to rethink treatment delivery. One way to address this gap in care delivery is to improve treatment accessibility and scalability, such as dissemination via mobile apps. Guided self-help Cognitive Behavior Therapy (CBT-gsh) is a cost-effective option that can be delivered by non-traditional service providers, such as nurses and physicians. Our scientific premise is that the mHealth CBT-gsh app, Building Healthy Eating and Self-Esteem Together for University Students (BEST-U), will lead to reductions in binge eating (primary outcome) through reductions in dietary restraint and weight/shape concerns (target mechanisms). Prior to implementing BEST-U at other universities, we need to test the intervention in a real-world setting with the end goal of disseminating at scale. Our objectives are to: 1) conduct an effectiveness test of BEST-U compared to a similar dose of present-centered therapy (PCT) in students with non-low weight binge-spectrum EDs and 2) test target mechanisms that lead to changes in binge eating. To accomplish our objectives, we will test the following specific aims: 1) conduct an RCT of BEST-U (N=37) compared to a similar dose of PCT (N=37) in students with non-low weight binge-spectrum EDs; 2) test target mechanisms that lead to changes in binge eating and other ED symptoms; and 3) characterize barriers and facilitators to implementation across two campuses. Our exploratory aim will test food reinforcement and food-choice impulsivity as potential target mechanisms or response moderators of rapid response in binge eating. Given that few studies have identified underlying mechanisms that explain how CBT-gsh works and for whom, this study may lead to improved ability to tailor or modify existing CBT-gsh or lead to novel intervention development for students who are unlikely to respond rapidly (or at all) to first line CBT interventions for EDs.

Eating disorders (EDs) are a critical concern on college campuses and the COVID-19 pandemic has led to increased ED prevalence of 62% in university women and 140% in university men. Resources are inadequate to meet this rising demand as student counseling centers are often understaffed and only 20-21.9% of students reported receiving care for their eating problems, due to financial, logistical, and psychological barriers to accessing treatment. Unfortunately, even when students receive treatment, only a fraction of providers use evidence-based strategies. Untreated (or poorly treated) EDs result in greater healthcare utilization and costs to students, as well as lower academic achievement and increased psychiatric disability and mortality suggesting a critical need for quality ED treatment on university campuses and for rethinking modes of treatment delivery.

One way to address this gap in care delivery is to improve accessibility and scalability of treatment options, such as delivering care via mobile apps. Guided self-help Cognitive-Behavior Therapy (CBT-gsh) is a cost-effective option that can be delivered by a range of non-traditional service providers, such as nurses and physicians. Existing mobile health (mHealth) CBT-gsh programs do not include critical components of CBT such as food and symptom monitoring and reinstatement of regular eating patterns and have limitations that yield low engagement. Our team has developed an easy to use mHealth CBT-gsh program incorporating evidence-based for college students named Building Healthy Eating and Self-Esteem Together for University Students (BEST-U)that includes modules deployed through a smart phone app paired with 20-30 minute coaching sessions. BEST-U incorporates a range of evidence-based skills, and the electronic format allows coaches immediate and easy access to participant reports. BEST-U provides a comprehensive all-in-one assessment and intervention package, is easy-to-implement, brief, and has been tested across genders and in diverse ages and ethnic groups. BEST-U, therefore, has the potential to deliver effective, time-limited, interventions applicable to all young adults in routine student healthcare settings.

Beyond knowing that CBT-gsh interventions are effective generally, it is critical to know how such interventions work and for whom. Without this data, it will remain difficult to: 1) determine what components to add to improve efficacy and 2) identify which clients will respond and which should be referred to alternative care. Thus, novel and scalable treatments to test underlying mechanisms are urgently needed in this population.

Our hypothesis is that the mHealth CBT-gsh app, BEST-U, will lead to reductions in binge eating (primary outcome) through reductions in dietary restraint, weight/shape concerns (targets), and negative emotions. Our pilot data showed strong support for our premise, specifically the need for brief, targeted mHealth interventions in students and the ability of the program to significantly reduce binge eating and impairment and increase wellbeing, with high user acceptability and low drop-out rates. Importantly, these treatment gains were maintained at 3- and 6-month follow-up. However, prior to implementing BEST-U at other universities, we need to test the intervention in a real-world setting with the end goal of disseminating at scale. Thus, we will: 1) conduct an effectiveness test of BEST-U (N=37) compared to a similar dose of present-centered therapy (PCT; N=37) in students with non-low weight binge-spectrum EDs; 2) test target mechanisms that lead to changes in binge eating; and 3) characterize barriers and facilitators to implementing such an intervention across two college campuses.

In addition to our core hypotheses, our exploratory aim is to test food reinforcement and food-choice impulsivity as target mechanisms or response moderators of rapid response in binge eating. Rapid change in binge eating during the first four weeks of CBT-based ED interventions (i.e., "rapid response") is associated with improved end-of-treatment outcomes and aligns temporally with the introduction of "regular eating," a key element for reducing dietary restraint and, thereby, risk for binge eating. However, it is unknown why some individuals respond rapidly to normalization in eating patterns by reducing or eliminating binge eating and why binge eating persists for others. We posit that changes in the relative reinforcement value of food will predict, and food-choice impulsivity will moderate, these differential responses.

Inclusion Criteria:

• Age ≥ 18 years.
• Student enrolled at KU.
• Bulimia nervosa (BN) or binge-eating disorder (BED) (or sub-threshold BN or BED).
• Access to a smartphone.
• No uncorrected vision problems that would interfere with ability to participate in the study.
• Students taking psychotropic medications must be on a stable therapeutic dose for four weeks prior to study enrollment.
• Able to read and speak fluent English.

Exclusion Criteria:

• Presence of current moderate/severe suicidal ideation with active intent.
• Significant psychopathology that could interfere with treatment (e.g., current substance-use disorder or psychosis).
• Medical conditions or medications that could interfere with treatment (e.g., Type 1 diabetes mellitus, cancer, current pregnancy or nursing, taking corticosteroids, etc.).
• Lab abnormalities indicating medical instability (e.g., low heart rate, electrolyte disturbance, acute medical complications of malnutrition) or another medical problem that would prevent outpatient care as determined through physical health assessment by the student's local clinician.
• Already receiving therapy for an ED.
• Positive screen for anorexia nervosa (AN), atypical AN (AAN), and/or low body weight (i.e., BMI < 19.5) or avoidant and restrictive food intake disorder (ARFID).

Per NIMH requirements, we will share data from the proposed project using the NDA. Data from this project will be preserved to enable sharing through the NDA to validate and replicate the research findings described in our Specific Aims. Data sharing will also enable independent investigators to conduct secondary analyses. Participants will be apprised of how their data will be shared during the consent process. We are committed to sharing research data in a way that is consistent with applicable law and policy, agency mission, and USA national, homeland, and economic security. De-identified data collected from this study will be made publicly available on the NIMH Data Archive. We will restrict any data that may reveal subjects' identities (e.g., geographical location). We view data sharing as crucial for advancing science in eating disorder (ED) research, particularly given that there are few treatment studies of CBT-gsh in young adults.

All data will be deposited to NDA starting 12 months after the award begins and will be deposited every six months thereafter following the usual NDA data submission dates.

The research community will have access to data when the award ends. As required by NDA, studies will also be created that contain the data used for every publication. Those studies will be shared when the pre-print is available. NDA studies have digital object identifiers (DOI) to aid in findability. We will include that DOI in relevant publications. NDA will make decisions about how long to preserve the data, but that data archive has not deleted any deposited data up to now.