Clinical trial NCT05693896: Treating Binge Eating and Obesity Digitally in Black Women
Official title: Treating Binge Eating and Obesity Digitally in Black Women: A Feasibility Study
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Binge Eating
Binge-Eating Disorder
Weight Gain Prevention
Obesity
Lead sponsor: University of North Carolina, Chapel Hill
Sponsor class: OTHER
Collaborators: name: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
First posted: 2023-01-23
Enrollment: 60
Sex: FEMALE
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: SCREENING

Brief summary: More than 30% of Black women with obesity binge eat. Binge eating may increase the risk for the development of metabolic syndrome and binge-eating-disorder (BED), which is associated with severe obesity. Though several effective treatments for binge eating exist, Black women have not fared well. Not only has their inclusion in treatment trials been limited, but when participating, they are more likely to drop out, and/or lose less weight, compared to their White counterparts. Furthermore, treatment for binge eating is often not available in primary care and community-based settings places where Black women are more likely to receive treatment for their eating and weight-related concerns. Currently, there is scant intervention research to treat binge eating in Black women. With the highest rates of obesity (57%) nationally, Black women are in need of culturally-relevant treatments for binge eating and weight gain prevention. Given the established relationship between frequent binge eating and subsequent weight gain, addressing binge eating among Black women with obesity is imperative.

Detailed description: Aim 1. Modify and adapt a validated program to be a culturally-relevant digital health tool for binge eating and weight management for Black women (BMI \> 30 kg/m\^2) who binge eat.

Aim 1a. Identify the barriers and facilitators to detecting and treating binge eating in Black women with obesity, and identify strategies for optimizing digital health tools to engage and retain this population.

Aim 1b. Conduct usability testing with a group of stakeholders to guide content and design refinements; refine tool.

Aim 2. In a randomized clinical trial, examine the feasibility and preliminary efficacy of the digital health appetite awareness + behavioral weight program in primary care.

Eligibility criteria: Inclusion Criteria:

* Over 18 years of age,
* BMI ≥ 30 kg/m\^2,
* have and regularly use a Bluetooth-enabled smartphone,
* report at least one binge eating episode weekly,
* work or live within 30 miles of Kannapolis, NC,
* complete the screening questionnaire

Exclusion Criteria:

* currently pregnant,
* in substance abuse treatment,
* involved in another weight reduction program,
* have a history of anorexia,
* are purging,
* currently in treatment for eating difficulties,
* are concurrent intravenous drug users
* consume \>4 alcoholic beverages/day

Primary outcomes:
measure: Feasibility (Recruitment): Total Number of Eligible Adults Enrolled in the Study
timeFrame: 3 month
measure: Retention: Percentage of Participants Retained in the Study
timeFrame: 6 months
measure: Attendance: Percentage of Intervention Sessions Attended
timeFrame: 6 months
Secondary outcomes:
measure: Change from Baseline to Month 3 in weight regain
timeFrame: Baseline, 3 months
measure: Change from Baseline to Month 6 in weight regain
timeFrame: Baseline, 6 months
measure: Change in number of Binge Eating Episodes from Baseline to Month 3
timeFrame: Baseline, 3 months
measure: Change in number of Binge Eating Episodes from Baseline to Month 6
timeFrame: Baseline, 6 months
Other outcomes:
Locations:
city: Chapel Hill
country: United States
facility: UNC-Chapel Hill
state: North Carolina
Study officials:
affiliation: University of North Carolina, Chapel Hill
name: Rachel Goode, PhD,MPH
role: PRINCIPAL_INVESTIGATOR
References: