Using Technology to Investigate Dietary and Physical Activity Lapses in a Behavioral Weight Loss Program
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Obesity
- Sponsor
- Williams College
- Enrollment
- 100
- Locations
- 1
- Primary Endpoint
- Physical activity lapse/intention-behavior gap
- Status
- Active, not recruiting
- Last Updated
- last year
Overview
Brief Summary
Approximately 70% of American adults have overweight/obesity, which increases risk of major medical issues and preventable death (Abdelaal et. al, 2017). Many individuals with overweight/obesity attempt to lose weight through behavioral strategies, e.g., adopting a reduced-calorie diet and/or increased physical activity. However, it is exceedingly difficult to consistently adhere to a reduced-calorie diet and high levels of physical activity; as such, most individuals attempting to lose weight via these methods experience repeated instances of non-adherence, i.e., dietary and physical activity lapses. These lapses are a core driver of weight loss failure, undermining individuals' ability to achieve weight control (Forman et al, 2017). As such, it is important to understand what predicts these lapses, which in turn allows for better lapse prevention. The current study proposes to measure these risk factors in an ecologically valid manner, i.e., in the moment they occur and in the context of individuals' everyday lives, using advanced technology. Specifically, the current study will use ecological momentary assessments (EMA; brief, repeated surveys delivered in one's natural environment, typically via a smartphone) and sensor technology (e.g., Fitbit and sensors on smartphone devices) to measure momentary risk factors of dietary and physical activity lapse, as well as the lapses themselves. Findings from this research project will lay the groundwork for a sophisticated just-in-time adaptive intervention (JITAI), a tailored, personalized intervention that targets momentary risk factors (e.g., cravings) via in-the-moment support, thereby reducing lapse occurrence and improving adherence to behavioral weight control prescriptions.
Investigators
Rebecca Crochiere
Assistant Professor of Psychology
Williams College
Eligibility Criteria
Inclusion Criteria
- •Current BMI = 27-50 kg/m2
- •Adult (aged 18-65)
- •Lives in the United States
- •Possession of a smartphone with a data plan that allows for app data collection
- •Ability to understand and provide informed consent
- •Proficiency in speaking, reading, and writing English
Exclusion Criteria
- •Presently involved in another weight loss program
- •Currently pregnant or plan to become pregnant within the study period
- •Have a medical condition or psychiatric symptoms that: may pose a risk to the participant during the program; cause a change in weight, appetite, or eating behavior; or limit ability to comply with the program
- •Endorse eating disordered behavior, including loss of control (LOC) eating, or the subjective experience that one cannot control how much food he or she consumes
- •Have experienced a recent (i.e., within the last 3 months) change in a weight-influencing medication
Outcomes
Primary Outcomes
Physical activity lapse/intention-behavior gap
Time Frame: up to 12 weeks
Physical activity lapse/intention-behavior gap will be measured using ecological momentary assessment (EMA; brief, smartphone-delivered surveys) and accelerometers. EMA surveys will be delivered in 2-week bursts at the beginning, middle, and end of treatment. There will be 6 EMA surveys delivered every 2-3 hours throughout the day. Each EMA survey will ask about the participant's intention to engage in moderate-to-vigorous physical activity (MVPA) in the next 2-3 hours and actual engagement in MVPA. Actual MVPA also will be measured through accelerometers (Fitbits). Thus, by measuring intention to engage in MVPA in the next 2-3 hours at Time 1 (e.g., EMA survey at 9:00am) and if the participant actually engaged in MVPA via accelerometer and EMA at Time 2 (2-3 hours later, e.g., at 12:00pm), we can detect a physical activity intention-behavior gap or physical activity lapse.
Secondary Outcomes
- Dietary lapse(up to 12 weeks)