Overview
This project capitalizes on principles of control systems engineering to build a dynamical model that predicts weight change during weight loss maintenance using behavioral, psychosocial, and environmental indicators evaluated in a system identification experiment. A 6-month behavioral obesity treatment will be administered to produce weight loss. Participants losing at least 3% of initial body weight will be followed for an additional 12 months via daily smartphone surveys that incorporates passive sensing to objectively monitor key behaviors. Survey data pertaining to behavioral, psychosocial, and environmental indicators will be used to develop a controller algorithm that can predict when an individual is entering a heightened period of risk for regain and why risk is elevated. Interventions targeting key risk indicators will be randomly administered during the system ID experiment. Survey and passive sensing data documenting the effects of the interventions will likewise drive development of the controller algorithm, allowing it to determine which interventions are most likely to counter risk of regain.
Eligibility
Inclusion Criteria:
- English language fluent and literate at the 6th grade level
- Body mass index (BMI) between 25 and 50 kg/m-squared
- Able to walk 2 city blocks without stopping
- Owns a smartphone
Exclusion Criteria:
- Report of a heart condition, chest pain during periods of activity or rest, or loss of consciousness in the 12 months prior to enrolling.
- Currently participating in another weight loss program
- Currently taking weight loss medication
- Has lost ≥5% of body weight in the 6 months prior to enrolling
- Has been pregnant within the 6 months prior to enrolling
- Plans to become pregnant within 18 months of enrolling
- Any medical condition that would affect the safety of participating in unsupervised physical activity
- Any condition that would result in inability to follow the study protocol, including terminal illness and untreated major psychiatric illness