This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
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.
Control Systems Engineering to Address the Problem of Weight Loss Maintenance: A System Identification Experiment to Model Behavioral & Psychosocial Factors Measured by Ecological Momentary Assessment
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: The Miriam Hospital
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.