Physical Activity Clinical Trial
Official title:
Control Systems Engineering for Optimizing a Prenatal Weight Gain Intervention
The purpose is to establish feasibility of delivering an individually-tailored, behavioral intervention to manage gestational weight gain [GWG] that adapts to the unique needs and challenges of overweight/obese pregnant women [OW/OBPW] and will utilize control systems engineering to optimize this intervention; in other words, make this intervention manage GWG in OW/OBPW as effectively and efficiently as possible.
The research proposed here will establish the dosage of components needed to impact GWG and develop an efficient (optimized) intervention to effectively manage GWG in OW/OBPW before a randomized controlled trial (RCT) can be implemented. The aims of the proposed research are: to establish feasibility of delivering an individually-tailored behavioral intervention for managing GWG in OW/OBPW. Two studies will be conducted to establish feasibility. Study 1 will examine viability of delivering dosages/sequencing of components (education, goal-setting, self-monitoring, HE/PA), GWG/HE/PA self-monitoring using e-health technology mechanisms, and data collection by delivering varied dosages to OW/OBPW over a brief, 4-week period followed by focus groups to evaluate user acceptability. The investigators will then make necessary revisions to the intervention. Study 2 will pilot test intervention delivery with decision rules for when/how to adapt dosages for an individual and randomization/retention/data collection procedures with treatment and control groups in a new cohort of OW/OBPW. Also, the investigators aim to use feasibility data collected from Aim 1 and control systems engineering to build a model that characterizes the effects of energy balance and planned/self-regulatory behaviors on GWG over time and use this model to develop an optimized intervention. The investigators will identify a dynamical model from feasibility data collected in Aim 1 that considers how changes in GWG responds to changes in energy intake, PA, and planned/self-regulatory behaviors. Model predictive control (a decision-making method from control systems engineering) will inform how the dosage adaptations are decided. The investigators will then identify a customized intervention plan for each woman based on her levels of energy intake, PA, planned/self-regulatory behaviors and the extent to which she is meeting GWG goals over pregnancy. This will lead to final program modifications and result in an individually-tailored, optimized intervention. The investigators will test the efficacy of this optimized intervention for managing GWG in OW/OBPW in a future RCT. This innovative research will develop an individually-tailored, optimized intervention that effectively and efficiently manages GWG in OW/OBPW and that will eventually be available to all pregnant women (via e-health technology) to improve the health of mothers and infants and impact the etiology of obesity and cardiovascular disease at a critical time in the life cycle. ;
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