Efficacy of a Novel Digital Platform to Scale-Up a Personalized Prenatal Weight Gain Intervention Using Control Systems Methodology

新型数字平台使用控制系统方法扩大个性化产前体重增加干预的功效

• 批准号: 10562400
• 负责人: Danielle Symons Downs
• 金额: $ 68.53万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10562400
• 关键词: Address; Architecture; Behavior; Birth Weight; Body mass index; COVID-19 pandemic; Categories; Cognitive; Control Groups; Data; Eating; Eating Behavior; Education; Effectiveness; Energy Intake; Future; Gestational Age; Goals; Grant; Guidelines; Health; Health Benefit; Healthy Eating; Individual; Infant; Infant Health; Intake; Intervention; Low Birth Weight Infant; Maternal Health; Measurement; Measures; Methodology; Modeling; Modification; Monitor; Mothers; Obesity; Outcome; Outcome Measure; Outcome Study; Overweight; Persons; Phase; Physical activity; Pregnancy; Pregnant Women; Prenatal care; Qualifying; Randomized; Recommendation; Remote session; Research; Risk; Risk Reduction; Sleep; System; Time; Translational Research; Weight Gain; Woman; attentional control; design; digital platform; dosage; efficacy evaluation; efficacy testing; efficacy trial; energy balance; feasibility trial; gestational weight gain; health care delivery; high body mass index; high risk; infant outcome; innovation; mHealth; novel; offspring; perinatal outcomes; post intervention; prenatal; prepregnancy; primary outcome; randomized trial; remote delivery; restraint; scale up; secondary outcome; simulation; social; social cognitive theory; theories; tool; web interface

PROJECT SUMMARY Pregnant women with overweight/obesity (PW-OW/OB) and high gestational weight gain (GWG) are at increased risk for adverse maternal-infant outcomes. Given this high risk and the rapidly changing landscape of healthcare delivery due to the COVID-19 pandemic, there is a timely need for automated, scalable approaches relying on remote delivery to regulate GWG. Our team addressed this need and developed the Healthy Mom Zone (HMZ) intervention with adapted dosages to regulate GWG. Adaptations give less treatment (e.g., education) to women who can self-regulate GWG within recommendations and more treatment (physical activity/energy intake activities) to women who need more support to regulate GWG. Theory-based components were designed with a multiphase, translational science framework and control systems methodology with the long-term goal to scale- up future use by prenatal clinicians. With R01HL119245, we randomized PW-OW/OB to intervention and control groups and examined feasibility and initial impact of HMZ on GWG. A control system driven by decision rules and a woman’s observed GWG informed when to adapt dosages (GWG within goals, dosage was maintained; GWG above goals, dosage was adapted). Trial feasibility markers showed high compliance, low subject burden and attrition; compliance was better with remove vs. in-person delivery. The HMZ group had 21% lower mean GWG and were more likely to have GWG within goals than controls. Exploratory analyses also showed promise for HMZ to impact secondary maternal-infant outcomes. Given these initial findings, we made refinements to increase efficacy and scalability (e.g., added sleep/eating behavior content, modified all components for remote delivery). We replaced the initial control system with a new automated, model-based predictive control system that forecasts a woman’s future GWG under different possible values of activity/intake behaviors and determinants. We found that it made more efficient decisions to adapt dosages and regulated GWG better than the initial system. With a Penn State seed grant, we built an architecture for a novel digital platform with a web interface that automates the linkage of subject data to the new control system, computes optimized dosage changes across multiple maternal variables, and produces a host of behavior strategies to regulate GWG. The goal of the proposed research is to examine efficacy of the enhanced HMZ 2.0 intervention with new control system/digital platform to regulate GWG and impact maternal-infant outcomes while collecting implementation data to inform future scalability. N=144 PW-OW/OB will be randomized to HMZ 2.0 intervention or attention control groups from ~8-36 weeks gestation. Aim 1 will examine efficacy of HMZ 2.0 on GWG (primary outcome) and activity/intake behaviors and social cognitive determinants between intervention and control groups. Aim 2 will measure pre- to post-intervention differences in secondary maternal sleep/eating behaviors and infant birth weight. Aim 3 will examine impact of implementation markers on HMZ 2.0 efficacy on study outcomes to inform future scalability. Impact of this novel research is an optimized and highly scalable intervention to regulate GWG.

项目摘要 超重/肥胖（PW-OW/OB）和高妊娠体重增加（GWG）的孕妇正在增加 不利的产妇结果的风险。鉴于这种高风险和医疗保健的迅速变化的格局 由于19年的大流行而导致的交付，有及时需要自动化的可扩展方法 远程交付以调节GWG。我们的团队满足了这一需求，并发展了健康的妈妈区（HMZ） 采用适应剂量调节GWG的干预措施。适应对妇女的治疗较少（例如，教育） 谁可以在建议和更多治疗中自我调节（体育锻炼/能量摄入） 活动）向需要更多支持来规范GWG的妇女。基于理论的组件是设计的 多相，转化科学框架和控制系统方法论具有长期目标的规模 - 提高产前临床医生的未来使用。使用R01HL119245，我们将PW-OW/OB随机进行干预和控制 组并检查了HMZ对GWG的可行性和最初影响。由决策规则驱动的控制系统 一名妇女观察到的GWG通知何时适应剂量（在目标范围内，保持了剂量； GWG高于目标，剂量得到了调整）。试验可行性标记显示出很高的依从性，Burnen的受试者低。 和流失;合规性更好地删除与面对面交付更好。 HMZ组的平均值低21％ GWG和更有可能将GWG在目标范围内的可能性比对照组更有可能。探索性分析也显示出希望 HMZ影响继发性产妇的结果。鉴于这些初步发现，我们对 提高效率和可扩展性（例如，增加了睡眠/饮食行为内容，修改了遥控器的所有组件 送货）。我们用新的自动化，基于模型的预测控制系统替换了初始控制系统 在不同可能的活动/摄入行为值的价值和 决定级。我们发现，它做出了更有效的决定，以适应剂量和调节GWG 初始系统。借助宾夕法尼亚州种子赠款，我们用网络建造了一个新颖的数字平台的建筑 自动化主题数据与新控制系统的接口，计算优化的剂量 多个母校变量的变化，并产生许多行为策略来调节GWG。 拟议的研究的目标是检查增强的HMZ 2.0干预的有效性 系统/数字平台，以调节GWG和影响产生的结果，同时收集实施 数据以告知未来的可伸缩性。 n = 144 PW-OW/OB将被随机分为HMZ 2.0干预或注意力 对照组约8-36周妊娠。 AIM 1将检查HMZ 2.0对GWG的效率（主要结果） 以及干预组和对照组之间的活动/摄入行为和社会认知决定者。目标2 将测量次生母亲睡眠/饮食行为和婴儿出生的干预前差异 重量。 AIM 3将检查实施标记对HMZ 2.0效率对研究结果的影响以告知 未来的可伸缩性。这项新研究的影响是一种优化且高度可扩展的干预措施，以调节GWG。