War of Attrition: Predicting Dropout from Pediatric Weight Management

消耗战：预测儿童体重管理中的退出

• 批准号: 10647817
• 负责人: Joseph Arnold Skelton
• 金额: $ 57.53万
• 依托单位: WAKE FOREST UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-23 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10647817
• 关键词: Address; Adherence; Adult; Advocate; Area; Automobile Driving; Behavior; Body Weight Changes; Calibration; Child; Child Health; Childhood; Clinic; Clinical; Collection; Communities; Data; Data Collection; Data Element; Discipline; Disease; Dropout; Drops; Effectiveness; Exposure to; Family; Feasibility Studies; Goals; Health Benefit; High Prevalence; Knowledge; Literature; Measures; Mentored Patient-Oriented Research Career Development Award; Modeling; Morbid Obesity; Obesity; Obesity Epidemic; Outcome; Parents; Participant; Patient Dropouts; Patients; Pediatric Hospitals; Predictive Factor; Prevention; Primary Care; Program Effectiveness; Reporting; Reproducibility; Research; Research Personnel; Resources; Risk; Site; Stress; Structure; System; Techniques; Testing; Time; Treatment outcome; United States Preventative Services Task Force; War; Weight; Weight maintenance regimen; advanced analytics; behavior change; cost outcomes; design; disadvantaged background; evidence base; high risk; improved; improved outcome; innovation; model building; model design; multidisciplinary; obesity in children; obesity treatment; outcome forecast; predictive modeling; prevent; programs; tool; uptake

Abstract The obesity epidemic is one of the foremost threats to the health of children and adults in the U.S today. Multidisciplinary pediatric weight management programs have been deemed effective, with increased access to these programs strongly advocated. However, the effectiveness of these programs is limited by attrition, with dropout ranging from 27-73%, limiting health benefits to children and inefficiently utilizing already scarce resources. Most research in this area is ad hoc, retrospective, observational, and inconsistent in the variables measured, leaving clinicians and researchers little in which to impact this phenomenon. In addition to better understanding the drivers of attrition, being able to predict or forecast dropout holds great potential to improve adherence and outcomes, and modify treatment approaches to best serve the needs of families. We have developed a model that isolates variables associated with attrition from pediatric weight management, with the potential to forecast participant dropout. We have the opportunity to expand and further refine this model through the collection of key data elements and increased study size. Therefore, we are proposing an expanded and refined approach to the study of attrition from pediatric weight management, utilizing the strength of increased participant numbers, acquisition of consistent data elements, and advanced analytic techniques. The overall goal of this project is to increase the accuracy and power of an attrition prediction model we have developed through its installation in additional weight management programs, then demonstrating its internal, external, and temporal validity. Finally, we will test this powerful tool as a means to decrease patient dropout. In Aim 1, we will increase the power and precision of the Outcomes Forecasting System (OFS) through the consistent acquisition of key patient, family, and treatment data, based on our conceptual model of adherence, from three different weight management sites. In Aim 2, external validity will be established through the installation of the OFS at a fourth pediatric weight management. Aim 3 will be an exploratory study of the feasibility and utility of the OFS in pediatric weight management programs to reduce attrition in high-risk patients and families. A greater understanding of patient, family, and disease-specific factors that predict dropout from pediatric weight management can be utilized to prevent attrition. Through the research aims proposed, the OFS will be refined to a level of precision, calibration, and efficiency to be a valuable tool to any weight management program. By identifying the most pertinent factors driving attrition across weight management sites, new avenues for treatment and prevention will be identified. This project will result in a valuable tool, available for dissemination across a diverse array of clinical programs to improve adherence, decrease costs, and improve outcomes.

抽象的 肥胖流行是当今美国儿童和成人健康的最大威胁之一。 多学科儿科体重管理计划被认为是有效的，并且获得更多机会 对这些方案大力提倡。然而，这些计划的有效性受到人员流失的限制， 辍学率从 27% 到 73% 不等，限制了儿童的健康福利，并且对本已稀缺的资源的利用效率低下 资源。该领域的大多数研究都是临时的、回顾性的、观察性的，并且变量不一致 测量，临床医生和研究人员几乎没有办法影响这一现象。除了更好 了解流失的驱动因素，能够预测或预测辍学具有巨大的改进潜力 坚持和结果，并修改治疗方法以最好地满足家庭的需求。我们有 开发了一个模型，从儿科体重管理中分离出与消耗相关的变量，其中 预测参与者退出的潜力。我们有机会扩展和进一步完善这个模型 通过收集关键数据元素和扩大研究规模。因此，我们建议扩大 并利用儿科体重管理的力量改进研究消耗的方法 增加参与者数量、获取一致的数据元素以及先进的分析技术。这 该项目的总体目标是提高我们现有的损耗预测模型的准确性和功效 通过将其安装在额外的体重管理程序中来开发，然后展示其内部， 外部和时间有效性。最后，我们将测试这个强大的工具作为减少患者流失的一种手段。 在目标 1 中，我们将通过以下方式提高结果预测系统 (OFS) 的能力和精度： 基于我们的依从性概念模型，一致获取关键患者、家庭和治疗数据， 来自三个不同的体重管理网站。在目标 2 中，外部效度将通过 在第四家儿科体重管理中心安装 OFS。目标 3 将是一项探索性研究 OFS 在儿科体重管理计划中减少高危人群流失的可行性和实用性 患者和家属。更好地了解患者、家庭和疾病特定的预测因素 退出儿科体重管理可用于防止人员流失。通过研究目标 根据提议，OFS 将在精度、校准和效率方面得到改进，成为任何人都可以使用的有价值的工具。 体重管理计划。通过确定导致体重流失的最相关因素 将确定管理地点、治疗和预防的新途径。该项目将导致 有价值的工具，可用于在各种临床项目中传播以提高依从性， 降低成本，改善结果。

项目成果

Stay in treatment: Predicting dropout from pediatric weight management study protocol.

• DOI: 10.1016/j.conctc.2021.100799
• 发表时间: 2021-06
• 期刊: Contemporary clinical trials communications
• 影响因子: 1.5
• 作者: Berry DC;Rhodes ET;Hampl S;Young CB;Cohen G;Eneli I;Fleischman A;Ip E;Sweeney B;Houle TT;Skelton J
• 通讯作者: Skelton J

Time Equivalency and Child Adiposity: The Biggest Bang for the Buck.

• DOI: 10.1542/peds.2020-042168
• 发表时间: 2021-04
• 期刊: Pediatrics
• 影响因子: 8
• 作者: Cardel MI;Newsome FA;Skelton JA
• 通讯作者: Skelton JA