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: 10022516
• 负责人: Joseph Arnold Skelton
• 金额: $ 58.71万
• 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 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10022516
• 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; Disadvantaged; 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; Predictive Factor; Prevention; Preventive; Primary Health Care; Program Effectiveness; Reporting; Reproducibility; Research; Research Personnel; Resources; Risk; Site; Structure; System; Techniques; Testing; Time; Treatment outcome; War; Weight; Weight maintenance regimen; advanced analytics; base; behavior change; cost outcomes; design; evidence base; high risk; improved; improved outcome; innovation; 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.

摘要 肥胖症的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， 这些方案都是大力提倡的。然而，这些计划的有效性受到自然减员的限制， 辍学率在27- 73%之间，限制了儿童的健康福利，并且没有有效地利用已经稀缺的资源。 资源这一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，让临床医生和研究人员很少在其中影响这一现象。除了更好的 了解自然减员的驱动因素，能够预测或预测辍学率， 治疗方法和结果，并修改治疗方法，以最好地满足家庭的需要。我们有 开发了一个模型，该模型将与儿童体重管理相关的损耗变量分离出来， 预测参与者退出的可能性。我们有机会扩大和进一步完善这一模式 通过收集关键数据元素和增加研究规模。因此，我们建议扩大 和完善的方法来研究从儿科体重管理的损耗，利用的力量， 增加参与者数量，获得一致的数据元素和先进的分析技术。的 这个项目的总体目标是提高我们现有的人员流失预测模型的准确性和能力。 开发通过其安装在额外的体重管理计划，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，以减少病人辍学。 在目标1中，我们将通过 基于我们的依从性概念模型，持续获取关键患者、家庭和治疗数据， 来自三个不同的减肥网站在目标2中，外部效度将通过 在第四个儿科体重管理中安装OFS。目标3将是一项探索性研究， OFS在儿科体重管理项目中减少高风险患者的消耗的可行性和实用性 患者和家属。更好地了解患者、家庭和疾病特异性因素， 可以利用从儿科体重管理中退出来防止损耗。通过研究目的 建议，OFS将被细化到精度，校准和效率的水平，成为任何有价值的工具， 体重管理计划。通过确定最相关的因素驱动磨损跨体重 管理地点，将确定新的治疗和预防途径。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。