Optimizing a Sensor-Enabled mHealth Intervention for Adolescents with Suboptimal Asthma Control

项目摘要 哮喘影响美国9%的青少年，是青少年发病的主要原因。国家 哮喘指南强调哮喘自我管理行为对控制哮喘的重要性， 提高生活质量。青少年对哮喘自我管理行为的依从性不佳 通过不发达和高度可变的自我调节认知，情绪和行为的能力;以及 父母支持的规范性下降，而多种需求正在增加。每个青少年都会经历 不同的威胁，他们的自我调节能力在不同的时刻，需要个性化， 适应性自我调节支持，以增加日常自我管理行为并实现持续哮喘 控制智能手机是提高青少年依从性的最佳机制，然而，现有的 哮喘自我管理应用程序并不结合联合收割机， 策略和适应性干预技术，根据用户数据定制体验。我们的团队 最近开发的青少年响应性哮喘护理（ReACT; R56 HL 141394），一个技术生态系统， 包括一个智能手机应用程序，移动的传感器来评估药物剂量，一个SmartHub来实现实时 数据监听和基于云的干预交付算法。ReACT提供个性化和自适应 通过目标设定、反馈和障碍改善哮喘自我管理的自我调节支持 具有解决问题的能力。我们的试点工作结果表明，ReACT是可以接受的 并在我们假设的自我调节和问题机制中产生了干预后的变化- 解决技能。拟议的研究将根据我们从试点工作中吸取的经验教训优化ReACT， 更新国家哮喘指南。我们将进行一项不平衡（2：1）随机试验， 我们的多中心试验方案的可行性，确定ReACT是否对近端 假设驱动哮喘控制的机制，并探索ReACT对哮喘控制的影响， 哮喘相关的生活质量。哮喘控制不佳的13 - 17岁青少年（n = 120）将 随机分配至ReACT或按方案分层的mHealth对照条件，持续6个月。青少年 控制条件将收到一个应用程序，其中包括静态哮喘教育信息和记录表格 症状和坚持。对照条件旨在反映护理标准，优化招募， 并保持兴趣，同时对哮喘管理的影响最小。评估将 发生在基线、3个月和干预后（6个月）时间点。干预效果的机制将 通过自我报告（例如，自我调节）和目标（例如，药物依从性）评估。 我们将评估计划的未来临床试验结果（例如，哮喘控制和哮喘相关的生活质量）， 为今后的工作提供效应量估计。我们将有必要和足够的信息， 我们的多中心临床试验方案的可行性和本项目结束时计划的分析。

PROJECT SUMMARY Asthma affects 9% of adolescents in the United States and is a leading cause of youth morbidity. National asthma guidelines emphasize the importance of asthma self-management behaviors to control asthma and promote quality of life. Adolescents have suboptimal adherence to asthma self-management behaviors driven by an underdeveloped and highly variable capacity to self-regulate cognitions, emotions, and behaviors; and a normative decrease in parental support while multiple demands are increasing. Each adolescent experiences different threats to their ability to self-regulate at different moments in time, necessitating personalized and adaptive self-regulatory support to increase daily self-management behaviors and achieve sustained asthma control. Smartphones are an optimal mechanism for improving adolescent adherence, however, existing asthma self-management apps do not combine what is known about evidence-based behavior change strategies and adaptive intervention technologies that tailor the experience based on user data. Our team recently developed Responsive Asthma Care for Teens (ReACT; R56 HL141394), a technological ecosystem including a smartphone app, mobile sensors to assess medication dosing, a Smarthub to achieve real-time data listening, and cloud-based intervention delivery algorithms. ReACT provides personalized and adaptive self-regulatory support to improve asthma self-management via goal-setting, feedback, and barrier identification with problem-solving skills. Results of our pilot work demonstrated that ReACT was acceptable and produced post-intervention changes in our hypothesized mechanisms of self-regulation and problem- solving skills. The proposed study will optimize ReACT based on lessons learned from our pilot work and updated national asthma guidelines. We will conduct an unbalanced (2:1) randomized pilot trial to examine feasibility of our multisite trial protocol, determine if ReACT produces a clinically significant effect on proximal mechanisms hypothesized to drive asthma control, and explore the impact of ReACT on asthma control and asthma-related quality of life. Adolescents ages 13-17 with suboptimal asthma control (n=120) will be randomized to ReACT or a mHealth control condition stratified by regimen for 6-months. Adolescents in the control condition will receive an app that includes static asthma education information and a form for recording symptoms and adherence. The control condition is designed to mirror standard of care, optimize recruitment, and sustain interest while concurrently having a minimal impact on asthma management. Assessments will occur at baseline, 3-month, and post-intervention (6-month) time points. Mechanisms of intervention effect will be collected via both self-report (e.g., self-regulation) and objective (e.g., medication adherence) assessments. We will assess planned future clinical trial outcomes (e.g., asthma control and asthma-related quality of life) to provide effect size estimates for future work. We will have the necessary and sufficient information about the feasibility of our multisite clinical trial protocol and planned analyses at the end of this project.