Operationalizing Behavioral Theory for mHealth: Dynamics, Context, and Personalization

摘要 本行政副刊对家长U01奖的具体目标进行了扩展，建议 协调集中纵向健康中涉及的微随机试验(MRT)的数据 行为网络(ILHBN)，研究数字试验和即时干预的参与度。这位家长 项目(HeartSteps II，U01CA229445)是ILHBN的一部分，旨在合作研究 使用密集纵向数据(ILD)收集对个人日常生活中动态健康行为的影响 和新颖的分析方法。该网络包括7个U01项目和1个U24研究协调 中心(RCC)。数字干预的有效性在很大程度上取决于参与者对 数字行为改变干预(DBCI)。要实现行为改变，参与者需要参与 使用DBCI应用程序的界面组件(例如，应用程序页面查看、登录)以及行为更改 在DBCI中使用的技术(例如，活动计划、体重记录、日记条目)。有非常多的 通过在全球范围内共享和分析ILD来推进理论驱动的行为改变干预措施 ILHBN网络干预。最大限度地利用这些数据来推动移动健康科学的发展 并支持对开发和测试新的分析方法感兴趣的研究人员 复杂的，真实世界的行为数据，我们提出了一个行政补充，以加强工作 具有以下新的具体目标的家长赠款：1)：管理数据、辅助数据和元数据并与其共享 ILHBN的成员，以及2)联合IT干预的业务运作和模范参与。这个项目 会不会是第一个及时调查参与度变化的模式、相关性和原因的人， 随着时间的推移，移动干预。它还将支持对ILHBN旗舰项目贡献的数据的管理 数据库。这些数据将支持模型的开发，这些模型有可能导致对一系列 动态行为流程，包括总体上与移动技术的互动。最后，这一点 补充资料将支持开发综合技术援助系统中参与的动态计算模型 运行它们的工具。这些活动共同推动了ILD领域以及与ILD和JITAI的接触 基本上是这样的。

Abstract This Administrative Supplement expands on the Specific Aims of the parent U01 award by proposing to harmonize data across the Micro-Randomized Trials (MRTs) involved in the Intensive Longitudinal Health Behaviors Network (ILHBN) to study engagement in digital trials and just-in-time interventions. This parent project (HeartSteps II, U01CA229445) is part of the ILHBN, established to collaboratively study factors that influence dynamic health behaviors in individuals’ daily lives using intensive longitudinal data (ILD) collection and novel analytic methods. The network includes seven U01 projects and one U24 Research Coordinating Center (RCC). The effectiveness of digital interventions is heavily reliant upon the participant’s engagement with the digital behavior change intervention (DBCI). To achieve behavior change, the participant needs to engage with the interface components of the DBCI app (e.g., app page views, logins), as well as the behavior change techniques (e.g., activity planning, weight-logging, diary entries) employed in the DBCI. There are tremendous opportunities to advance theory-driven behavior change interventions by sharing and analyzing ILD across the ILHBN network interventions. To maximize the utility of these data to advance the science of mobile health engagement and to support researchers interested in developing and testing new methods for analyzing complex, real-world behavioral data, we propose an Administrative Supplement that augments the work of the parent grant with the following new specific aims; 1): Curate and share data, paradata, and metadata with members of the ILHBN, and 2) Operationalize and Model Engagement in JIT interventions. This project will the first to investigate the patterns and correlates and causes of changes in engagement in Just-In-Time, mobile interventions over time. It will also support the curation of data to be contributed to the ILHBN flagship database. These data will support the development of models with the potential to lead to insights about a range of dynamic behavioral processes including engagement with mobile technologies in general. Finally, this Supplement will support the development of dynamic computational models of engagement in JITAIs and the tools to run them. Together, these activities move the field of ILD and engagement with ILD and JITAIs forward substantially.