Accelerating collaborative, cumulative, and open intervention science with an e-intervention authoring platform

背景资料。研究已经确定了一系列针对关键行为健康的循证干预措施 不良饮食、吸烟、不健康饮酒或久坐不动的生活方式等风险。然而，说实话， 成功的行为干预科学应该至少满足三个关键标准：(1)证明 干预效果的累积提高；(2)提供干预措施的比例较高 以及(3)证明对人口有意义的影响/减少疾病负担。它目前 与这些都不相遇。造成这种情况的一些原因包括(1)过度依赖不精确的交付机制 (人；通常是某种类型的治疗师或教练)很难大规模培训到忠诚，而且 不能精确地操作；(2)使用的样本大小可能远远低于所需的样本大小 准确地表征反应的异质性；以及(3)治疗师特征的交叉研究可变性， 样本特征，以及测量策略。所有这一切结合在一起，创造了一门缺乏证据的科学 在先前基准的基础上，累积改进情况。建议的解决方案。移动技术显示出重大意义 承诺作为一种可复制、透明、模块化和精确的干预交付机制。然而， 由于下列因素，流动干预措施的开发和实施进展缓慢 开发干预所需的巨大时间和金钱；跨平台兼容性的限制 和互操作性；以及缺乏可供协作的一致系统。为了满足这些需求， PI开发了计算机化干预创作系统(CIAS)，它促进了行为 通过允许研究人员直接开发复杂和交互的移动设备来干预科学 无需编程的应用程序。Cias已经被PI自己实验室之外的调查人员使用， 这一过程显示了NIH资助的广泛调查人员对该软件的浓厚兴趣， 以及显著的局限性。当前的目标。拟议的应用程序将解决这些限制，使 成为一个重要的、开源的、几乎唯一的非商业性研究资源。在目标1中，我们将 参与持续的用户体验测试，旨在使该工具更直观地使用。这一过程 预计将导致调查员界面的戏剧性重组，以及一套完整的 基于证据的用户培训和支持材料。在Aim 2中，我们将添加一系列特性和功能 使CIAS更加强大、灵活和可互操作(例如，通过构建智能医疗IT标准，如 以及FHIR开放规范，以促进与电子健康记录的集成)。在《目标3》中，我们将 参与有重点的努力，利用开放科学促进使用计算机辅助分析系统，作为多实验室合作的一部分 实践(例如，通过与开放科学框架的整合)。重要的是，我们将参与所有 在一个经验丰富的顾问小组的协助下，他们将帮助确保最终 产品具有广泛的相关性，面向未来，并可供广泛的行为科学家使用。

Background. Research has identified a wide range of evidence-based interventions for key behavioral health risks such as poor diet, smoking, unhealthy alcohol use, or a sedentary lifestyle. However, to be truly successful, behavioral intervention science should fulfill at least three key criteria: (1) demonstration of cumulative increases in intervention efficacy; (2) provision of interventions that reach a high proportion of those in need; and (3) demonstration of a meaningful population impact/reduction in disease burden. It currently meets none of these. Some reasons for this include (1) over-reliance on an imprecise delivery mechanism (people; usually therapists or coaches of some kind) that is difficult to train to fidelity on a large scale, and that cannot be manipulated with precision; (2) use of sample sizes that may be far below what is needed to accurately characterize heterogeneity of response; and (3) cross-study variability in therapist characteristics, sample characteristics, and measurement strategy. All of this combines to create a science that lacks evidence of cumulative improvements upon prior benchmarks. Proposed solution. Mobile technology shows significant promise as an intervention delivery mechanism that is replicable, transparent, modular, and precise. However, progress in the development and implementation of mobile interventions has been slowed by factors such as the tremendous time and money needed to develop an intervention; limitations in cross-platform compatibility and interoperability; and lack of a consistent system around which to collaborate. To address these needs, the PI developed the Computerized Intervention Authoring System (CIAS), which facilitates behavioral intervention science by allowing investigators to directly develop sophisticated and interactive mobile applications without programming. CIAS is already being used by investigators outside of the PI’s own lab, a process that has revealed significant interest in this software from a wide range of NIH-funded investigators, as well as significant limitations. Current aims. The proposed application will address these limitations, making CIAS into a significant, open-source, and virtually unique non-commercial research resource. In Aim 1, we will engage in sustained user experience testing designed to make the tool far more intuitive to use. This process is expected to result in a dramatic reorganization of the investigator interface, as well as in a complete set of evidence-based user training and support materials. In Aim 2, we will add a range of features and capabilities to make CIAS more powerful, flexible, and interoperable (e.g., by building to SMART Health IT standards, as well as FHIR open specifications to facilitate integration with Electronic Health Records). In Aim 3, we will engage in focused efforts to promote the use of CIAS as part of multi-lab collaborations using open science practices (e.g., via integration with the Open Science Framework). Importantly, we will engage in all of the above with the assistance of a highly accomplished panel of advisors who will help ensure that the final product is broadly relevant, future-facing, and usable to a broad range of behavioral scientists.