Nahum-Shani Inbal, Dziak John J, Walton Maureen A, Dempsey Walter
Institute for Social Research, University of Michigan, Ann Arbor, Michigan.
Prevention Research Center, The Pennsylvania State University, State College, Pennsylvania.
Adv Methods Pract Psychol Sci. 2022 Jul-Sep;5(3). doi: 10.1177/25152459221114279. Epub 2022 Sep 7.
Advances in mobile and wireless technologies offer tremendous opportunities for extending the reach and impact of psychological interventions and for adapting interventions to the unique and changing needs of individuals. However, insufficient engagement remains a critical barrier to the effectiveness of digital interventions. Human delivery of interventions (e.g., by clinical staff) can be more engaging but potentially more expensive and burdensome. Hence, the integration of digital and human-delivered components is critical to building effective and scalable psychological interventions. Existing experimental designs can be used to answer questions either about human-delivered components that are typically sequenced and adapted at relatively slow timescales (e.g., monthly) or about digital components that are typically sequenced and adapted at much faster timescales (e.g., daily). However, these methodologies do not accommodate sequencing and adaptation of components at multiple timescales and hence cannot be used to empirically inform the joint sequencing and adaptation of human-delivered and digital components. Here, we introduce the hybrid experimental design (HED)-a new experimental approach that can be used to answer scientific questions about building psychological interventions in which human-delivered and digital components are integrated and adapted at multiple timescales. We describe the key characteristics of HEDs (i.e., what they are), explain their scientific rationale (i.e., why they are needed), and provide guidelines for their design and corresponding data analysis (i.e., how can data arising from HEDs be used to inform effective and scalable psychological interventions).
移动和无线技术的进步为扩大心理干预的覆盖范围和影响力,以及使干预措施适应个体独特且不断变化的需求提供了巨大机遇。然而,参与度不足仍然是数字干预有效性的关键障碍。由人员实施干预(例如由临床工作人员)可能更具吸引力,但潜在成本更高且负担更重。因此,将数字和人员实施的组成部分相结合对于构建有效且可扩展的心理干预至关重要。现有的实验设计可用于回答有关通常在相对较慢的时间尺度(例如每月)进行排序和调整的人员实施组成部分的问题,或者有关通常在快得多的时间尺度(例如每天)进行排序和调整的数字组成部分的问题。然而,这些方法无法适应在多个时间尺度上对组成部分进行排序和调整,因此不能用于以实证方式为人员实施和数字组成部分的联合排序及调整提供依据。在此,我们介绍混合实验设计(HED)——一种新的实验方法,可用于回答有关构建心理干预的科学问题,在这种干预中,人员实施和数字组成部分在多个时间尺度上进行整合和调整。我们描述了HED的关键特征(即它们是什么),解释了其科学原理(即为什么需要它们),并为其设计和相应的数据分析提供了指导方针(即如何利用HED产生的数据为有效且可扩展的心理干预提供依据)。