Young Sean D
Institute for Prediction Technology, Department of Informatics, University of California, Irvine, Irvine, CA, United States.
Department of Emergency Medicine, UCI School of Medicine, Irvine, CA, United States.
J Med Internet Res. 2020 Jun 26;22(6):e15563. doi: 10.2196/15563.
A growing number of interventions incorporate digital and social technologies (eg, social media, mobile phone apps, and wearable devices) into their design for behavior change. However, because of a number of factors, including changing trends in the use of technology over time, results on the efficacy of these interventions have been mixed. An updated framework is needed to help researchers better plan behavioral technology interventions by anticipating the needed resources and potential changes in trends that may affect interventions over time. Focusing on the domain of health interventions as a use case, we present the Adaptive Behavioral Components (ABC) model for technology-based behavioral interventions. ABC is composed of five components: basic behavior change; intervention, or problem-focused characteristics; population, social, and behavioral characteristics; individual-level and personality characteristics; and technology characteristics. ABC was designed with the goals of (1) guiding high-level development for digital technology-based interventions; (2) helping interventionists consider, plan for, and adapt to potential barriers that may arise during longitudinal interventions; and (3) providing a framework to potentially help increase the consistency of findings among digital technology intervention studies. We describe the planning of an HIV prevention intervention as a case study for how to implement ABC into intervention design. Using the ABC model to plan future interventions might help to improve the design of and adherence to longitudinal behavior change intervention protocols; allow these interventions to adapt, anticipate, and prepare for changes that may arise over time; and help to potentially improve intervention behavior change outcomes. Additional research is needed on the influence of each of ABC's components to help improve intervention design and implementation.
越来越多的干预措施在其行为改变设计中融入了数字和社交技术（如社交媒体、手机应用程序和可穿戴设备）。然而，由于包括技术使用趋势随时间变化在内的诸多因素，这些干预措施的效果参差不齐。需要一个更新的框架，以帮助研究人员通过预测所需资源以及可能随时间影响干预措施的趋势变化，更好地规划行为技术干预措施。以健康干预领域作为一个应用案例，我们提出了基于技术的行为干预的适应性行为成分（ABC）模型。ABC由五个成分组成：基本行为改变；干预或问题聚焦特征；人群、社会和行为特征；个体层面和个性特征；以及技术特征。ABC的设计目标是：（1）指导基于数字技术的干预措施的高层次开发；（2）帮助干预人员考虑、规划并适应纵向干预过程中可能出现的潜在障碍；（3）提供一个框架，有可能帮助提高数字技术干预研究结果的一致性。我们将一项艾滋病毒预防干预措施的规划作为一个案例研究，说明如何将ABC应用于干预设计。使用ABC模型来规划未来的干预措施可能有助于改进纵向行为改变干预方案的设计和依从性；使这些干预措施能够适应、预测并为随时间可能出现的变化做好准备；并有可能帮助改善干预行为改变的结果。需要对ABC每个成分的影响进行更多研究，以帮助改进干预设计和实施。
