Riley William T, Martin Cesar A, Rivera Daniel E
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:6880-3. doi: 10.1109/EMBC.2014.6945209.
Among health behaviors, physical activity has the most extensive record of research using passive sensors. Control systems and other system dynamic approaches have long been considered applicable for understanding human behavior, but only recently has the technology provided the precise and intensive longitudinal data required for these analytic approaches. Although sensors provide intensive data on the patterns and variations of physical activity over time, the influences of these variations are often unmeasured. Health behavior theories provide an explanatory framework of the putative mediators of physical activity changes. Incorporating the intensive longitudinal measurement of these theoretical constructs is critical to improving the fit of control system model of physical activity and for advancing behavioral theory. Theory-based control models also provide guidance on the nature of the controllers which serve as the basis for just-in-time adaptive interventions based on these control system models.
在健康行为中,身体活动是使用被动传感器进行研究记录最为广泛的领域。控制系统和其他系统动力学方法长期以来一直被认为适用于理解人类行为,但直到最近,这项技术才提供了这些分析方法所需的精确且密集的纵向数据。尽管传感器能提供有关身体活动随时间变化的模式和差异的密集数据,但这些差异的影响往往未得到测量。健康行为理论为身体活动变化的假定中介因素提供了解释框架。纳入这些理论构念的密集纵向测量对于提高身体活动控制系统模型的拟合度以及推进行为理论至关重要。基于理论的控制模型还为控制器的性质提供了指导,这些控制器是基于这些控制系统模型进行即时自适应干预的基础。