Influencing Basic Behavioral Mechanisms of Action while targeting Daily Walking in Those at Risk for Cardiovascular Disease: Science of Behavior Change Factorial Experiment of Behavioral Change

我们使用行为改变的基础科学1，2实验医学方法来有效地测试效果 四种不同的行为改变技术（BCT）。这些BCT被选择来接合其中一个关键 行动的行为机制（MoAs）-自我效能-改善每天步行至少1000步， 那些久坐不动和心血管疾病风险升高的人。3，4我们提出了一个随机的25 实验室的实验，这样做。尽管我们有数百种行为改变干预措施， 活动开始时，大多数测试多BCT干预，每个随机对照试验中平均有6个BCT。6 对这些试验的系统评价得出结论，自我效能在许多情况下是提出的关键 7 - 11他们还得出结论，自我效能感是显着的 通过这些多BCT干预措施改善，身体活动也是如此。 我的结论是，一个BCT独特地参与或改变了自我效能感，而自我效能感的变化反过来又 增加体力活动，他们不能这样做。13他们不能，因为目前公布的体力活动 干预措施-只有一个例外-总是涉及多个最佳儿童支助小组。这些干预措施不 定量评估参与者是否使用了BCT。这些干预措施并不能评估 MoA和行为，以便可以适当地测试完整的中介模型， 分析了而且，他们没有估计进行这种中介模型测试的统计能力， 可能没有足够的能力来检测调解。 行为改变科学的实验方法建议研究人员识别假定的MoA， 通过实验和/或干预参与该MoA，然后评估MoA 参与产生行为改变。我们使用这种方法设计了一个实验， 久坐不动的成年人将被随机分配到16个牢房中的一个，进行为期5个月的干预。本项目的创新点 包括：1）确定四个BCT中的每一个对假设的MoA的个体效应， 设计; 2）使用序贯中介分析来解决纵向中介; 3）包括足够的 参与者（N = 480）具有足够的统计功效;以及4）定量评估BCT是否 采用 有心血管疾病风险的参与者中久坐不动的行为非常普遍， 发病率和死亡率的风险。确定哪些独特的行为改变技术涉及自我效能， 改善步行，哪些没有，可能会使未来的干预措施更有效，更科学 这是一个非常重要的公共卫生问题。

We use the basic science of behavior change1,2 experimental medicine approach to efficiently test the effects of four distinct behavior change techniques (BCTs). These BCTs are selected to engage one of the key behavioral mechanisms of action (MoAs)--self-efficacy--for improving daily walking by at least 1000 steps in those who are very sedentary and at elevated cardiovascular disease risk.3,4 We propose a randomized 25 factorial experiment to do so. Whereas we have hundreds of behavior change interventions aimed at physical activity initiation, most test multi-BCT interventions, averaging six BCTs in each randomized controlled trial.6 Systematic reviews of these trials concluded that self-efficacy was in many cases the key proposed mechanism of action that improved initiation.7-11 They also concluded that self-efficacy was significantly improved by these multi-BCT interventions, as was physical activity.7,12 However, when they attempt to conclude that one BCT uniquely engaged or changed self-efficacy, and that the change in self-efficacy in turn increased the physical activity, they cannot do so.13 They cannot, because currently published physical activity interventions--with one single exception--always have multiple BCTs involved. These interventions don't quantitatively assess whether the BCT was used by the participant. These interventions don't assess the key MoA and behavior repeatedly across time, so that a full mediation model can be appropriately tested and analyzed. And, they don't estimate statistical power for conducting such a mediation model test, and so are likely under-powered to detect mediation. The Science of Behavior Change experimental method proposes that researchers identify the putative MoA, engage this MoA through experimentation and/or intervention, and then assess the degree to which MoA engagement produces behavior change. We used this approach to design an experiment in which eligible sedentary adults will be randomized to one of 16 cells for five months of intervention. Innovations of this project include: 1) identifying the individual effects of each of four BCTs on the hypothesized MoA, with a full factorial design; 2) using sequential mediation analysis to address longitudinal mediators; 3) including sufficient participants (N=480) to have adequate statistical power; and 4) quantitatively assessing whether the BCT was used. Sedentary behavior among participants at risk for CVD is highly prevalent, and is associated with increased risk for morbidity and mortality. Identifying which unique behavior change techniques engage self-efficacy and improve walking, and which ones don't, may allow future interventions to be more efficient and scientifically informed to precisely target this important public health problem.