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检验效果 四种不同的行为改变技术(BCT)。这些BCT被选中来接合其中一个关键 行为行为机制(MOAS)--自我效能--改善日常步行至少1000步 那些经常久坐且心血管疾病风险增加的人。3，4我们建议随机选择25 要做到这一点，需要进行析因实验。尽管我们有成百上千的行为改变干预措施，旨在 活动启动，大多数测试多BCT干预，在每个随机对照试验中平均有6个BCT。 对这些试验的系统回顾得出结论，在许多情况下，自我效能是提出的关键 7-11他们还得出结论，自我效能感显著 通过这些多种最佳做法的干预，体力活动也得到了改善。7，12然而，当他们试图 得出的结论是，一个BCT唯一地参与或改变了自我效能，并且自我效能的改变依次 增加了体力活动，但他们不能这样做。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bct。这些干预措施不会 定量评估参与者是否使用了BCT。这些干预措施并没有评估关键 MOA和行为，以便可以适当地测试和测试完整的中介模型 分析过了。而且，他们并不估计进行这种中介模型测试的统计能力，因此也是如此 可能没有足够的力量来检测调解。 行为改变科学实验方法提出，研究人员识别推定的MOA， 通过实验和/或干预使MOA参与进来，然后评估MOA的程度 参与会带来行为的改变。我们使用这种方法设计了一个实验，在该实验中符合条件的 久坐不动的成年人将被随机分到16个细胞中的一个进行为期5个月的干预。本项目的创新之处 包括：1)确定四种BCT中的每一种对假设的MOA的单独影响，并带有完整的阶乘 设计；2)使用序贯中介分析来处理纵向中介；3)包括足够的 参与者(N=480)具有足够的统计能力；以及4)定量评估BCT是否 使用。 久坐行为在有心血管疾病风险的参与者中非常普遍，并与增加 有发病和死亡的风险。确定哪些独特的行为改变技术利用自我效能感和 改善行走，以及哪些不改善，可能会使未来的干预措施更有效、更科学 被告知准确地针对这一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.