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

点击翻译按钮获取中文摘要

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.