Implementing and Evaluating an Older Adult Physical Activity Model at Scale: Framework for Action

ABSTRACT

Most research intervention trials demonstrate efficacy in selected samples. However, to improve population health, interventions that prove efficacious or effective in a research setting need to be delivered at scale. Despite this, relatively little attention has been paid to mechanisms and factors that support scaling up effective interventions. Thus, the purpose of this article is to describe the conceptual frameworks that guide implementation at scale of an evidence-based physical activity strategy for older adults (Choose to Move), our partnership approach to implementation and scale-up, and the methods we adopted to evaluate implementation and impact of this scaled-up model on older adults' physical activity, mobility, and social connectedness. From a socioecologic perspective, we describe 1) the design of the Choose to Move intervention, 2) the partnerships with key delivery organizations, 3) the implementation and scale-up frameworks that guide our approach, 4) the delivery of Choose to Move at scale, and 5) the protocols we will adopt to evaluate implementation and impact of Choose to Move. We adopt a type 2 hybrid effectiveness–implementation pre- and post-study design guided by scale-up, implementation, and evaluation frameworks. Specifically, we will first evaluate contextual factors that influence the implementation of Choose to Move. Second, we will evaluate effectiveness of Choose to Move on older adults' physical activity, sedentary time, capacity for mobility, and social connectedness using mixed methods. To address the escalating proportion of older adults that comprise our population and low levels of physical activity among them, it seems timely to refocus away from small-scale interventions. Should Choose to Move, a scalable, evidence-based physical activity model, be successfully delivered at scale, our approach has great implications to enhance older adult health at the population level.