A Person-Centered Approach to Understanding Physical Activity and Sedentary Behavior After Stroke
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PROJECT SUMMARY/ABSTRACT Stroke affects nearly 9.4 million Americans and remains a leading cause of long-term disability. Many stroke survivors experience mobility limitations that contribute to low physical activity (PA) and high sedentary behavior (SB), two distinct behaviors with independent consequences for cardiovascular disease (CVD) risk, recurrent stroke, and long-term health. Fewer than 30% of stroke survivors meet PA guidelines, and more than 78% of waking hours each day are spent sedentary. These patterns contribute to a significant cardiovascular burden, reflected in the fact that up to 25% of stroke survivors will experience another stroke and many will face preventable CVD-related complications, including early death. This burden is not experienced equally across all individuals with stroke, particularly among individuals who are Black, from socioeconomically disadvantaged neighborhoods, or live in rural areas. Most existing studies examine only one or two environmental or personal factors at a time, rely on geographically limited samples, and use in-person designs that create barriers for individuals with mobility or transportation challenges who wish to participate. As a result, we lack a comprehensive understanding of how multiple contextual factors collectively contribute to real-world PA and SB after stroke. Guided by the International Classification of Functioning, Disability, and Health (ICF) model, this project will address this gap by using remote activity monitoring and nationwide recruitment to identify distinct contextual profiles that help explain variability in PA and SB post-stroke. Latent variable mixture modeling (LVMM) will be used to identify unobserved subgroups of stroke survivors based on a comprehensive set of environmental and personal factors associated with PA and SB. Aim 1 will identify latent classes based on environmental factors and examine their relationship to PA outcomes. Aim 2 will identify latent classes based on personal factors and examine their relationship to SB outcomes. By combining a person-centered analytic framework with continuous remote activity monitoring, this project will generate new knowledge about how patterns of contextual factors are associated with post-stroke PA and SB, while reducing participant burden to support nationwide participation. These findings will provide the foundation for future tailored and scalable interventions that target the contextual factors most relevant for supporting PA, reducing SB, and promoting long-term stroke recovery and cardiovascular health. This training plan is supported by a multidisciplinary training environment that integrates stroke rehabilitation and social epidemiology. It will advance my skills in remote activity monitoring, assessment of personal and environmental factors relevant to activity levels in individuals with chronic stroke, and advanced statistical modeling. Together, this fellowship will support my development into an independent rehabilitation scientist committed to optimizing stroke rehabilitation for all.
