Background Social isolation, the relative absence of or infrequency of contact with different types of social relationships, and loneliness (perceived isolation) are associated with adverse health outcomes. Objective To review observational and intervention research that examines the impact of social isolation and loneliness on cardiovascular and brain health and discuss proposed mechanisms for observed associations. Methods We conducted a systematic scoping review of available research. We searched 4 databases, PubMed, PsycInfo, Cumulative Index of Nursing and Allied Health, and Scopus. Findings Evidence is most consistent for a direct association between social isolation, loneliness, and coronary heart disease and stroke mortality. However, data on the association between social isolation and loneliness with heart failure, dementia, and cognitive impairment are sparse and less robust. Few studies have empirically tested mediating pathways between social isolation, loneliness, and cardiovascular and brain health outcomes using appropriate methods for explanatory analyses. Notably, the effect estimates are small, and there may be unmeasured confounders of the associations. Research in groups that may be at higher risk or more vulnerable to the effects of social isolation is limited. We did not find any intervention studies that sought to reduce the adverse impact of social isolation or loneliness on cardiovascular or brain health outcomes. Conclusions Social isolation and loneliness are common and appear to be independent risk factors for worse cardiovascular and brain health; however, consistency of the associations varies by outcome. There is a need to develop, implement, and test interventions to improve cardiovascular and brain health for individuals who are socially isolated or lonely.
Reducing cardiovascular disease disparities will require a concerted, focused effort to better adopt evidence-based interventions, in particular, those that address social determinants of health, in historically marginalized populations (ie, communities excluded on the basis of social identifiers like race, ethnicity, and social class and subject to inequitable distribution of social, economic, physical, and psychological resources). Implementation science is centered around stakeholder engagement and, by virtue of its reliance on theoretical frameworks, is custom built for addressing research-to-practice gaps. However, little guidance exists for how best to leverage implementation science to promote cardiovascular health equity. This American Heart Association scientific statement was commissioned to define implementation science with a cardiovascular health equity lens and to evaluate implementation research that targets cardiovascular inequities. We provide a 4-step roadmap and checklist with critical equity considerations for selecting/adapting evidence-based practices, assessing barriers and facilitators to implementation, selecting/using/adapting implementation strategies, and evaluating implementation success. Informed by our roadmap, we examine several organizational, community, policy, and multisetting interventions and implementation strategies developed to reduce cardiovascular disparities. We highlight gaps in implementation science research to date aimed at achieving cardiovascular health equity, including lack of stakeholder engagement, rigorous mixed methods, and equity-informed theoretical frameworks. We provide several key suggestions, including the need for improved conceptualization and inclusion of social and structural determinants of health in implementation science, and the use of adaptive, hybrid effectiveness designs. In addition, we call for more rigorous examination of multilevel interventions and implementation strategies with the greatest potential for reducing both primary and secondary cardiovascular disparities.
Background There is growing concern that routine mammography screening is overused among older women. Successful and equitable de-implementation of mammography will require a multi-level understanding of the factors contributing to mammography overuse. Methods This explanatory, sequential, mixed-methods study collected survey data (n= 52, 73.1% Hispanic, 73.1% Spanish-speaking) from women ≥70 years of age at the time of screening mammography, followed by semi-structured interviews with a subset of older women completing the survey (n=19, 63.2% Hispanic, 63.2% Spanish-speaking) and providers (n=5, 4 primary care, 1 obstetrics and gynecology) to better understand multi-level factors influencing mammography overuse and inform potential de-implementation strategies. We conducted a descriptive analysis of survey data and content analysis of qualitative interview data. Survey and interview data were examined separately, compared, integrated, and organized according to Norton and Chambers Continuum of Factors Influencing De-Implementation Process. Results Survey findings show that 87.2% of older women believe it is important to plan for an annual mammogram, 80.8% received a provider recommendation, and 78.9% received a reminder in the last 12 months to schedule a mammogram. Per interviews with older women, the majority were unaware of or did not perceive to have experienced overuse and intended to continue mammography screening. Findings from interviews with older women and providers suggest that there are multiple opportunities for older women to obtain a mammogram. Per provider interviews, almost all reported that reducing overuse was not viewed as a priority by the system or other providers. Providers also discussed that variation in mammography screening practices across providers, fear of malpractice, and monetary incentives may contribute to overscreening. Providers identified potential strategies to reduce overscreening including patient and provider education around harms of screening, leveraging the electronic health record to identify women who may receive less health benefit from screening, customizing system-generated reminder letters, and organizing workgroups to develop standard processes of care around mammography screening. Conclusions Multi-level factors contributing to mammography overuse are dynamic, interconnected, and reinforced. To ensure equitable de-implementation, there is a need for more refined and empirical testing of theories, models, and frameworks for de-implementation with a strong patient-level component that considers the interplay between multilevel factors and the larger care delivery process.
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