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Keywords

Hypertension; Intervention; Theory; African American; Health Disparities

Disciplines

Community Health and Preventive Medicine | Medicine and Health Sciences | Public Health Education and Promotion | Social and Behavioral Sciences

Abstract

African American adults, in the United States (US), bear the greatest burden of high blood pressure (HBP)--a primary risk factor for cardiovascular disease and premature death. Current research does not adequately inform the design of multi-level interventions that work to control HBP in this at-risk population. The purpose of this study was to uncover information about priority strategies recommended for HBP control in African American adults. Research questions are 1) what are factors that reduce or manage HBP in at-risk African Americans and 2) what factors are important to the design and implementation of successful HBP interventions in at-risk African Americans? A qualitative interpretive descriptive design and in-depth interview were used with a purposive sample (n=10) of doctorate-educated healthcare clinicians (i.e., physicians) and academicians (i.e., researchers) based on eligibility criteria: a) experience in treating or conducting research about HBP in African American adults, b) located within the Southern US, and c) consent to participate. Thematic analysis of audio-taped interview transcripts yielded a theoretical framework that consists of three multi-level elements believed to be critical components of interventions that can successfully manage HBP in at-risk African Americans: 1) social support, 2) lifestyle coaching, and 3) personalized medical management. Unique domains within the each element were revealed that ranged from stress management and holism to emotional resonant patient-caregiver partnership and experiential learning. Our findings were consistent with the social ecological model and have the potential to help address racial/ethnic-based health disparities through the design of patient-centered interventions. Findings will also be used to identify parameters available to simulation modelers in the design of models for optimal population level HBP control policy.


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