Usha Menon1, Kimlin Ashing, Mei Wei Chang, Shannon M Christy, Katarina Friberg-Felsted, Virginia Gil Rivas, Clement K Gwede, Qian Lu, Cathy D Meade, Jamila Sly, Monica Wang, Betina Yanez, Karen Yeary, Jean C Yi, Kassandra I Alcaraz. 1. Usha Menon, PhD, RN, FAAN, is Professor and Vice Dean of Research, University of South Florida College of Nursing, Tampa, Florida. Kimlin Ashing, PhD, is Founding Director, Center of Community Alliance for Research Education, and Professor, Department of Population Sciences, Beckman Research Institute, City of Hope Medical Center, Duarte, California. Mei Wei Chang, PhD, RN, is Associate Professor, The Ohio State University, College of Nursing, Columbus. Shannon M. Christy, PhD, is Assistant Member, Department of Health Outcomes and Behavior, Division of Population Science, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida. Katarina Friberg-Felsted, PhD, is Assistant Professor, College of Nursing, University of Utah Salt Lake City. Virginia Gil Rivas, PhD, is Professor, Department of Psychological Science, University of North Carolina at Charlotte. Clement K. Gwede, PhD, MPH, RN, FAAN, is Senior Member, Division of Population Science, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida. Qian Lu, MD, PhD, is Associate Professor, Department of Health Disparities Research, MD Anderson Cancer Center, Houston, Texas. Cathy D. Meade, PhD, RN, FAAN, is Senior Member, Division of Population Science, H. Lee Moffitt Cancer Center, and Research Institute & Department of Oncological Sciences, University of South Florida, College of Medicine, Tampa, Florida. Jamila Sly, PhD, is Assistant Professor, Department of Oncology Sciences, Icahn School of Medicine at Mount Sinai, New York, New York. Monica Wang, ScD, MS, is Assistant Professor, Department of Community Health Sciences, Boston University School of Public Health, and Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Betina Yanez, PhD, is Assistant Professor, Department of Medical Social Sciences and Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois. Karen Yeary, PhD, is Associate Professor, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock. Jean C. Yi, PhD, is Staff Scientist, Project Director, Biobehavioral Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington. Kassandra I. Alcaraz, PhD, MPH, is Strategic Director of Health Disparities Research, Behavioral Research Center, American Cancer Society, Atlanta, Georgia.
Abstract
BACKGROUND: An emphasis on precision health (PH) has stimulated precision medicine studies to focus on the interplay of biological, behavioral, and environmental factors with disease risks, treatments, prognoses, and outcomes affecting health disparities. It is imperative, as well, that improving health equity among underserved populations remains central to the efforts and aims of PH. OBJECTIVES: The aim if this study was to apply the transdisciplinary ConNECT Framework: A Model for Advancing Behavioral Medicine Science and Practice to Foster Health Equity to PH by integrating a population health agenda for reducing health disparities. METHODS: There are five ConNECT principles: (a) integrating context; (b) fostering a norm of inclusion; (c) ensuring equitable diffusion of innovations; (d) harnessing communication technology; and (e) prioritizing specialized training as an organizing framework to PH, including examples of how to integrate behavioral and socioecological determinants to better understand the contexts of individuals, systems, and place to design targeted treatments and interventions. RESULTS: We describe proactive, actionable strategies for the systematic application of ConNECT Framework principles to address health equity via the PH initiative. Context and implications for nursing research and practice are also described. DISCUSSION: The ConNECT Framework emphasizes that diversity inclusion is imperative for true population health benefit from PH, broadly in public health, behavioral medicine, medicine, and nursing, to equip health researchers and practitioners to account for contextual socioecologic data that can be aligned with biologic data for more population responsive and individually tailored interventions to prevent, diagnose, and treat diseases.
BACKGROUND: An emphasis on precision health (PH) has stimulated precision medicine studies to focus on the interplay of biological, behavioral, and environmental factors with disease risks, treatments, prognoses, and outcomes affecting health disparities. It is imperative, as well, that improving health equity among underserved populations remains central to the efforts and aims of PH. OBJECTIVES: The aim if this study was to apply the transdisciplinary ConNECT Framework: A Model for Advancing Behavioral Medicine Science and Practice to Foster Health Equity to PH by integrating a population health agenda for reducing health disparities. METHODS: There are five ConNECT principles: (a) integrating context; (b) fostering a norm of inclusion; (c) ensuring equitable diffusion of innovations; (d) harnessing communication technology; and (e) prioritizing specialized training as an organizing framework to PH, including examples of how to integrate behavioral and socioecological determinants to better understand the contexts of individuals, systems, and place to design targeted treatments and interventions. RESULTS: We describe proactive, actionable strategies for the systematic application of ConNECT Framework principles to address health equity via the PH initiative. Context and implications for nursing research and practice are also described. DISCUSSION: The ConNECT Framework emphasizes that diversity inclusion is imperative for true population health benefit from PH, broadly in public health, behavioral medicine, medicine, and nursing, to equip health researchers and practitioners to account for contextual socioecologic data that can be aligned with biologic data for more population responsive and individually tailored interventions to prevent, diagnose, and treat diseases.
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