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ConNECT Framework, health disparities, precision health



  1. Menon, Usha
  2. Ashing, Kimlin
  3. Chang, Mei Wei
  4. Christy, Shannon M.
  5. Friberg-Felsted, Katarina
  6. Rivas, Virginia Gil
  7. Gwede, Clement K.
  8. Lu, Qian
  9. Meade, Cathy D.
  10. Sly, Jamila
  11. Wang, Monica
  12. Yanez, Betina
  13. Yeary, Karen
  14. Yi, Jean C.
  15. Alcaraz, Kassandra I.


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.