Building the Evidence Base to Inform Planned Intervention Adaptations by Practitioners Serving Health Disparity Populations

Jennifer Alvidrez, Anna María Nápoles, Guillermo Bernal, Jacqueline Lloyd, Victoria Cargill, Dionne Godette, Lisa Cooper, Maria Yellow Horse Brave Heart, Rina Das, Tilda Farhat

Research output: Contribution to journalArticlepeer-review

Abstract

Many evidence-based interventions (EBIs) have been developed to prevent or treat major health conditions. However, many EBIs have exhibited limited adoption, reach, and sustainability when implemented in diverse community settings. This limitation is especially pronounced in low-resource settings that serve health disparity populations. Often, practitioners identify problems with existing EBIs originally developed and tested with populations different from their target population and introduce needed adaptations to make the intervention more suitable. Although some EBIs have been extensively adapted for diverse populations and evaluated, most local adaptations to improve fit for health disparity populations are not well documented or evaluated. As a result, empirical evidence is often lacking regarding the potential effectiveness of specific adaptations practitioners may be considering. We advocate an expansion in the emphasis of adaptation research from researcher-led interventions to research that informs practitioner-led adaptations. By presenting a research vision and strategies needed to build this area of science, we aim to inform research that facilitates successful adaptation and equitable implementation and delivery of EBIs that reduce health disparities.

Original languageEnglish (US)
Pages (from-to)S94-S101
JournalAmerican journal of public health
Volume109
Issue numberS1
DOIs
StatePublished - Jan 1 2019

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

Fingerprint Dive into the research topics of 'Building the Evidence Base to Inform Planned Intervention Adaptations by Practitioners Serving Health Disparity Populations'. Together they form a unique fingerprint.

Cite this