Lost in translation: advancing intervention adaptation for populations with non-dominant language preference in high diversity settings.

Abstract

As the population of individuals with non-dominant language preference (NDLP) continues to grow, the field of implementation science has yet to fully address the unique barriers that this population faces in accessing evidence-based interventions (EBIs). Traditional models of cultural adaptation have been designed primarily for single linguistic or ethnic groups, focusing on aligning interventions with specific cultural values, beliefs, and practices. While effective within narrowly defined populations, this approach is not scalable to high-diversity settings where multiple NDLP groups are served simultaneously. In this Commentary, we argue for a reconceptualization of how implementation science approaches language barriers, advocating for all implementation efforts to consider language as a core determinant of success. We highlight how two relatively recent tools developed within implementation science-the Core Function and Form Framework and causal pathway diagrams-can advance EBI adaptation for populations with NDLP. We propose a highly scalable approach that systematically assesses the linguistic, cultural, and social needs of each individual and uses these data to guide individualized tailoring of an intervention, building on the emerging model of "personalized adaptation." We highlight the need to innovate methods to ensure an individualized approach to EBI adaptation is feasible, scalable, and led by communities, with input from end-users. By harnessing the wisdom of the fields of implementation science and cultural adaptation, interventions can be adapted to the linguistic, cultural, and social needs of populations with NDLP to bring us closer to health equity in a diverse world.