As implementation science in global health continues to evolve, there is a need for valid and reliable measures that consider diverse linguistic and cultural contexts. A standardized, reproducible process for multilingual measure development may improve accessibility and validity by participants in global health settings. To address this need, we propose a rigorous methodology for multilingual measurement development. We use the example of a novel measure of multi-professional team communication quality, a determinant of implementation efforts.
The development and translation of this novel bilingual measure is comprised of seven steps. In this paper, we describe a measure developed in English and Spanish, however, this approach is not language specific. Participants are engaged throughout the process: first, an interprofessional panel of experts and second, through cognitive interviewing for measure refinement. The steps of measure development included: (1) literature review to identify previous measures of team communication; (2) development of an initial measure by the expert panel; (3) cognitive interviewing in a phased approach with the first language (English); (4): formal, forward-backward translation process with attention to colloquialisms and regional differences in languages; (5) cognitive interviewing repeated in the second language (Spanish); (6) language synthesis to refine both instruments and unify feedback; and (7) final review of the refined measure by the expert panel.
A draft measure to assess quality of multi-professional team communication was developed in Spanish and English, consisting of 52 questions in 7 domains. This measure is now ready for psychometric testing.
This seven-step, rigorous process of multilingual measure development can be used in a variety of linguistic and resource settings. This method ensures development of valid and reliable tools to collect data from a wide range of participants, including those who have historically been excluded due to language barriers. Use of this method will increase both rigor and accessibility of measurement in implementation science and advance equity in research and practice.