Translation and linguistic validation of 24 PROMIS item banks into French.

PURPOSE: The Patient-Reported Outcome Measurement Information System (PROMIS®) was developed to provide reliable, valid, and normed item banks to measure health. The item banks provide standardized scores on a common metric allowing for individualized, brief assessment (computerized adaptive tests), short forms (e.g. heart failure specific), or profile assessments (e.g. PROMIS-29). The objective of this study was to translate and linguistically validate 24 PROMIS adult item banks into French and highlight cultural nuances arising during the translation process. METHODS: We used the FACIT translation methodology. Forward translation into French by two native French-speaking translators was followed by reconciliation by a third native French-speaking translator. A native English-speaking translator fluent in French then completed a back translation of the reconciled version from French into English. Three independent reviews by bilingual translators were completed to assess the clarity and consistency of terminology and equivalency across the English source and French translations. Reconciled versions were evaluated in cognitive interviews for conceptual and linguistic equivalence. RESULTS: Twenty-four adult item banks were translated: 12 mental health, 10 physical health, and two social health. Interview data revealed that 577 items of the 590 items translated required no revisions. Conceptual and linguistic differences were evident for 11 items that required iterations to improve conceptual equivalence and two items were revised to accurately reflect the English source. CONCLUSION: French translations of 24 item banks were created for routine clinical use and research. Initial translation supported conceptual equivalence and comprehensibility. Next steps will include validation of the item banks.

Examining Race-Related Error in Two-Compartment Models of Body Composition Assessment: A Systematic Review and Meta-Analysis.

BACKGROUND: The Brozek and Siri formulas estimate relative adiposity (%Fat) from total body density (Db) using a 2-compartment (2C) model. Racial/ethnic differences in Db have been reported, along with subsequent errors in estimated %Fat. OBJECTIVE: The primary aim of this systematic review and meta-analysis was to examine potential race/ethnic differences in the accuracy of the Brozek and Siri 2C formulas using aggregate-level data. METHODS: Peer-reviewed studies available in English that provided 2C and 4C estimates of %Fat were located using searches of the PubMed (n = 150), Scopus (n = 170), and Web of Science (n = 138) online electronic databases. Random-effects models were used to determine potential differences between racial groups using a mean ES and 95% confidence intervals. RESULTS: The cumulative results from 78 effects indicate that the relative accuracy of the Brozek equation did not vary between racial groups (between group p = 0.053). In contrast, the Siri equation slightly underestimated %Fat for Asian adults (ESWMD = -1.40%, 95%CI -2.33% to -0.46%; p = 0.004) and Black adults (ESWMD = -1.10%, 95%CI -2.11% to -0.08%; p = 0.034), with no significant differences observed in Hispanic adults (ESWMD = 0.64%, 95%CI -1.02% to 2.31%; p = 0.448) and White adults (ESWMD = 0.08%, 95%CI -0.42% to 0.57%; p = 0.766) (between group p = 0.019). CONCLUSION: Small, but statistically significant, error was found between racial groups when estimating %Fat using the 2C Siri equation when compared to 4C models. However, the observed error due to race/ethnicity appears to be of little clinical or practical significance when using either equation.