Research & Innovation
Publications
Differential item functioning between English, German, and Spanish PROMIS® physical function ceiling items
PMU Author
Peter Augat
All Authors
Constantin Yves Plessen, Felix Fischer, Claudia Hartmann, Gregor Liegl, Ben Schalet, Aaron J. Kaat, Rodrigo Pesantez, Alexander Joeris, Marilyn Heng, Matthias Rose, , Peter Augat
Journal association
QUALITY OF LIFE RESEARCH
Abstract
PurposeWe investigated the validity of the German and Spanish translations of 35 new high functioning items added to the Patient Reported Outcomes Measurement Information System (PROMIS (R)) Physical Function item bank 2.0. We assessed differential item functioning (DIF) between three general population samples from Argentina, Germany, and the United States.MethodsPROMIS Physical Function data was collected in online panels from 3601 individuals (mean age, 41.6 years old; range, 18-88 years; 53.7% female). Of these, 1001 participants completed the Spanish version, 1000 completed the German version, and 1600 completed the English version. DIF was assessed by a multiverse analysis that systematically varied analytic choices across the entire range of plausible options within the logistic ordinal regression framework.ResultsTranslated items generally met the assumptions of unidimensionality, monotonicity, and local independence. The 272 different analyses suggest consistent DIF between languages in four items. Test characteristic curves suggested that the magnitude and impact of DIF on the test scores were negligible for all items at the test level. After correcting for potential DIF, we observed greater scoring for physical functioning in Argentina compared to the US, Cohen's d = 0.25, [0.17, 0.33], and Argentina compared to Germany, Cohen's d = 0.23, [0.15, 0.32].ConclusionsOur findings support the universal applicability of PROMIS Physical Function items across general populations in Argentina, Germany, and the U.S. The sensitivity analyses indicate that the identification of DIF items was robust for different data analytic decisions. Multiverse analysis is a promising approach to address lack of clear cutoffs in DIF identification.
Keywords
PHYSICAL FUNCTION, Differential item functioning, Promis, Sensitivity analysis