International audienceBackground: Patient-reported outcome measures (PROMs) are commonly used in deprescribing studies. Assuming measurement invariance, patients with different characteristics should perceive and interpret the items in the same way. However, differential item functioning (DIF) may occur when patients from two different subgroups perceive or interpret an item differently in PROMs. These patients with a same ”true” level have differential probabilities of endorsing an item. If DIF occurs, the estimation of the difference when comparing two subgroups may be biased.Objective: This study aims to detect DIF in the revised Patients’ Attitudes Toward Deprescribing questionnaire (rPATD).Methods: Data from a proton pump inhibitors (PPI) deprescribing trial in France were used. The French rPATD was sent by post to a 10% sample of patients who received PPI for more than one year, before the start of the trial in November 2020. Firstly, we will verify that our data fits a partial credit model, i.e. unidimensionality and local independence. Secondly, we will assess the DIF across three covariables: gender, age, and medication management. The DIF detection will be performed at the item-level using the ROSALI algorithm, previously described and developed on STATA.Results: A total of 1862 patients responded to the rPATD. The analyses are currently performed.Conclusions: At the conference, we will be able to i) assess the occurrence of DIF in our dataset and ii) illustrate how to detect DIF in PROMs to avoid measurement bias