Developing an accurate and efficient tool for the internalizing spectrum: A simulation study of the adaptive algorithm to the Inventory of Depression and Anxiety Symptoms II (IDAS‐II)

Abstract

Objectives: This research simulates an adaptive version of the IDAS‐II (IDAS‐CAT). Methods: 2021 participants from both community (n = 1692) and patients (n = 329) samples completed the IDAS‐II. Item response theory metric properties of the IDAS‐II full test and the 20‐items of the general depression (GD) scale were obtained. The efficiency and accuracy of different computerized adaptive algorithms were simulated. Different subsamples completed additional external measures in order to gather evidence of validity of the scores estimated with the simulated adaptive algorithms selected. Results: Both unidimensional computerized adaptive testing algorithm selected for theGDscale and the bifactor model chosen for the full test, allow70%reduction in the length of administration, maintaining a measurement error below 0.30 on the general and 0.50 on the specific factors. Results show high correlations of the scores estimated with the adaptive algorithms and the estimates based on the full test, as well as correlations with external criteria almost equal to those generated with the full test. Conclusions: IDAS‐CAT could be a reliable and fast tool for measuring internalizing spectrum.