Article

Migrating from a legacy fixed-format measure to CAT administration: Calibrating the PHQ-9 to the PROMIS depression measures

General Internal Medicine, University of Washington, Box 359780, Harborview Medical Center, 325 Ninth Ave, Seattle, WA 98104, USA
Quality of Life Research (Impact Factor: 2.49). 03/2011; 20(9):1349-57. DOI: 10.1007/s11136-011-9882-y
Source: PubMed

ABSTRACT

We provide detailed instructions for analyzing patient-reported outcome (PRO) data collected with an existing (legacy) instrument so that scores can be calibrated to the PRO Measurement Information System (PROMIS) metric. This calibration facilitates migration to computerized adaptive test (CAT) PROMIS data collection, while facilitating research using historical legacy data alongside new PROMIS data.
A cross-sectional convenience sample (n = 2,178) from the Universities of Washington and Alabama at Birmingham HIV clinics completed the PROMIS short form and Patient Health Questionnaire (PHQ-9) depression symptom measures between August 2008 and December 2009. We calibrated the tests using item response theory. We compared measurement precision of the PHQ-9, the PROMIS short form, and simulated PROMIS CAT.
Dimensionality analyses confirmed the PHQ-9 could be calibrated to the PROMIS metric. We provide code used to score the PHQ-9 on the PROMIS metric. The mean standard errors of measurement were 0.49 for the PHQ-9, 0.35 for the PROMIS short form, and 0.37, 0.28, and 0.27 for 3-, 8-, and 9-item-simulated CATs.
The strategy described here facilitated migration from a fixed-format legacy scale to PROMIS CAT administration and may be useful in other settings.

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    • "Currently eight mental health CATs/CAT systems have been applied to real patients. So far the mental health CATs cover only a few domains like depression (Fliege et al., 2005a, 2009; Gibbons et al., 2008, 2012; Pilkonis et al., 2011; 2014), anxiety (Becker et al., 2008; Gibbons et al., 2008, 2014; Walter et al., 2005, 2007), stress (Kocalevent et al., 2009), anger (Pilkonis et al., 2011), and generic health-related quality of life (HRQOL, Rebollo et al., 2010). "
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