Article

Quality of Life Research

, Volume 20, Issue 9, pp 1349-1357

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

  • Laura E. GibbonsAffiliated withGeneral Internal Medicine, University of Washington Email author 
  • , Betsy J. FeldmanAffiliated withAllergy and Infectious Diseases, University of Washington
  • , Heidi M. CraneAffiliated withAllergy and Infectious Diseases, University of Washington
  • , Michael MugaveroAffiliated withDepartment of Medicine, Division of Infectious Disease, University of Alabama at Birmingham
  • , James H. WilligAffiliated withDepartment of Medicine, Division of Infectious Disease, University of Alabama at Birmingham
  • , Donald PatrickAffiliated withDepartment of Health Services, University of Washington
  • , Joseph SchumacherAffiliated withDivision of Preventive Medicine, School of Medicine, University of Alabama at Birmingham
  • , Michael SaagAffiliated withCenter for AIDS Research, University of Alabama at Birmingham
  • , Mari M. KitahataAffiliated withAllergy and Infectious Diseases, University of Washington
    • , Paul K. CraneAffiliated withGeneral Internal Medicine, University of Washington

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Abstract

Purpose

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.

Methods

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.

Results

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.

Conclusions

The strategy described here facilitated migration from a fixed-format legacy scale to PROMIS CAT administration and may be useful in other settings.

Keywords

Calibration Computerized adaptive testing Depression Item banks Item response theory PROMIS