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. Gibbons
  • Betsy J. Feldman
  • Heidi M. Crane
  • Michael Mugavero
  • James H. Willig
  • Donald Patrick
  • Joseph Schumacher
  • Michael Saag
  • Mari M. Kitahata
  • Paul K. Crane
Article

DOI: 10.1007/s11136-011-9882-y

Cite this article as:
Gibbons, L.E., Feldman, B.J., Crane, H.M. et al. Qual Life Res (2011) 20: 1349. doi:10.1007/s11136-011-9882-y

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

CalibrationComputerized adaptive testingDepressionItem banksItem response theoryPROMIS

Abbreviations

CAT

Computerized adaptive testing

CFA

Confirmatory factor analysis

CFI

Comparative Fit Index

DIF

Differential item functioning

PHQ-9

Patient Health Questionnaire from the PRIME-MD depression measure

PRO

Patient-reported outcome

PROMIS

Patient-Reported Outcome Measurement Information System

RMSEA

Root mean square error of approximation

SD

Standard deviation

SEM

Standard error of measurement

TLI

Tucker–Lewis Index

UW

University of Washington

UAB

University of Alabama at Birmingham

Supplementary material

11136_2011_9882_MOESM1_ESM.doc (272 kb)
Supplementary material 1 (DOC 272 kb)

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Laura E. Gibbons
    • 1
  • Betsy J. Feldman
    • 2
  • Heidi M. Crane
    • 2
  • Michael Mugavero
    • 3
  • James H. Willig
    • 4
  • Donald Patrick
    • 5
  • Joseph Schumacher
    • 6
  • Michael Saag
    • 7
  • Mari M. Kitahata
    • 2
  • Paul K. Crane
    • 1
  1. 1.General Internal MedicineUniversity of WashingtonSeattleUSA
  2. 2.Allergy and Infectious DiseasesUniversity of WashingtonSeattleUSA
  3. 3.Department of Medicine, Division of Infectious DiseaseUniversity of Alabama at BirminghamBirminghamUSA
  4. 4.Department of Medicine, Division of Infectious DiseaseUniversity of Alabama at BirminghamBirminghamUSA
  5. 5.Department of Health ServicesUniversity of WashingtonSeattleUSA
  6. 6.Division of Preventive Medicine, School of MedicineUniversity of Alabama at BirminghamBirminghamUSA
  7. 7.Center for AIDS ResearchUniversity of Alabama at BirminghamBirminghamUSA