Using Patient Health Questionnaire-9 item parameters of a common metric resulted in similar depression scores compared to independent item response theory model reestimation

J Clin Epidemiol. 2016 Mar:71:25-34. doi: 10.1016/j.jclinepi.2015.10.006. Epub 2015 Oct 22.

Abstract

Objectives: To investigate the validity of a common depression metric in independent samples.

Study design and setting: We applied a common metrics approach based on item-response theory for measuring depression to four German-speaking samples that completed the Patient Health Questionnaire (PHQ-9). We compared the PHQ item parameters reported for this common metric to reestimated item parameters that derived from fitting a generalized partial credit model solely to the PHQ-9 items. We calibrated the new model on the same scale as the common metric using two approaches (estimation with shifted prior and Stocking-Lord linking). By fitting a mixed-effects model and using Bland-Altman plots, we investigated the agreement between latent depression scores resulting from the different estimation models.

Results: We found different item parameters across samples and estimation methods. Although differences in latent depression scores between different estimation methods were statistically significant, these were clinically irrelevant.

Conclusion: Our findings provide evidence that it is possible to estimate latent depression scores by using the item parameters from a common metric instead of reestimating and linking a model. The use of common metric parameters is simple, for example, using a Web application (http://www.common-metrics.org) and offers a long-term perspective to improve the comparability of patient-reported outcome measures.

Keywords: Common metric; Depression; Item bank; Outcome assessment; Patient-reported outcomes; Score linking.

MeSH terms

  • Adult
  • Austria / epidemiology
  • Depressive Disorder / diagnosis*
  • Depressive Disorder / epidemiology
  • Female
  • Germany / epidemiology
  • Humans
  • Male
  • Middle Aged
  • Psychometrics
  • Reproducibility of Results
  • Surveys and Questionnaires / standards*