Disentangling trait versus state characteristics of the Pain Catastrophizing Scale and the PHQ-8 Depression Scale.

Journal Article (Journal Article)

BACKGROUND: Research on the role of trait versus state characteristics of a variety of measures among persons experiencing pain has been a focus for the past few decades. Studying the trait versus state nature of the Pain Catastrophizing Scale (PCS) and the Patient Health Questionnaire (PHQ-8) depression scale would be highly informative given both are commonly measured in pain populations and neither scale has been studied for trait/state contributions. METHODS: The PHQ-8 and PCS were obtained on persons undergoing knee arthroplasty at baseline, 2-, 6- and 12-month post-surgery (N = 402). The multi-trait generalization of the latent trait-state model was used to partition trait and state variability in PCS and PHQ-8 item responses simultaneously. A set of variables were used to predict trait catastrophizing and trait depression. RESULTS: For total scores, the latent traits and latent states explain 63.2% (trait = 43.2%; state = 20.0%) and 50.2% (trait = 29.4%; state = 20.8%) of the variability in PCS and PHQ-8, respectively. Patients with a high number of bodily pain sites, high levels of anxiety, young patients and African-American patients had high levels of trait catastrophizing and trait depression. The PCS and the PHQ-8 consist of both enduring trait and dynamic state characteristics, with trait characteristics dominating for both measures. CONCLUSION: Clinicians and researchers using these scales should not assume the obtained measurements solely reflect either trait- or state-based characteristics. SIGNIFICANCE: Clinicians and researchers using the PCS or PHQ-8 scales are measuring both state and trait characteristics and not just trait- or state-based characteristics.

Full Text

Duke Authors

Cited Authors

  • Dumenci, L; Kroenke, K; Keefe, FJ; Ang, DC; Slover, J; Perera, RA; Riddle, DL

Published Date

  • September 2020

Published In

Volume / Issue

  • 24 / 8

Start / End Page

  • 1624 - 1634

PubMed ID

  • 32538517

Pubmed Central ID

  • 32538517

Electronic International Standard Serial Number (EISSN)

  • 1532-2149

Digital Object Identifier (DOI)

  • 10.1002/ejp.1619

Language

  • eng

Conference Location

  • England