Using Dynamic Structural Equation Modeling to Examine Between- and Within-Persons Factor Structure of the DASS-21

Assessment. 2023 Oct;30(7):2115-2127. doi: 10.1177/10731911221137541. Epub 2022 Dec 8.

Abstract

The recent integration of traditional time series analysis and confirmatory factor analysis techniques allows researchers to evaluate the psychometric properties of measurement instruments at between- and within-persons levels while accounting for autoregressive dependencies. The current study applies a dynamic structural equation modeling (SEM) latent factor analysis (i.e., DSEM-CFA) to a sample of 333 individuals who completed the DASS-21 at their regular therapy sessions. The results of the DSEM-CFA illuminate the reliability, invariance, and structural features of each DASS-21 subscale both between and within persons. The results suggest that the DASS-21 reliably measures depression, anxiety, and stress symptoms when evaluating differences between persons, but does not reliably assess within-persons fluctuations in symptoms over time. The results also suggest that currently accepted methods of modeling sensitivity to change within an instrument are likely lacking and the DSEM-CFA provides insight into reliability within and between persons, which is extremely important for instruments used across time.

Keywords: dynamic SEM; factor analysis; multilevel; psychometrics; time series.

MeSH terms

  • Anxiety Disorders*
  • Anxiety* / diagnosis
  • Depression / diagnosis
  • Factor Analysis, Statistical
  • Humans
  • Latent Class Analysis
  • Psychometrics
  • Reproducibility of Results
  • Stress, Psychological / diagnosis