The Perceived Stress Scale as a Measure of Stress: Decomposing Score Variance in Longitudinal Behavioral Medicine Studies

Abstract

Background: The Perceived Stress Scale (PSS) is a widely used measure designed to assess perceptions of recent stress. However, it is unclear to what extent the construct assessed by the PSS represents factors that are stable versus variable within individuals, and how these components might vary over time.

Purpose: Determine the degree to which variability in repeated PSS assessments is attributable to between-person versus within-person variance in two different studies and populations.

Methods: Secondary analyses utilized data from two studies with up to 13 PSS assessments: An observational study of 127 patients with heart failure followed over 39 months (Study 1), and an experimental study of 73 younger, healthy adults followed over 12 months (Study 2). Multilevel linear mixed modeling was used to estimate sources of variance in the PSS total and subscale scores across assessments.

Results: Between-person variance accounted for a large proportion of the total variance in PSS total scores in Study 1 (42.3%) and Study 2 (51.1%); within-person variance comprised the remainder. Between-person variance was higher for shorter assessment periods (e.g., 1 week), and was comparable when examining only the first 12 months of assessments in each study (52.9% vs. 51.1%).

Conclusions: Within two samples differing in age and health status, between-person variance accounted for approximately half of the total variation in PSS scores over time. While within-person variance was observed, the construct assessed by the PSS may substantially reflect a more stable characteristic of how an individual perceives stressful life circumstances than previously appreciated.

Keywords: Longitudinal; Perceived stress scale; Psychological; Psychometric properties; Reliability; Stress; Test–retest correlation.

Fig. 1.

Variogram for 13 monthly assessments of the 14-item perceived stress scale. The variogram shows the predicted test–retest correlation for three parsimonious variance decomposition models created using data from Study 2: (1) Compound symmetry (black horizontal line)—assumes that the within-person variance is uncorrelated from one assessment to the next, and thus the test–retest correlation does not depend on the time interval between assessments; (2) First-order serial correlation (i.e., autocorrelated within-person residuals; brown curve): the test–retest correlation of the within-person component of variance declines exponentially as a function of the time interval between assessments; and (3) First-order serial correlation with unique variance (i.e., the combination of a first-order serially autocorrelated component and a non-autocorrelated fluctuations component; blue curve): The non-autocorrelated component consists of “rapidly changing” (so as to not be correlated from 1 month to the next) situation-dependent factors and/or random measurement error. Estimates of the 1-, 2-, 3-, …, 12-month test–retest correlations and their 95% confidence intervals, obtained by fitting a Toeplitz model to the repeated measures data, are shown as red circles with vertical 95% confidence error bars. The variogram reveals that the third model (blue curve) provides the best fit to the 12 estimated test–retest correlations, consistent with the lower BIC statistics reported in Supplementary Material 2. Based on the estimates from the third model, the light green shaded area represents the portion of the test–retest correlation attributable to stable, trait-like variance; the light blue shaded area represents the portion of the test–retest correlation attributable to autocorrelated within-person (state-like) variance. Corresponding variograms for the Perceived Helpless subscale and the Perceived Self-Efficacy subscale are provided in Supplementary Material 3A and B.