Quantifying the Degree of Fatigue in People Reporting Symptoms of Post-COVID Syndrome: Results from a Rasch Analysis

Abstract

Purpose: Fatigue is a defining feature of post-COVID syndrome (PCS), yet there is no accepted measure of this life-altering consequence. The aim here was to create a measure fit for the purposes of quantifying the severity of PCS fatigue and provide initial evidence for its relationships with measures of converging constructs. Methods: A cross-sectional analysis of the first 414 participants in the Quebec Action for Post-COVID cohort study who self-identified with PCS was undertaken. In total, 17 items were available, including items commonly used in fatigue studies and to identify post-exertional malaise (PEM). Results: Rasch analysis identified that 10 of the 17 items fit a unidimensional linear model with a theoretical range from 0 to 21 (none to highest fatigue). The PCS Fatigue Severity Measure V1 (mean: 13.8; SD: 4.7) correlated highly with criterion measures of fatigue (r ≈│0.8│). Correlations with converging constructs of pain, physical function, and health rating exceeded │0.5│. Conclusion: PCS Fatigue Severity Measure V1 was distinguished between people working versus those on sick leave (difference: 5.1 points; effect size: 1.08). Effect sizes for people with and without irritability or meeting criteria for post-traumatic distress were approximately equal to 0.5. There is sufficient evidence that this measure is fit for purpose for quantifying fatigue in this population at one point in time. Further evidence in other samples is required to verify content and performance over time.