Confirmatory Factor Analyses and Differential Item Functioning of the Patient Experience with Treatment and Self-Management (PETS vs. 2.0): A Measure of Treatment Burden.

Abstract

Purpose: To examine the factor structure and differential item functioning (DIF) of the Patient Experience with Treatment and Self-management (PETS version 2.0), a measure of treatment burden.

Patients and methods: Version 2.0 of the PETS has 60 items, extending the previously-validated 48-item version 1.0 by three domains (nine items) and three additional items in an existing domain. We conducted confirmatory factor analyses (CFA) on survey responses of 439 community-dwelling adults living with multiple chronic conditions who completed PETS version 2.0, using R packages, "lavaan" and "semTools." We tested fit of second-order factors to explore simplifying the reporting of PETS scores. We examined DIF for the two second-order factors with "lordif" R package, testing groups by gender, education, and health literacy, using the McFadden pseudo R ² change criterion of ≥0.02 to flag items with DIF. Cronbach's alpha and the intraclass correlation coefficient (ICC) were used to determine the reliability of PETS domains.

Results: The first-order CFA model featuring 12 multi-item domains had an excellent fit (Comparative Fit Index [CFI]=0.989), as did the second-order CFA model (CFI=0.987), specifying two superordinate factors of treatment burden (workload and impact). Items in the workload and impact second-order factors did not show any DIF across gender, education, and health literacy groups as shown by McFadden pseudo R ² changes <0.02. Cronbach's alphas for all multi-item domain scales were ≥0.80, and ICCs of ten scales were ≥0.70, meeting the threshold for adequate test-retest reliability.

Conclusion: Findings support the construct validity and reliability of PETS version 2.0. The fit of a factor model featuring superordinate (ie, second-order) factors of workload and impact supports index scoring that will simplify reporting of PETS scores. DIF analyses indicate that items from these indices can be interpreted in the same way, regardless of gender, education, or health literacy.