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 R² 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 R² 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.

Keywords:

• factor structure
• patient-reported outcomes
• multi-morbidity
• psychometric testing
• questionnaire
• validation

Acknowledgments

The research reported in this manuscript was supported by the National Institute of Nursing Research of the National Institutes of Health (USA) under award number R01NR015441 (D. Eton, Principal investigator). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We thank Ms. Ann Harris and the Mayo Clinic Survey Research Center for formatting, distribution, and receipt of the survey. We also thank Ms. Kandace Lackore, Ms. Sarah Jenkins, and Mr. Richard Pendegraft for database support.

Disclosure

Dr Jennifer L. St. Sauver reports grants from National Institutes on Aging (USA), during the conduct of the study; grants from Exact Sciences, outside the submitted work. Dr Mark Linzer reports grants from the National Institutes of Health (NIH, USA), during the conduct of the study; grants from American Medical Association, American College of Physicians, Institute for Healthcare Improvement, American Board of Internal Medicine and NIH, outside the submitted work; in addition, Dr Linzer consults on a grant from Harvard University and received honoraria for Medical Grand Rounds on clinician worklife and burnout prevention from Harvard University and the University of Chicago. Dr David T. Eton reports grants from the NIH (USA), during the conduct of the study. The authors report no other conflicts of interest in this work.