Abstract
Purpose: While quality of life measures may be used to assess meaningful change and group differences, their scaling and validation often rely on a single occasion of measurement. Using the 13-item FACIT-Fatigue questionnaire at three timepoints, this study tests whether individual items change together in ways consistent with a general fatigue factor. Methods: The measurement model of derivatives (MMOD) is a novel method for measurement evaluation that directly assesses whether a given factor structure accurately describes how individual test items change over time. MMOD transforms item-level longitudinal data into a set of orthogonal change scores, each one representing either a within-person longitudinal mean or a different type of longitudinal change. These change scores are then factor analyzed and tested for invariance. This approach is applied to the FACIT-Fatigue scale in a sample of patients with renal cell carcinoma treated on ’ECOG-ACRIN Cancer Research Group (ECOG-ACRIN) study 2805. Results: Analyses revealed strong evidence of unidimensionality, and apparent factorial invariance using traditional techniques. MMOD revealed a small but statistically significant difference in factor structure (χ122=49.597, p<. 001), where factor loadings were weaker and more variable for measuring longitudinal change. Conclusions: The differences in factor structure were not large enough to substantially affect scale usage in this application, but they do reveal some variability across items in the FACIT-Fatigue in their ability to detect change. Future applications should consider differential sensitivity of individual items in multi-item scales, and perhaps even capitalize upon these differences by selecting items that are more sensitive to change.
| Original language | English |
|---|---|
| Pages (from-to) | 1589-1597 |
| Number of pages | 9 |
| Journal | Quality of Life Research |
| Volume | 27 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 1 2018 |
Bibliographical note
Funding Information:This study was coordinated by the ECOG-ACRIN Cancer Research Group (Peter J O'Dwyer, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award numbers: CA180820, CA180794, CA189828. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. government. Drs. Estabrook and Cella are supported by U02C-CA186878-01 (2014–2018) from the National Cancer Institute, National Institutes of Health. No authors have declared any conflicts of interest that would affect this work.
Funding Information:
Acknowledgements This study was coordinated by the ECOG-ACRIN Cancer Research Group (Peter J O’Dwyer, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award numbers: CA180820, CA180794, CA189828. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. government. Drs. Estabrook and Cella are supported by U02C-CA186878-01 (2014–2018) from the National Cancer Institute, National Institutes of Health.
Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.
Keywords
- Factor analysis
- Fatigue
- Longitudinal modeling
- Measurement invariance
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health
