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05-03-2018 | Uitgave 6/2018

Quality of Life Research 6/2018

Longitudinal and dynamic measurement invariance of the FACIT-Fatigue scale: an application of the measurement model of derivatives to ECOG-ACRIN study E2805

Tijdschrift:
Quality of Life Research > Uitgave 6/2018
Auteurs:
Ryne Estabrook, David Cella, Fengmin Zhao, Judith Manola, Robert S. DiPaola, Lynne I. Wagner, Naomi B. Haas

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 (\(\chi ^2_{12}=49.597\), \({\textit{p}}<.001\)), 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.

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