King's College London

Research portal

The Chalder Fatigue Questionnaire is a valid and reliable measure of perceived fatigue severity in multiple sclerosis

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)677-684
JournalMultiple Sclerosis
Volume22
Issue number5
Early online date31 Jul 2015
DOIs
Publication statusPublished - 2016

Documents

  • Chalder Fatigue Questionnaire-MS

    PURE_Revised_MS_Fatigue_CFA_final_submitted_MS_JUNE_2015_v4_.docx, 133 KB, application/vnd.openxmlformats-officedocument.wordprocessingml.document

    11/08/2015

    Accepted author manuscript

King's Authors

Abstract

Background: Fatigue is one of the most distressing symptoms of multiple sclerosis (MS). Measuring MS fatigue poses a number of challenges. Many measures confound definitions of severity and impact of fatigue and/or lack psychometric validation in MS.
Objective: To evaluate the psychometric properties of an 11-item fatigue severity measure, the Chalder Fatigue Questionnaire (CFQ) in MS including validity of the factor structure, internal reliability, discriminant validity and sensitivity to change.
Methods: Data were pooled from four previous studies investigating MS fatigue using the CFQ (n=444). Data analysis included confirmatory factor analysis to determine the factor structure and model fit, correlations to assess discriminant validity and effects sizes to determine sensitivity to change.
Results: A bi-factor model with one general fatigue factor, incorporating two smaller group factors (mental and physical fatigue) had good model fit and appeared the most appropriate factor structure underlying the CFQ scale. The CFQ had high internal consistency, showed small to moderate correlations with impact of fatigue and mood, and was sensitive to change across low and high intensity behavioural interventions.
Conclusions: The CFQ measuring a composite of physical and mental fatigue severity (i.e. a total score) is a psychometrically sound measure of fatigue severity in MS.

Download statistics

No data available

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454