Validation of the Neurological Fatigue Index for stroke (NFI-Stroke)
Web of Science
AuthorMills, RJ; Pallant, JF; Koufali, M; Sharma, A; Day, S; Tennant, A; Young, CA
Source TitleHealth and Quality of Life Outcomes
University of Melbourne Author/sPallant, Julie
AffiliationRural Clinical School
Document TypeJournal Article
CitationsMills, R. J., Pallant, J. F., Koufali, M., Sharma, A., Day, S., Tennant, A. & Young, C. A. (2012). Validation of the Neurological Fatigue Index for stroke (NFI-Stroke). HEALTH AND QUALITY OF LIFE OUTCOMES, 10 (1), https://doi.org/10.1186/1477-7525-10-51.
Access StatusOpen Access
BACKGROUND: Fatigue is a common symptom in Stroke. Several self-report scales are available to measure this debilitating symptom but concern has been expressed about their construct validity. OBJECTIVE: To examine the reliability and validity of a recently developed scale for multiple sclerosis (MS) fatigue, the Neurological Fatigue Index (NFI-MS), in a sample of stroke patients. METHOD: Six patients with stroke participated in qualitative interviews which were analysed and the themes compared for equivalence to those derived from existing data on MS fatigue. 999 questionnaire packs were sent to those with a stroke within the past four years. Data from the four subscales, and the Summary scale of the NFI-MS were fitted to the Rasch measurement model. RESULTS: Themes identified by stroke patients were consistent with those identified by those with MS. 282 questionnaires were returned and respondents had a mean age of 67.3 years; 62% were male, and were on average 17.2 (SD 11.4, range 2-50) months post stroke. The Physical, Cognitive and Summary scales all showed good fit to the model, were unidimensional, and free of differential item functioning by age, sex and time. The sleep scales failed to show adequate fit in their current format. CONCLUSION: Post stroke fatigue appears to be represented by a combination of physical and cognitive components, confirmed by both qualitative and quantitative processes. The NFI-Stroke, comprising a Physical and Cognitive subscale, and a 10-item Summary scale, meets the strictest measurement requirements. Fit to the Rasch model allows conversion of ordinal raw scores to a linear metric.
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