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Multiple Sclerosis, Vol. 9, No. 5, 461-466 (2003)
DOI: 10.1191/1352458503ms953oa

Predictors of alternative medicine use by multiple sclerosis patients

Ruth Ann Marrie

Mellen Center for MS Treatment and Research, U10, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, Ohio 44195, USA, marrier{at}ccf.org

Olympia Hadjimichael

Department of Neurology, Yale University Medical School, New Haven, USA

Timothy Vollmer

Division of Neurology, Barrow Neurological Institute, Phoenix, USA

Objective: To determine the frequency of alternative medicine use among multiple sclerosis (MS) patients, and the factors which predict such use. Methods: We examined 20778 MS patients enrolled in the North A merican Research C onsortium on Multiple Sclerosis (NARC O MS) Patient Registry, residing in the USA. We used demographic and clinical data to create multivariate logistic regression models for i) lifetime use of any alternative medicine, ii) lifetime use of any alternative provider (A P), and iii) lifetime use of each of the three most common A P. Results: 20387 patients provided data regarding alternative medicine use. Lifetime use of any alternative medicine was 54% and current use was 30%. C hiropractors (51%), massage therapists (34%), and nutritionists (24%) were the most commonly used A P. In all five models, use of alternative medicine was most strongly predicted by use of a conventional provider, and more modestly by disease factors indicating more severe or prolonged disease. Predictive power of the models was poor (c-index =0.62-0.68), despite good fits for the data. Conclusions: Demographic factors play only a minimal role in predicting the use of alternative medicine in this MS population while disease factors play a slightly stronger role. There must be other factors involved that may include accessibility, social acceptability and cultural factors. G iven the frequency of alternative medicine use by this patient population, further characterization of these factors is important.

Key Words: alternative medicine • cross-sectional • epidemiology • multiple sclerosis • predictors


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