We appreciate the financial assistance provided by the National Institute of Allergy and Infectious Diseases (grant numbers AI36295 and AI49720).
Data mining: comparing the empiric CFS to the Canadian ME/CFS case definition†
Article first published online: 5 AUG 2011
© 2011 Wiley Periodicals, Inc.
Journal of Clinical Psychology
Volume 68, Issue 1, pages 41–49, January 2012
How to Cite
Jason, L. A., Skendrovic, B., Furst, J., Brown, A., Weng, A. and Bronikowski, C. (2012), Data mining: comparing the empiric CFS to the Canadian ME/CFS case definition. J. Clin. Psychol., 68: 41–49. doi: 10.1002/jclp.20827
- Issue published online: 15 DEC 2011
- Article first published online: 5 AUG 2011
- chronic fatigue syndrome;
- myalgic encephalomyelitis;
- data mining;
- empiric CFS case definition;
- Canadian clinical ME/CFS case definition
This article contrasts two case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We compared the empiric CFS case definition (Reeves et al., 2005) and the Canadian ME/CFS clinical case definition (Carruthers et al., 2003) with a sample of individuals with CFS versus those without. Data mining with decision trees was used to identify the best items to identify patients with CFS. Data mining is a statistical technique that was used to help determine which of the survey questions were most effective for accurately classifying cases. The empiric criteria identified about 79% of patients with CFS and the Canadian criteria identified 87% of patients. Items identified by the Canadian criteria had more construct validity. The implications of these findings are discussed. © 2011 Wiley Periodicals, Inc. J Clin Psychol 67:1–9, 2011.