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Psychometric properties of the CDC Symptom Inventory for assessment of chronic fatigue syndrome.
MedLine Citation:
PMID:  16042777     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
OBJECTIVES: Validated or standardized self-report questionnaires used in research studies and clinical evaluation of chronic fatigue syndrome (CFS) generally focus on the assessment of fatigue. There are relatively few published questionnaires that evaluate case defining and other accompanying symptoms in CFS. This paper introduces the self-report CDC CFS Symptom Inventory and analyzes its psychometric properties. METHODS: One hundred sixty-four subjects (with CFS, other fatiguing illnesses and non fatigued controls) identified from the general population of Wichita, Kansas were enrolled. Evaluation included a physical examination, a standardized psychiatric interview, three previously validated self-report questionnaires measuring fatigue and illness impact (Medical Outcomes Survey Short-Form-36 [MOS SF-36], Multidimensional Fatigue Inventory [MFI], Chalder Fatigue Scale), and the CDC CFS Symptom Inventory. Based on theoretical assumptions and statistical analyses, we developed several different Symptom Inventory scores and evaluated them on their ability to differentiate between participants with CFS and non-fatigued controls. RESULTS: The Symptom Inventory had good internal consistency and excellent convergent validity. A Total score (all symptoms), Case Definition score (CFS case defining symptoms) and Short Form score (6 symptoms with minimal correlation) differentiated CFS cases from controls. Furthermore, both the Case Definition and Short Form scores distinguished people with CFS from fatigued subjects who did not meet criteria for CFS. CONCLUSION: The Symptom Inventory appears to be a reliable and valid instrument to assess symptoms that accompany CFS. It is a positive addition to existing instruments measuring fatigue because it allows other dimensions of the illness to be assessed. Further research is needed to confirm and replicate the current findings in a normative population.
Authors:
Dieter Wagner; Rosane Nisenbaum; Christine Heim; James F Jones; Elizabeth R Unger; William C Reeves
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Publication Detail:
Type:  Journal Article     Date:  2005-07-22
Journal Detail:
Title:  Population health metrics     Volume:  3     ISSN:  1478-7954     ISO Abbreviation:  Popul Health Metr     Publication Date:  2005 Jul 
Date Detail:
Created Date:  2005-08-08     Completed Date:  2005-10-06     Revised Date:  2009-11-18    
Medline Journal Info:
Nlm Unique ID:  101178411     Medline TA:  Popul Health Metr     Country:  England    
Other Details:
Languages:  eng     Pagination:  8     Citation Subset:  -    
Affiliation:
Division of Viral and Rickettsial Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA. dieter_krefeld@web.de
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