title: Identification of candidate categories of the International Classification of Functioning Disability and Health (ICF) for a Generic ICF Core Set based on regression modelling.
abstract: BACKGROUND
  The International Classification of Functioning, Disability and Health (ICF) is the framework developed by WHO to describe functioning and disability at both the individual and population levels.While condition-specific ICF Core Sets are useful, a Generic ICF Core Set is needed to describe and compare problems in functioning across health conditions.
  
  
  METHODS
  The aims of the multi-centre, cross-sectional study presented here were: a) to propose a method to select ICF categories when a large amount of ICF-based data have to be handled, and b) to identify candidate ICF categories for a Generic ICF Core Set by examining their explanatory power in relation to item one of the SF-36. The data were collected from 1039 patients using the ICF checklist, the SF-36 and a Comorbidity Questionnaire.ICF categories to be entered in an initial regression model were selected following systematic steps in accordance with the ICF structure. Based on an initial regression model, additional models were designed by systematically substituting the ICF categories included in it with ICF categories with which they were highly correlated.
  
  
  RESULTS
  Fourteen different regression models were performed. The variance the performed models account for ranged from 22.27% to 24.0%. The ICF category that explained the highest amount of variance in all the models was sensation of pain. In total, thirteen candidate ICF categories for a Generic ICF Core Set were proposed.
  
  
  CONCLUSIONS
  The selection strategy based on the ICF structure and the examination of the best possible alternative models does not provide a final answer about which ICF categories must be considered, but leads to a selection of suitable candidates which needs further consideration and comparison with the results of other selection strategies in developing a Generic ICF Core Set.
authors.affiliation: ICF Research Branch of the WHO Collaborating Center for the Family of International Classifications at the German Institute of Medical Documentation and Information, IHRS, Ludwig-Maximilian University, Munich, Germany. alarcos.cieza@med.uni-muenchen.de
authors.forename: Alarcos
authors.initials: A
authors.lastname: Cieza
authors.forename: Szilvia
authors.initials: S
authors.lastname: Geyh
authors.forename: Somnath
authors.initials: S
authors.lastname: Chatterji
authors.forename: Nenad
authors.initials: N
authors.lastname: Kostanjsek
authors.forename: Bedirhan T
authors.initials: BT
authors.lastname: Ustün
authors.forename: Gerold
authors.initials: G
authors.lastname: Stucki
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000145:classification / Q000523:psychology*; D015897:Comorbidity; D003430:Cross-Sectional Studies; D004185:Disability Evaluation; D006233:Persons with Disabilities / Q000145:classification / Q000523:psychology*; D005858:Germany; D006801:Humans; D038801:International Classification of Diseases; D008875:Middle Aged; D015233:Models, Statistical; D010146:Pain / Q000209:etiology / Q000523:psychology; D012044:Regression Analysis; D018434:Sickness Impact Profile; D014944:World Health Organization