OBJECTIVE: To examine whether graphical modeling is a potentially useful method for the study of human functioning using data collected by means of the International Classification of Functioning, Disability and Health (ICF). STUDY DESIGN AND SETTING: The applicability of the method was examined in a convenience sample of 616 patients from a cross-sectional multicentric study undergoing early postacute rehabilitation. Functioning was qualified using 115 second-level ICF categories. The modeling was carried out on a data set with imputed missing values. The least absolute shrinkage and selection operator (LASSO) for generalized linear models was used to identify conditional dependencies between the ICF categories. Bootstrap aggregating was used to enhance the accuracy and validity of model selection. RESULTS: The resulting graph showed highly meaningful relationships. For example, one structure centered around speaking and included three paths addressing conversation, speech functions, and mental functions of language. CONCLUSION: Graphical modeling of human functioning using data collected by means of the ICF yields clinically meaningful results. The structures found may be the basis for the identification of suitable targets for rehabilitation interventions, the identification of confounders and intermediate variables, and the selection of parsimonious sets of variables for multivariate epidemiological modeling.
OBJECTIVE: To examine whether graphical modeling is a potentially useful method for the study of human functioning using data collected by means of the International Classification of Functioning, Disability and Health (ICF). STUDY DESIGN AND SETTING: The applicability of the method was examined in a convenience sample of 616 patients from a cross-sectional multicentric study undergoing early postacute rehabilitation. Functioning was qualified using 115 second-level ICF categories. The modeling was carried out on a data set with imputed missing values. The least absolute shrinkage and selection operator (LASSO) for generalized linear models was used to identify conditional dependencies between the ICF categories. Bootstrap aggregating was used to enhance the accuracy and validity of model selection. RESULTS: The resulting graph showed highly meaningful relationships. For example, one structure centered around speaking and included three paths addressing conversation, speech functions, and mental functions of language. CONCLUSION: Graphical modeling of human functioning using data collected by means of the ICF yields clinically meaningful results. The structures found may be the basis for the identification of suitable targets for rehabilitation interventions, the identification of confounders and intermediate variables, and the selection of parsimonious sets of variables for multivariate epidemiological modeling.
Authors: Jan D Reinhardt; Ulrich Mansmann; Bernd A G Fellinghauer; Ralf Strobl; Eva Grill; Erik von Elm; Gerold Stucki Journal: Int J Public Health Date: 2010-12-17 Impact factor: 3.380
Authors: Markus Kalisch; Bernd A G Fellinghauer; Eva Grill; Marloes H Maathuis; Ulrich Mansmann; Peter Bühlmann; Gerold Stucki Journal: BMC Med Res Methodol Date: 2010-02-11 Impact factor: 4.615
Authors: Martin Müller; Gabriele Bartoszek; Katrin Beutner; Hanna Klingshirn; Susanne Saal; Anna-Janina Stephan; Ralf Strobl; Eva Grill; Gabriele Meyer Journal: Ger Med Sci Date: 2015-07-15
Authors: Susanne Saal; Gabriele Meyer; Katrin Beutner; Hanna Klingshirn; Ralf Strobl; Eva Grill; Eva Mann; Sascha Köpke; Michel H C Bleijlevens; Gabriele Bartoszek; Anna-Janina Stephan; Julian Hirt; Martin Müller Journal: BMC Geriatr Date: 2018-02-28 Impact factor: 3.921