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Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis

BACKGROUND: Numerous studies examined factors in promoting a patient preference for active participation in treatment decision making with only modest success. The purpose of this study was to identify types of patients wishing to participate in treatment decisions as well as those wishing to play a...

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Autores principales: Loeffert, Sabine, Ommen, Oliver, Kuch, Christine, Scheibler, Fueloep, Woehrmann, Andrej, Baldamus, Conrad, Pfaff, Holger
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3161344/
https://www.ncbi.nlm.nih.gov/pubmed/20831826
http://dx.doi.org/10.1186/1472-6947-10-47
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author Loeffert, Sabine
Ommen, Oliver
Kuch, Christine
Scheibler, Fueloep
Woehrmann, Andrej
Baldamus, Conrad
Pfaff, Holger
author_facet Loeffert, Sabine
Ommen, Oliver
Kuch, Christine
Scheibler, Fueloep
Woehrmann, Andrej
Baldamus, Conrad
Pfaff, Holger
author_sort Loeffert, Sabine
collection PubMed
description BACKGROUND: Numerous studies examined factors in promoting a patient preference for active participation in treatment decision making with only modest success. The purpose of this study was to identify types of patients wishing to participate in treatment decisions as well as those wishing to play a completely active or passive role based on a Germany-wide survey of dialysis patients; using a prediction typal analysis method that defines types as configurations of categories belonging to different attributes and takes particularly higher order interactions between variables into account. METHODS: After randomly splitting the original patient sample into two halves, an exploratory prediction configural frequency analysis (CFA) was performed on one-half of the sample (n = 1969) and the identified types were considered as hypotheses for an inferential prediction CFA for the second half (n = 1914). 144 possible prediction types were tested by using five predictor variables and control preferences as criterion. An α-adjustment (0.05) for multiple testing was performed by the Holm procedure. RESULTS: 21 possible prediction types were identified as hypotheses in the exploratory prediction CFA; four patient types were confirmed in the confirmatory prediction CFA: patients preferring a passive role show low information seeking preference, above average trust in their physician, perceive their physician's participatory decision-making (PDM)-style positive, have a lower educational level, and are 56-75 years old (Type 1; p < 0.001) or > 76 years old (Type 2; p < 0.001). Patients preferring an active role show high information seeking preference, a higher educational level, and are < 55 years old. They have either below average trust, perceive the PDM-style negative (Type 3; p < 0.001) or above average trust and perceive the PDM-style positive (Type 4; p < 0.001). CONCLUSIONS: The method prediction configural frequency analysis was newly introduced to the research field of patient participation and could demonstrate how a particular control preference role is determined by an association of five variables.
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spelling pubmed-31613442011-08-29 Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis Loeffert, Sabine Ommen, Oliver Kuch, Christine Scheibler, Fueloep Woehrmann, Andrej Baldamus, Conrad Pfaff, Holger BMC Med Inform Decis Mak Research Article BACKGROUND: Numerous studies examined factors in promoting a patient preference for active participation in treatment decision making with only modest success. The purpose of this study was to identify types of patients wishing to participate in treatment decisions as well as those wishing to play a completely active or passive role based on a Germany-wide survey of dialysis patients; using a prediction typal analysis method that defines types as configurations of categories belonging to different attributes and takes particularly higher order interactions between variables into account. METHODS: After randomly splitting the original patient sample into two halves, an exploratory prediction configural frequency analysis (CFA) was performed on one-half of the sample (n = 1969) and the identified types were considered as hypotheses for an inferential prediction CFA for the second half (n = 1914). 144 possible prediction types were tested by using five predictor variables and control preferences as criterion. An α-adjustment (0.05) for multiple testing was performed by the Holm procedure. RESULTS: 21 possible prediction types were identified as hypotheses in the exploratory prediction CFA; four patient types were confirmed in the confirmatory prediction CFA: patients preferring a passive role show low information seeking preference, above average trust in their physician, perceive their physician's participatory decision-making (PDM)-style positive, have a lower educational level, and are 56-75 years old (Type 1; p < 0.001) or > 76 years old (Type 2; p < 0.001). Patients preferring an active role show high information seeking preference, a higher educational level, and are < 55 years old. They have either below average trust, perceive the PDM-style negative (Type 3; p < 0.001) or above average trust and perceive the PDM-style positive (Type 4; p < 0.001). CONCLUSIONS: The method prediction configural frequency analysis was newly introduced to the research field of patient participation and could demonstrate how a particular control preference role is determined by an association of five variables. BioMed Central 2010-09-11 /pmc/articles/PMC3161344/ /pubmed/20831826 http://dx.doi.org/10.1186/1472-6947-10-47 Text en Copyright ©2010 Loeffert et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Loeffert, Sabine
Ommen, Oliver
Kuch, Christine
Scheibler, Fueloep
Woehrmann, Andrej
Baldamus, Conrad
Pfaff, Holger
Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis
title Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis
title_full Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis
title_fullStr Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis
title_full_unstemmed Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis
title_short Configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis
title_sort configural frequency analysis as a method of determining patients' preferred decision-making roles in dialysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3161344/
https://www.ncbi.nlm.nih.gov/pubmed/20831826
http://dx.doi.org/10.1186/1472-6947-10-47
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