OBJECTIVES: The Patient Assessment of Chronic Illness Care (PACIC) is a widely used instrument to evaluate the quality and patient-centeredness of chronic illness care based on the Chronic Care Model (CCM). It is a validated and reliable instrument which consists of 20 items. Additionally, a short form with 11 items was developed. The aim of this study was to translate this short form into German and examine the psychometric properties among patients with a chronic illness in Germany. STUDY DESIGN: Observational study design. METHODS: We performed a translation and cultural adaptation of the PACIC short form into German. The German version was externally validated with the 20-item PACIC. Cronbach a, descriptive statistics, and principal component analysis were used to assess psychometric properties. RESULTS: In total, 264 primary care patients completed the PACIC short form. The PACIC short form showed good convergent construct validity to the 20-item PACIC (Spearman rank correlation 0.82, P < .001) and high internal consistency (Cronbach a 0.87). Principal component analysis underlined the 1-dimensional structure of the instrument. No correlation between the mean overall score of the PACIC short form and the number of chronic conditions (r = 0.068; P = .273) was found. CONCLUSIONS: The PACIC short form showed good to very good psychometric properties and reliable measures regarding patient assessment of receiving care congruent with the CCM. It is a less burdensome instrument which can be used for further research of patients with more than 1 chronic condition.
OBJECTIVES: The Patient Assessment of Chronic Illness Care (PACIC) is a widely used instrument to evaluate the quality and patient-centeredness of chronic illness care based on the Chronic Care Model (CCM). It is a validated and reliable instrument which consists of 20 items. Additionally, a short form with 11 items was developed. The aim of this study was to translate this short form into German and examine the psychometric properties among patients with a chronic illness in Germany. STUDY DESIGN: Observational study design. METHODS: We performed a translation and cultural adaptation of the PACIC short form into German. The German version was externally validated with the 20-item PACIC. Cronbach a, descriptive statistics, and principal component analysis were used to assess psychometric properties. RESULTS: In total, 264 primary care patients completed the PACIC short form. The PACIC short form showed good convergent construct validity to the 20-item PACIC (Spearman rank correlation 0.82, P < .001) and high internal consistency (Cronbach a 0.87). Principal component analysis underlined the 1-dimensional structure of the instrument. No correlation between the mean overall score of the PACIC short form and the number of chronic conditions (r = 0.068; P = .273) was found. CONCLUSIONS: The PACIC short form showed good to very good psychometric properties and reliable measures regarding patient assessment of receiving care congruent with the CCM. It is a less burdensome instrument which can be used for further research of patients with more than 1 chronic condition.
Authors: Taylor L Clark; Addie L Fortmann; Athena Philis-Tsimikas; Thomas Bodenheimer; Kimberly L Savin; Haley Sandoval; Julia I Bravin; Linda C Gallo Journal: Transl Behav Med Date: 2022-02-16 Impact factor: 3.046
Authors: Anja Wollny; Christin Löffler; Eva Drewelow; Attila Altiner; Christian Helbig; Anne Daubmann; Karl Wegscheider; Susanne Löscher; Michael Pentzek; Stefan Wilm; Gregor Feldmeier; Sara Santos Journal: BMC Fam Pract Date: 2021-05-15 Impact factor: 2.497
Authors: Jo Rick; Kelly Rowe; Mark Hann; Bonnie Sibbald; David Reeves; Martin Roland; Peter Bower Journal: BMC Health Serv Res Date: 2012-08-31 Impact factor: 2.655
Authors: Kayvan Bozorgmehr; Joachim Szecsenyi; Dominik Ose; Werner Besier; Manfred Mayer; Johannes Krisam; Christian O Jacke; Hans-Joachim Salize; Ralf Brandner; Sandra Schmitt; Marion Kiel; Martina Kamradt; Tobias Freund Journal: Trials Date: 2014-06-21 Impact factor: 2.279
Authors: Beatrice Huang; Rachel Willard-Grace; Denise De Vore; Jessica Wolf; Chris Chirinos; Stephanie Tsao; Danielle Hessler; George Su; David H Thom Journal: BMC Pulm Med Date: 2017-06-09 Impact factor: 3.317
Authors: Andrea Siebenhofer; Lisa R Ulrich; Karola Mergenthal; Ina Roehl; Sandra Rauck; Andrea Berghold; Sebastian Harder; Ferdinand M Gerlach; Juliana J Petersen Journal: Implement Sci Date: 2012-08-28 Impact factor: 7.327