التفاصيل البيبلوغرافية
| العنوان: |
Applying a measurement system analysis approach to dyadic data |
| المؤلفون: |
Möllerberg, Marie-Louise, Kristofer, Årestedt, Hagell, Peter, Melin, Jeanette |
| المساهمون: |
Kristianstad University, Faculty of Health Science, Högskolan Kristianstad, Fakulteten för hälsovetenskap, Originator, Kristianstad University, Faculty of Health Science, Forskningsplattformen Hälsa i samverkan, Högskolan Kristianstad, Fakulteten för hälsovetenskap, Forskningsplattformen Hälsa i samverkan, Originator, Kristianstad University, Faculty of Health Science, Patient Reported Outcomes - Clinical Assessment Research and Education (PROCARE), Högskolan Kristianstad, Fakulteten för hälsovetenskap, Patient Reported Outcomes - Clinical Assessment Research and Education (PROCARE), Originator, Kristianstad University, Faculty of Health Science, Department of Nursing and Integrated Health Sciences, Högskolan Kristianstad, Fakulteten för hälsovetenskap, Avdelningen för sjuksköterskeutbildningarna och integrerad hälsovetenskap, Originator |
| المصدر: |
1st Scandinavian Applied Measurement Conference. |
| مصطلحات موضوعية: |
Medical and Health Sciences (3), Health Sciences (303), Other Health Sciences (30399), Medicin och hälsovetenskap (3), Hälsovetenskap (303), Annan hälsovetenskap (30399), Nursing (30305), Omvårdnad (30305) |
| الوصف: |
Introduction : The Person-Centred Care instrument for outpatient care (PCCoc) is a 36-item patient-reported experience measure with 4 ordered response categories, that aims to capture the degree of perceived person-centred care (PCC) from a patient perspective among persons with long-term conditions. The PCCoc is based on a framework that conceptualises outpatient PCC from lower to higher levels of perceived PCC, from personalization via shared decision-making to empowerment, where 35 of the PCCoc items are a part of the framework´s hierarchy. This study investigates to what extent empirical item responses are consistent with the hierarchical PCCoc conceptual framework among persons with long-term conditions in outpatient care. Methods : PCCoc data (322 responses) from persons with long-term psychiatric, cardiological, rheumatological or neurological conditions were analysed. The Rasch measurement model (RMM) was used to evaluate model fit and the empirical item ordering. Correspondence between the empirical and conceptually expected item hierarchies was assessed graphically and using the polyserial correlation between RMM derived item locations and their a-priori expected rank order. Result : Two items showed clear misfit to the RMM (fit residuals >4.9). The polyserial correlation between empirical item locations and the expected rank order using all 35 PCCoc items was 0.64; after removing the 2 misfitting items it was 0.71. In addition, subtests (i.e., testlets consisting of a combination of all items belonging to the respective hierarchical domain) were created to account for any local dependency. Subtest locations on the hierarchical continuum indicated good correspondence between empirical data and the conceptual hierarchy, when based on 35 as well as 33 items. Both subtests had a polyserial correlation of 0.99 between testlet locations and the expected rank order. Conclusion : The observed correspondence between empirical data and the conceptual framework indicates that the PCCoc reflects the underlying framework, and therefore can be a valuable instrument to support targeted PCC-promoting interventions. |
| قاعدة البيانات: |
SwePub |