Irene G M Wijers1, Alba Ayala2, Carmen Rodriguez-Blazquez3, Angel Rodriguez-Laso4, Vicente Rodriguez-Rodriguez5, Maria João Forjaz2. 1. Department of Preventive Medicine and Quality Management, General University Hospital Gregorio Marañón, Madrid, Spain. 2. National School of Public Health, Carlos III Institute of Health and REDISSEC, Madrid, Spain. 3. National Centre of Epidemiology, Carlos III Institute of Health and CIBERNED, Madrid, Spain. 4. Biomedical Research Foundation of the University Hospital of Getafe, Madrid, Spain. 5. Institute of Economics, Geography and Demography, Spanish National Research Council, Madrid, Spain.
Abstract
Purpose of the Study: The Disease Burden Morbidity Assessment (DBMA) is a self-report questionnaire in which participants rate the disease burden caused by a number of medical conditions. This paper studies the measurement properties of the DBMA, using Rasch analysis. Design and Methods: We used data of 1,400 community-dwelling adults aged 50 years and older participating in the Ageing in Spain Longitudinal Study, Pilot Survey (ELES-PS). Test of fit to the Rasch model, reliability, unidimensionality, response dependency, category structure, scale targeting, and differential item functioning (DIF) were studied in an iterative way. Construct validity of the linear measure provided by the Rasch analysis was subsequently assessed. Results: To achieve an adequate fit to the Rasch model, all items were rescored by collapsing response categories. Reliability (Person Separation Index) was low. The scale was unidimensional and neither response dependency nor relevant DIF were found. The linear measure had a correlation of -0.48 with physical functioning, -0.47 with perceived health, 0.32 with depression, and -0.24 with quality of life (QoL) and displayed satisfactory known-groups validity by sex and age groups. Relative precision analysis showed that the linear measure discriminated better between age groups than the original raw score, but for sex no difference was found. Implications: Despite some limitations, support was found for the validity of the DBMA in older adults. Its linear scores may be useful to assess strategies aimed at improving the QoL of patients with multimorbidity. More research is needed in a hospital-based sample.
Purpose of the Study: The Disease Burden Morbidity Assessment (DBMA) is a self-report questionnaire in which participants rate the disease burden caused by a number of medical conditions. This paper studies the measurement properties of the DBMA, using Rasch analysis. Design and Methods: We used data of 1,400 community-dwelling adults aged 50 years and older participating in the Ageing in Spain Longitudinal Study, Pilot Survey (ELES-PS). Test of fit to the Rasch model, reliability, unidimensionality, response dependency, category structure, scale targeting, and differential item functioning (DIF) were studied in an iterative way. Construct validity of the linear measure provided by the Rasch analysis was subsequently assessed. Results: To achieve an adequate fit to the Rasch model, all items were rescored by collapsing response categories. Reliability (Person Separation Index) was low. The scale was unidimensional and neither response dependency nor relevant DIF were found. The linear measure had a correlation of -0.48 with physical functioning, -0.47 with perceived health, 0.32 with depression, and -0.24 with quality of life (QoL) and displayed satisfactory known-groups validity by sex and age groups. Relative precision analysis showed that the linear measure discriminated better between age groups than the original raw score, but for sex no difference was found. Implications: Despite some limitations, support was found for the validity of the DBMA in older adults. Its linear scores may be useful to assess strategies aimed at improving the QoL of patients with multimorbidity. More research is needed in a hospital-based sample.
Authors: Anne Marie Plass; Dominique Van Praag; Amra Covic; Anastasia Gorbunova; Ruben Real; Nicole von Steinbuechel Journal: PLoS One Date: 2019-10-24 Impact factor: 3.240