Department of Preventive Medicine and Quality Management, General University Hospital Gregorio Marañón, Madrid, Spain.
National School of Public Health, Carlos III Institute of Health and REDISSEC, Madrid, Spain.
Gerontologist. 2018 Sep 14;58(5):e302-e310. doi: 10.1093/geront/gnx061.
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.
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.
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.
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.
疾病负担评估（DBMA）是一种自我报告问卷，参与者根据多项健康状况评估疾病负担。本文使用 Rasch 分析研究 DBMA 的测量特性。
我们使用了年龄在 50 岁及以上、参加西班牙老龄化纵向研究试点调查（ELES-PS）的 1400 名社区居民的数据。采用迭代方法研究适合 Rasch 模型的拟合度、信度、单维性、反应依赖性、类别结构、量表定位和差异项目功能（DIF）。随后评估 Rasch 分析提供的线性度量的结构效度。
为了使 Rasch 模型拟合良好，我们对所有项目的反应类别进行了重新评分。信度（个体分离指数）较低。该量表具有单维性，未发现反应依赖性或相关 DIF。线性度量与身体机能呈负相关（-0.48），与感知健康呈负相关（-0.47），与抑郁呈正相关（0.32），与生活质量（QoL）呈负相关（-0.24），且按性别和年龄组划分具有满意的已知组有效性。相对精度分析表明，线性度量比原始原始分数更能区分年龄组，但在性别方面没有差异。
尽管存在一些局限性，但支持 DBMA 在老年人中的有效性。其线性评分可能有助于评估旨在改善患有多种疾病的患者生活质量的策略。需要在基于医院的样本中进行更多研究。
