Smith Adam B, Wright Penny, Selby Peter J, Velikova Galina
Psychosocial & Clinical Practice Research Group, Cancer Research UK Clinical Centre, St. James's University Hospital, Leeds, UK.
Health Qual Life Outcomes. 2007 Apr 20;5:19. doi: 10.1186/1477-7525-5-19.
Although the Functional Assessment of Cancer Therapy--General questionnaire (FACT-G) has been validated few studies have explored the factor structure of the instrument, in particular using non-sample dependent measurement techniques, such as Rasch Models. Furthermore, few studies have explored the relationship between item fit to the Rasch Model and clinical utility. The aim of this study was to investigate the dimensionality and measurement properties of the FACT-G with Rasch Models and Factor analysis.
A factor analysis and Rasch analysis (Partial Credit Model) was carried out on the FACT-G completed by a heterogeneous sample of cancer patients (n = 465). For the Rasch analysis item fit (infit mean squares > or = 1.30), dimensionality and item invariance were assessed. The impact of removing misfitting items on the clinical utility of the subscales and FACT-G total scale was also assessed.
The factor analysis demonstrated a four factor structure of the FACT-G which broadly corresponded to the four subscales of the instrument. Internal consistency for these four scales was very good (Cronbach's alpha 0.72 - 0.85). The Rasch analysis demonstrated that each of the subscales and the FACT-G total scale had misfitting items (infit means square > or = 1.30). All these scales with the exception of the Social & Family Well-being Scale (SFWB) were unidimensional. When misfitting items were removed, the effect sizes and the clinical utility of the instrument were maintained for the subscales and the total FACT-G scores.
The results of the traditional factor analysis and Rasch analysis of the FACT-G broadly agreed. Caution should be exercised when utilising the Social & Family Well-being scale and further work is required to determine whether this scale is best represented by two factors. Additionally, removing misfitting items from scales should be performed alongside an assessment of the impact on clinical utility.
尽管癌症治疗功能评估通用问卷（FACT-G）已经过验证，但很少有研究探讨该工具的因子结构，特别是使用非样本依赖测量技术，如拉施模型。此外，很少有研究探讨项目与拉施模型的拟合度和临床效用之间的关系。本研究的目的是用拉施模型和因子分析来研究FACT-G的维度和测量特性。
对由异质性癌症患者样本（n = 465）完成的FACT-G进行因子分析和拉施分析（部分计分模型）。对于拉施分析，评估项目拟合度（内拟合均方≥1.30）、维度和项目不变性。还评估了去除拟合不佳项目对分量表和FACT-G总量表临床效用的影响。
因子分析表明FACT-G具有四因子结构，大致对应于该工具的四个分量表。这四个量表的内部一致性非常好（克朗巴赫α系数为0.72 - 0.85）。拉施分析表明，每个分量表和FACT-G总量表都有拟合不佳的项目（内拟合均方≥1.30）。除社会与家庭幸福感量表（SFWB）外，所有这些量表都是单维的。去除拟合不佳的项目后，分量表和FACT-G总分的效应量和临床效用得以维持。
FACT-G的传统因子分析和拉施分析结果大致一致。使用社会与家庭幸福感量表时应谨慎，需要进一步研究以确定该量表是否最好由两个因子表示。此外，从量表中去除拟合不佳的项目时，应同时评估对临床效用的影响。
