在德国一般人群样本中对简短健康调查 8 项量表（SF-8）结构的验证性和双因素分析。
Confirmatory and bi-factor analysis of the Short Form Health Survey 8 (SF-8) scale structure in a German general population sample.
机构信息
Research Methods, Institute of Everyday Culture, Sports and Health, University of Education Freiburg, Kunzenweg 21, 79117, Freiburg, Germany.
Department of Medical Psychology and Medical Sociology, University of Leipzig, Leipzig, Germany.
出版信息
Health Qual Life Outcomes. 2021 Mar 3;19(1):73. doi: 10.1186/s12955-021-01699-8.
BACKGROUND
The SF-8 is a short form of the SF-36 Health Survey, which is used for generic assessment of physical and mental aspects of health-related quality of life (HRQoL). Each of the 8 dimensions of the SF-36 is covered by a single item in the SF-8. The aim of the study was to examine the latent model structure of the SF-8.
METHOD
One-, two- and three dimensional as well as bi-factor structural models were defined and estimated adopting the ML- as well as the WLSMV-algorithm for ordinal data. The data were collected in a German general population sample (N = 2545 persons).
RESULTS
A two- (physical and mental health) and a three-dimensional CFA structure (in addition overall health) represent the empirical data information adequately [CFI = .987/.995; SRMR = .024/.014]. If a general factor is added, the resulting bi-factor models provide a further improvement in data fit [CFI = .999/.998; SRMR = .001]. The individual items are much more highly associated with the general HRQoL factor (loadings: .698 to .908) than with the factors physical, mental, and overall health (loadings: -.206 to .566).
CONCLUSIONS
In the SF-8, each item reflects mainly general HRQoL (general factor) as well as one of the three components physical, mental, and overall health. The findings suggest in particular that the evaluation of the information of the SF-8 items can be validly supplemented by a general value HRQoL.
背景
SF-8 是 SF-36 健康调查的简短形式，用于评估与健康相关的生活质量（HRQoL）的身体和心理方面。SF-36 的 8 个维度中的每一个都由 SF-8 中的一个单一项目涵盖。本研究旨在检验 SF-8 的潜在模型结构。
方法
定义了一维、二维和三维以及双因素结构模型，并采用 ML 和 WLSMV 算法对顺序数据进行了估计。数据是从德国一般人群样本（N=2545 人）中收集的。
结果
双（身体和心理健康）和三维 CFA 结构（以及整体健康）充分代表了经验数据信息[CFI=0.987/0.995；SRMR=0.024/0.014]。如果加入一个一般因素，得到的双因素模型会进一步改善数据拟合[CFI=0.999/0.998；SRMR=0.001]。各个项目与一般 HRQoL 因素的相关性更高（负荷：0.698 至 0.908），而与身体、心理和整体健康因素的相关性较低（负荷：0.206 至 0.566）。
结论
在 SF-8 中，每个项目主要反映一般 HRQoL（一般因素）以及身体、心理和整体健康三个组成部分之一的信息。研究结果表明，SF-8 项目的信息评估可以通过一般的 HRQoL 值来有效补充。
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