Comparison of construct validity of two short forms of Stroke-Specific Quality of Life scale

作者
Chia-Yeh Chou,Chien‐Yu Huang,Yi‐Jing Huang,Gong‐Hong Lin,Sheau‐Ling Huang,Shu‐Chun Lee,Ching‐Lin Hsieh
出处
期刊:PLOS ONE [Public Library of Science]
卷期号:12 (12): e0188478-e0188478 被引量:15
标识
DOI:10.1371/journal.pone.0188478
摘要

BACKGROUND: No studies have compared the 2-factor structures of Wong's and Post's versions of the short-form Stroke-Specific Quality of Life (i.e., 12-item SSQOL) scale. This study compared the construct validity of 2 short-forms of the 12-item-SSQOL (not the 12-domain-SSQOL). METHODS: Data were obtained from a previous validation study of the original 49-item SSQOL in 263 patients. Construct validity was tested by confirmatory factor analysis (CFA) to examine whether the two-factor structure, including psychosocial and physical domains, was supported in both versions. The CFA tested the data-model fit by indices: chi-square χ2/df ratio, root mean square error of approximation (RMSEA), comparative fit index (CFI), nonnormative fit index (NNFI), standard root mean square residual (SRMR), and parsimony normed fit index (PNFI). Item factor loadings (cutoffs: .50) were examined. Model fit was compared using Akaike information criterion (AIC) and consistent AIC (i.e., CAIC) values. RESULTS: All model fit indices for Post's version fell within expected ranges: χ2/df ratio = 2.02, RMSEA = 0.05, CFI = 0.97, NNFI = 0.97, SRMR = 0.06, and PNFI = 0.76. In the psychosocial domain, the item factor loadings ranged from 0.46 to 0.63. In the physical domain, all items (except the language and vision items) had acceptable factor loadings (0.68 to 0.88). However, in Wong's version, none of the model indices met the criteria for good fit. In model fit comparisons, Post's version had smaller AIC and CAIC values than did Wong's version. CONCLUSIONS: All fit indices supported Post's version, but not Wong's version. The construct validity of Post's version with a 2-factor structure was confirmed, and this version of the 12-item SSQOL is recommended.

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