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Abstract：
OBJECTIVE: To investigate the scaling properties of the Subjective Index of Physical and Social Outcome (SIPSO) after stroke in survivors to hospital discharge, unselected by age.
METHODS: Factor, Mokken, and Rasch analyses of the SIPSO using data from a prospective observational cohort study.
METHODS: Three acute care hospitals.
METHODS: Consecutive admissions (N=312) with acute stroke, unselected by age.
METHODS: Not applicable.
METHODS: Patient- or proxy-reported SIPSO, collected by postal survey 6 months after stroke.
RESULTS: Complete SIPSO questionnaires were returned by 166 of 268 survivors (median age, 72y; interquartile range, 66-81y). Factor and Mokken analyses supported both 1- and 2-factor solutions. Fit to the Rasch model for the 10-item scale was poor (χ(2) test for item-trait interaction, χ(2)=69.6; P<.001). Differential item functioning by sex and age was demonstrated for the physical subscore and was dealt with through the creation of 2 super items, resulting in a good fit to the Rasch model (χ(2)=2.35; P=.67), ordered thresholds, good targeting to the latent trait, and reasonable separation reliability (Person-Separation Index, 0.8). For the social subscore, no differential item functioning was demonstrated by age or sex. Local dependence was dealt with through the creation of 2 super items. Thereafter, fit to the Rasch model (χ(2)=5.21; P=.27) and targeting to the latent trait were good, and thresholds ordered. Separation reliability was poor (Person-Separation Index, .67).
CONCLUSIONS: The 10-item SIPSO is a valid ordinal scale in a population including older stroke survivors. A physical and social subscale structure is also supported. Subscales can be manipulated to fit the Rasch model, and a conversion table for conversion to an interval scale is provided. The social subscore has poor separation reliability, limiting its use in older stroke survivors.
METHODS: Factor, Mokken, and Rasch analyses of the SIPSO using data from a prospective observational cohort study.
METHODS: Three acute care hospitals.
METHODS: Consecutive admissions (N=312) with acute stroke, unselected by age.
METHODS: Not applicable.
METHODS: Patient- or proxy-reported SIPSO, collected by postal survey 6 months after stroke.
RESULTS: Complete SIPSO questionnaires were returned by 166 of 268 survivors (median age, 72y; interquartile range, 66-81y). Factor and Mokken analyses supported both 1- and 2-factor solutions. Fit to the Rasch model for the 10-item scale was poor (χ(2) test for item-trait interaction, χ(2)=69.6; P<.001). Differential item functioning by sex and age was demonstrated for the physical subscore and was dealt with through the creation of 2 super items, resulting in a good fit to the Rasch model (χ(2)=2.35; P=.67), ordered thresholds, good targeting to the latent trait, and reasonable separation reliability (Person-Separation Index, 0.8). For the social subscore, no differential item functioning was demonstrated by age or sex. Local dependence was dealt with through the creation of 2 super items. Thereafter, fit to the Rasch model (χ(2)=5.21; P=.27) and targeting to the latent trait were good, and thresholds ordered. Separation reliability was poor (Person-Separation Index, .67).
CONCLUSIONS: The 10-item SIPSO is a valid ordinal scale in a population including older stroke survivors. A physical and social subscale structure is also supported. Subscales can be manipulated to fit the Rasch model, and a conversion table for conversion to an interval scale is provided. The social subscore has poor separation reliability, limiting its use in older stroke survivors.
摘要：
目的：探讨卒中幸存者出院后身体和社会结果主观指数（SIPSO）的缩放特性，不按年龄选择。
方法：因素，莫肯,使用来自前瞻性观察性队列研究的数据对SIPSO进行Rasch分析。
方法：三家急性护理医院。
方法：连续入院（N=312）急性中风，不按年龄选择。
方法：不适用。
方法：患者或代理报告的SIPSO，中风后6个月通过邮政调查收集。
结果：268名幸存者中有166人返回了完整的SIPSO问卷（中位年龄，72y；四分位数间距，66-81y）。因子和Mokken分析支持1-和2-因子解决方案。10项量表对Rasch模型的拟合度较差(项-性状相互作用的χ(2)检验，χ(2)=69.6；P<.001)。物理子得分证明了按性别和年龄划分的差异项目功能，并通过创建2个超级项目来处理，结果很好地拟合了Rasch模型(χ(2)=2.35；P=.67)，有序阈值，很好地瞄准了潜在的特征，和合理的分离可靠性(人分离指数，0.8).对于社交子分数，没有通过年龄或性别证明不同的项目功能.通过创建2个超级项目来处理本地依赖。此后,符合Rasch模型(χ(2)=5.21；P=.27)，针对潜在性状良好，和有序的门槛。分离可靠性差(人分离指数，.67).
结论：在包括老年卒中幸存者的人群中，10项SIPSO是有效的序数量表。还支持物理和社会子量表结构。可以操纵子秤以适应Rasch模型，并且提供了用于转换为间隔刻度的转换表。社会子分数具有较差的分离可靠性，限制其在老年中风幸存者中的使用。
方法：因素，莫肯,使用来自前瞻性观察性队列研究的数据对SIPSO进行Rasch分析。
方法：三家急性护理医院。
方法：连续入院（N=312）急性中风，不按年龄选择。
方法：不适用。
方法：患者或代理报告的SIPSO，中风后6个月通过邮政调查收集。
结果：268名幸存者中有166人返回了完整的SIPSO问卷（中位年龄，72y；四分位数间距，66-81y）。因子和Mokken分析支持1-和2-因子解决方案。10项量表对Rasch模型的拟合度较差(项-性状相互作用的χ(2)检验，χ(2)=69.6；P<.001)。物理子得分证明了按性别和年龄划分的差异项目功能，并通过创建2个超级项目来处理，结果很好地拟合了Rasch模型(χ(2)=2.35；P=.67)，有序阈值，很好地瞄准了潜在的特征，和合理的分离可靠性(人分离指数，0.8).对于社交子分数，没有通过年龄或性别证明不同的项目功能.通过创建2个超级项目来处理本地依赖。此后,符合Rasch模型(χ(2)=5.21；P=.27)，针对潜在性状良好，和有序的门槛。分离可靠性差(人分离指数，.67).
结论：在包括老年卒中幸存者的人群中，10项SIPSO是有效的序数量表。还支持物理和社会子量表结构。可以操纵子秤以适应Rasch模型，并且提供了用于转换为间隔刻度的转换表。社会子分数具有较差的分离可靠性，限制其在老年中风幸存者中的使用。
