Evaluating measurement invariance across assessment modes of phone interview and computer self-administered survey for the PROMIS measures in a population-based cohort of localized prostate cancer survivors

在以局部前列腺癌幸存者为基础的人群队列中,评估电话访谈和计算机自填问卷两种评估模式下 PROMIS 指标的测量不变性

阅读:1

Abstract

PURPOSE: To evaluate measurement invariance (phone interview vs computer self-administered survey) of 15 PROMIS measures responded by a population-based cohort of localized prostate cancer survivors. METHODS: Participants were part of the North Carolina Prostate Cancer Comparative Effectiveness and Survivorship Study. Out of the 952 men who took the phone interview at 24 months post-treatment, 401 of them also completed the same survey online using a home computer. Unidimensionality of the PROMIS measures was examined using single-factor confirmatory factor analysis (CFA) models. Measurement invariance testing was conducted using longitudinal CFA via a model comparison approach. For strongly or partially strongly invariant measures, changes in the latent factors and factor autocorrelations were also estimated and tested. RESULTS: Six measures (sleep disturbance, sleep-related impairment, diarrhea, illness impact-negative, illness impact-positive, and global satisfaction with sex life) had locally dependent items, and therefore model modifications had to be made on these domains prior to measurement invariance testing. Overall, seven measures achieved strong invariance (all items had equal loadings and thresholds), and four measures achieved partial strong invariance (each measure had one item with unequal loadings and thresholds). Three measures (pain interference, interest in sexual activity, and global satisfaction with sex life) failed to establish configural invariance due to between-mode differences in factor patterns. CONCLUSIONS: This study supports the use of phone-based live interviewers in lieu of PC-based assessment (when needed) for many of the PROMIS measures.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。