Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures

用于验证量表的样本量:对新开发的患者报告结局测量方法相关文献的回顾

阅读:1

Abstract

PURPOSE: New patient reported outcome (PRO) measures are regularly developed to assess various aspects of the patients' perspective on their disease and treatment. For these instruments to be useful in clinical research, they must undergo a proper psychometric validation, including demonstration of cross-sectional and longitudinal measurement properties. This quantitative evaluation requires a study to be conducted on an appropriate sample size. The aim of this research was to list and describe practices in PRO and proxy PRO primary psychometric validation studies, focusing primarily on the practices used to determine sample size. METHODS: A literature review of articles published in PubMed between January 2009 and September 2011 was conducted. Three selection criteria were applied including a search strategy, an article selection strategy, and data extraction. Agreements between authors were assessed, and practices of validation were described. RESULTS: Data were extracted from 114 relevant articles. Within these, sample size determination was low (9.6%, 11/114), and were reported as either an arbitrary minimum sample size (n = 2), a subject to item ratio (n = 4), or the method was not explicitly stated (n = 5). Very few articles (4%, 5/114) compared a posteriori their sample size to a subject to item ratio. Content validity, construct validity, criterion validity and internal consistency were the most frequently measurement properties assessed in the validation studies. Approximately 92% of the articles reported a subject to item ratio greater than or equal to 2, whereas 25% had a ratio greater than or equal to 20. About 90% of articles had a sample size greater than or equal to 100, whereas 7% had a sample size greater than or equal to 1000. CONCLUSIONS: The sample size determination for psychometric validation studies is rarely ever justified a priori. This emphasizes the lack of clear scientifically sound recommendations on this topic. Existing methods to determine the sample size needed to assess the various measurement properties of interest should be made more easily available.

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。