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

Abstract

Doc number: 2

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.