Applying Generalizability Theory to High-Stakes Objective Structured Clinical Examinations in a Naturalistic Environment

Abstract 

Purpose

The purpose of this project was to determine if generalizability theory could be successfully applied to a high-stakes licensure objective structured clinical examination as part of its normal administrative procedures and whether the analysis could yield useful information with regard to sources of variance.

Methods

The anonymized data received from the Canadian Chiropractic Examining Board for its June 2005 Clinical Skills Examination were analyzed with generalizability theory. Variance components were estimated with SPSS 11.5 (SPSS Inc, Chicago, Ill) as partially nested data. The data included 182 candidates, 43 raters, 40 standardized patient actors, and 18 individual cases.

Results

Internal consistency estimates (Cronbach α) were .86 for day 1 and .91 for day 2. The α estimates for stations averaged .68 for day 1 and .74 for day 2. The generalizability-coefficient for the day 1 exam was .65 and for the day 2 was .42. G-coefficients for stations averaged .63 for day 1 and .74 for day 2. On day 1, the raters contributed 7% of the variance, and on day 2, the raters contributed 8%.

Conclusions

Generalizability theory can contribute to the understanding of sources of variance and provide direction for the improvement of individual stations. The size of the rater variance in a station may also indicate the need for increased training in that station or the need to make the scoring checklist more clear and definitive. Generalizability theory, however, must be cautiously applied, and it requires careful selection of the floating raters and vigorous training of the raters in each station.