Comparison of UK and US methods for weighting and scoring the SF-36 summary measures.
BACKGROUND
The SF-36 is a widely used measure of health status that can be scored to provide either a profile of eight scores or two summary measures of health, the Physical Component Summary and Mental Component Summary (PCS and MCS). Scoring of the summary scales is undertaken by weighting and summing the original eight dimensions. These weights are gained from factor analysis of data from a general population and have been assumed to be country specific. However, it has been suggested that the weights gained from the US developers could be applied to all datasets, throughout the world, for purposes of comparability and simplicity. The purpose of this study is to evaluate US and UK scoring schemes in a UK population dataset, and in a cohort study of elderly congestive heart failure patients receiving standard therapy and a trial of open vs laparoscopic surgery for hernia repair.


METHODS
This paper compares algorithms developed in the USA and the UK for the calculation of the Physical and Mental Health Summary scores (PCS and MCS) for the SF-36 health status measure. In this study the PCS and MCS were calculated using a weighting scheme recommended by the developers and derived from a US population sample dataset, as well as being calculated from weights derived from an UK population sample dataset.


RESULTS
The two methods produced similar results, both cross-sectionally and in the assessment of change.


CONCLUSIONS
It is suggested that it may be necessary to weight the PCS and MCS using only the original US algorithms, which will lead to more uniform analysis of datasets and may also lead to greater uptake of the summary measures. Furthermore, the results would suggest that in international trials the SF-36 can be adopted and summary scores calculated for countries where no large-scale normative dataset is available. However, further research is needed to determine that the similarity of results gained using UK and US algorithms is not an idiosyncratic feature of the UK data. Studies to verify the findings reported here are required from other countries.
Jenkinson
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Department of Public Health, University of Oxford, Headington.
D000368:Aged; D000465:Algorithms; D015331:Cohort Studies; D005163:Factor Analysis, Statistical; D006305:Health Status Indicators; D006333:Heart Failure / Q000628:therapy; D006552:Hernia, Inguinal / Q000601:surgery; D006801:Humans; D011159:Population Surveillance; D006113:United Kingdom / Q000453:epidemiology; D014481:United States / Q000453:epidemiology