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Results from several population studies show that recommended scoring methods of the SF-36 and the SF-12 may lead to incorrect conclusions and subsequent health decisions

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Abstract

Purpose

To compare the measurement properties of the physical component summary (PCS) and mental component summary (MCS) scores of the SF-36 and SF-12 based on the traditional orthogonal scoring algorithms with the performance of the PCS and MCS scored based on structural equation model coefficients from a correlated model.

Methods

This study used three large-scale representative population studies to compare the measurement properties of the PCS and MCS scores of the SF-36 and SF-12 with the performance of the PCS and MCS scores based on structural equation models producing coefficients from a correlated model. We assessed the relationships of these scores with selected important mental health measures and chronic conditions from three representative Australian population studies that address clinical conditions of high prevalence and health service importance.

Results

Structural equation model scoring methods produced summary scores with higher correlations than the recommended orthogonal methods across a range of disease and health conditions. The problem experienced in using the orthogonal methods is that negative scoring coefficients are applied to negative z-scores for sub-scales, inflating the resulting summary scores. Effect sizes over a half of a standard deviation were common.

Conclusions

If health policy or investment decisions are made based on the results of studies employing the recommended orthogonal scoring methods then the expected outcome of such decisions or investments may not be achieved.

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Acknowledgments

We wish to thank the anonymous reviewer for their helpful suggestion that improved the strength of the arguments presented in this paper.

Ethical standard

This paper is based on a secondary analysis of various South Australian survey files. As such, this analysis did not require formal ethics approval; however, all of the original data collections were conducted under ethics approval with the informed consent of the participants.

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Authors and Affiliations

  1. School of Medicine, University of Adelaide, Adelaide, SA, Australia

    Graeme Tucker, Robert Adams & David Wilson

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  1. Graeme Tucker
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Correspondence to Graeme Tucker.

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Tucker, G., Adams, R. & Wilson, D. Results from several population studies show that recommended scoring methods of the SF-36 and the SF-12 may lead to incorrect conclusions and subsequent health decisions. Qual Life Res 23, 2195–2203 (2014). https://doi.org/10.1007/s11136-014-0669-9

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