The Equivalence of SF-36 Summary Health Scores Estimated Using Standard and Country-Specific Algorithms in 10 Countries

Citation data:

Journal of Clinical Epidemiology, ISSN: 0895-4356, Vol: 51, Issue: 11, Page: 1167-1170

Publication Year:
Usage 182
Abstract Views 168
Link-outs 14
Captures 165
Readers 160
Exports-Saves 5
Citations 416
Citation Indexes 416
Repository URL:;
Ware, John E., Jr.; Gandek, Barbara; Kosinski, Mark; Aaronson, Neil K.; Apolone, Giovanni; Brazier, John E.; Bullinger, Monika; Kaasa, Stein; Leplege, Alain; Prieto, Luis; Sullivan, Marianne; Thunedborg, Kate Show More Hide
Elsevier BV
Medicine; Algorithms; Cross-Cultural Comparison; Europe; Factor Analysis, Statistical; *Health Status Indicators; Humans; Psychometrics; *Quality of Life; Questionnaires; United States; Biostatistics; Epidemiology; Health Services Research
article description
Data from general population surveys ( n = 1771 to 9151) in nine European countries (Denmark, France, Germany, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) were analyzed to test the algorithms used to score physical and mental component summary measures (PCS-36/MCS-36) based on the SF-36 Health Survey. Scoring coefficients for principal components were estimated independently in each country using identical methods of factor extraction and orthogonal rotation. PCS-36 and MCS-36 scores were also estimated using standard (U.S.-derived) scoring algorithms, and results were compared. Product-moment correlations between scores estimated from standard and country-specific scoring coefficients were very high (0.98 to 1.00) for both physical and mental health components in all countries. As hypothesized for orthogonal components, correlations between physical and mental components within each country were very low (0.00 to 0.12) for both estimation methods. Mean scores for PCS-36 differed by as much as 3.0 points across countries using standard scoring, and mean scores for MCS-36 differed across countries by as much as 6.4 points. In view of the high degree of equivalence observed within each country, using standard and country-specific algorithms, we recommend use of standard scoring algorithms for purposes of multinational studies involving these 10 countries.