Do SF-36 summary component scores accurately summarize subscale scores?

Qual Life Res. 2001;10(5):395-404. doi: 10.1023/a:1012552211996.


Standard scoring algorithms were recently made available for aggregating scores from the eight SF-36 subscales in two distinct, higher-order summary scores: Physical Component Summary (PCS) and Mental Component Summary (MCS). Recent studies have suggested, however, that PCS and MCS scores are not independent and may in part be measuring the same constructs. The aims of this paper were to examine and illustrate (1) relationships between SF-36 subscale and PCS, MCS scores, (2) relationships between PCS and MCS scores, and (3) their implications for interpreting research findings. Simulation analyses were conducted to illustrate the contributions of various aspects of the scoring algorithm to potential discrepancies between subscale profile and summary component scores. Using the Swedish SF-36 normative database, correlation and regression analyses were performed to estimate the relationship between the two components, as well as the relative contributions of the subscales to the components. Discrepancies between subscale profile and component scores were identified and explained. Significant correlations (r = -0.74, -0.67) were found between PCS and MCS scores at their respective upper scoring intervals, indicating that the components are not independent. Regression analyses revealed that in these ranges PCS primarily measures aspects of mental health (57% of variance) and MCS measures physical health (65% of variance). Implications of the findings were discussed. It was concluded that the current PCS MCS scoring procedure inaccurately summarizes subscale profile scores and should therefore be revised. Until then, component scores should be interpreted with caution and only in combination with profile scores.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms
  • Female
  • Health Status Indicators*
  • Humans
  • Male
  • Middle Aged
  • Psychometrics
  • Quality of Life*
  • Regression Analysis
  • Surveys and Questionnaires / standards*
  • Sweden