Interpreting health-related quality of life using latent rank theory

Abstract

Health-related quality of life (HRQOL) is a useful evaluation measure of medical, health, and welfare activities, but it is difficult to apply it at the individual level. To solve this problem, we analyzed a widely used HRQOL instrument, the Medical Outcomes Study short form-36 (SF-36), using latent rank theory (LRT) to try to identify findings useful for supporting health care activities. We analyzed data from 2952 people obtained in a population health survey. In Analysis 1, we examined the feasibility of applying LRT. In Analysis 2, we performed qualitative interpretation analysis of the LRT results of Analysis 1 to determine more effective use of support activities in local public health care. Analysis 1 showed that LRT could properly extract information from SF-36 data. In Analysis 2, the LRT results allowed for the classification of each subject based on HRQOL status. The method would therefore be useful for determining appropriate interventions and selecting subjects for interventions. This study demonstrated a new methodology to more effectively use HRQOL measures in health care and psychological support.