Social Indicators Research and Health-Related Quality of Life Research

Abstract

The aim of this essay is to build a bridge between two intersecting areas of research, social indicators research on the one hand and health-related quality of life research on the other. The first substantive section of the paper introduces key concepts and definitions in the social indicators research tradition, e.g., social indicators, positive, negative, input and output indicators, social reports and quality of life. After that, there is a section reviewing some historical origins and motives of social indicators researchers, beginning roughly with Jeremy Bentham’s ‘felicific calculus’ and ending with the search for a comprehensive accounting scheme capable of measuring the quality of human existence with social, economic and environmental indicators.

Results of eleven surveys are reviewed which were undertaken to explain happiness on the basis of levels of satisfaction that respondents got from a dozen specific domains of their lives, e.g., satisfaction with their jobs, family relations and health. On average, for the eleven samples, we were able to explain 38% of the variance in reported happiness from some subset of the predictor variables. Satisfaction with one’s own health was never the strongest predictor of happiness in any sample. In five of the eleven samples, satisfaction with one’s own health failed to enter the final explanatory regression equation for lack of statistical significance. The results in this section of the essay show that different groups of people with different life circumstances, resources and constraints use different mixtures of ingredients to determine their happiness.

After examining some research revealing the relative importance of people’s satisfaction with their health to their overall happiness, I consider some studies revealing the importance of people’s self-reported health to their overall happiness. Self-reported health is measured primarily by the eight dimensions of SF-36. When a variety of additional potential predictors are entered into our regression equation, 44% of the variance in happiness scores is explained, but only one of the eight dimensions of SF-36 remains, namely, Mental Health. The latter accounts for a mere four percentage points out of the total 44. Thus, self-reported health has relatively little to contribute toward respondents’ reported happiness, and its measured contribution is significantly affected by the number and kinds of potential predictors employed.

Two approaches to explaining people’s satisfaction with their own health are considered. First, using the same set of health-related potential predictors of overall happiness, we are able to explain 56% of the variance in respondents’ satisfaction with their own health. Then, using Multiple Discrepancies Theory, we are able to explain about 51% of the variation in satisfaction with one’s own health scores for 8,076 undergraduates, with highs of 76% for a sample of Finnish females and 72% for Korean males. Accordingly, it is reasonable to conclude that if one’s aim is to explain people’s satisfaction with their own health, the potential predictors assembled in MDT can provide quite a bit and sometimes even more explanatory power than a reasonably broad set of measures of self-reported health.

In the penultimate section of the essay it is argued that there are good reasons for carefully distinguishing ideas of health and quality of life, and for not interpreting SF-36 and SIP scores as measures of the quality of life. It is suggested that we might all be better off if the term ‘health-related quality of life’ is simply abandoned. However, since this is unlikely to happen, it is strongly recommended that researchers be much more careful with their usage of the phrase and their interpretation of purported measures of whatever the phrase is supposed to designate.