Bringing the models together: An empirical approach to combining variables used to explain health actions

Abstract

Considerable confusion has existed among researchers with regard to the selection of a particular model of health behavior for study, and many investigators have long felt that the actual number of truly distinct concepts relevant to explaining health-related actions is considerably lower than the large number of variables currently employed. This paper explores selected approaches and models which have been advanced to explain health actions, in terms of structural similarities and differences identified by a panel of judges who are the relevant experts in this field. Judges were asked to partition a set of 109 variables, representing 14 different models, into 12–14 groups on the basis of similarity. The structural similarities among the variable groups were evaluated using Smallest Space Analysis. Six interpretable factors emerged from the analyses: (1) accessibility to health care, (2) evaluation of health care, (3) perception of symptoms and threat of disease, (4) social network characteristics, (5) knowledge about disease, and (6) demographic characteristics. The results of the study provide a first step in developing a unified framework for explaining health actions.