Date of Award
Doctor of Philosophy
Dr. James C. Petersen
Dr. Tom VanValey
Dr. Subhash Sonnad
Dr. Robert Smith
Many researchers have documented the range and extent of the health preventive behaviors. However, previous studies have generally focused on either the contact with medical professionals (secondary preventive care) or compliance with their recommendations (primary preventive care). Some have treated the two types of behaviors as one and related them to social demographic characteristics and socio-structural conditions (e.g., access to medical service). There have been very few studies that have compared the two sets of preventive behaviors. This study takes a first step to explore the correlates of secondary preventive activities and compare them with the correlates of primary preventive activities. We ask if there are patterns of relation among these activities and if social economic status affects more on secondary preventive behaviors than on primary preventive behaviors.
This study uses the data from The Behavioral Risk Factors Survey, a sample survey of 2400 adults in Michigan. The major variables in this study include socio-demographic factors and both sets of primary preventive behaviors and secondary preventive behaviors.
This dissertation examines the relation of these dimensions with socio-demographic variables and develops multivariate models of the factors that contribute to primary and secondary preventive activities. The major statistical measurements in the study are stepwise regression and canonical correlation analysis. Stepwise regression is conducted for each of the health preventive variables with demographic/socioeconomic variables and canonical correlation analyses are conducted to compare primary and secondary health preventive behaviors. Although they are significant at statistical level, the variances in stepwise regression tests and the redundancies of canonical correlation analyses are so that they have less predicting power in the interest direction. Of all the independent variables, sociodemographic variables such as age and gender are statistically significant in almost every single test among primary and secondary preventive variables. The results show that considerable similarity existed among socioeconomic groups involving the health risk factors. The analyses also reveal a reverse direction among socioeconomic and secondary preventive variables that those who in the disadvanted socioeconomic groups are more likely to receive the secondary preventive care. Thus, the tests do not show striking socioeconomic differences between the primary preventive and secondary preventive behaviors and they do not reveal that socio-economic variables impact more on the secondary preventive than on the primary preventive behaviors.
Chang, Jing, "A Comparative Study of Primary Preventive Behaviors and Secondary Preventive Behaviors Among Michigan Adults" (1993). Dissertations. 1874.