this age group who do not have a high school education are 20 percent less likely to have had a mammogram in the previous 2 years compared to women with a high school education or higher (Breen et al., 2001). Screening rates are also lower among women who lack health insurance. There are other predictors of screening rates, but these are among the most important. However, in spite of the remarkable increase in the proportion of women who report ever having had mammograms, as well as having had recent mammograms, most women still are not getting regular mammograms (Breen et al., 2001).
This volume presents an integrative model that summarizes key concepts from various behavioral theories (see Chapter 2). We use this theoretical model to highlight the factors that have been important in predicting use of mammography. We examined the factors that seem to be shared across diverse populations as well as those that appear to be unique to one or more groups. Understanding these issues is important to determine whether audience segmentation is needed for diverse populations. We focus our discussion on three elements of the integrative model that have the most relevance for mammography use: (1) attitudes and beliefs toward mammography screening; (2) perceived norms; and (3) environmental influences. The literature on predictors of mammography has less to say about the role of self-efficacy (personal agency), intention, and skills in women’s compliance with recommendations on screening mammography. This is partly because, unlike changing diet, mammography, while volitional, is primarily under the control of health professionals. Some studies (e.g., Ryan et al., 2001) have asked women if they feel confident they could get a mammogram if they wanted to do so and have provided tailored advice in this area.
Our review and analysis of the literature on factors that influence the use of screening mammography are organized in accor-