Predictors of Perceived Susceptibility of Breast Cancer and Changes Over Time: A Mixed Modeling Approach

Objective: To examine predictors of perceived susceptibility to breast cancer and assess differences across three dpendent measures. Design: Annual surveys were completed by US women veterans (N = 3,758) particepating in a repeat mammography intervention trial. Multivariable non-linear mixed model analyses examined individual- and group-level changes in perceived susceptibility to breast cancer. Dependent Measures: Three single-item measures of perceived susceptibility to breast cancer (percent risk, ordinal risk, and comparative risk likelihood). Predictors included demographic, health status, health behavior, affect, knowledge, and subjective norm variables. Results: Breast symptoms and greater cancer worry increased perceived susceptibility for all three measures. Other predictors varied by dependent measure. Random change, indicating individual variability, was observed for percent risk only. Conclusion: Despite small model effect sizes, breast symptoms and cancer worry were consistent predictors and may be good targets for meassages designed to influence women's perceived susceptibility to breast cancer. Researchers may benifit from using measues of perceived susceptibility with larger response scales, but additional measurement research is needed. Combining indicators of perceived susceptibility may be undesirable when different predictors are associated with different measures.