Predicting Breast Cancer Screening Behaviors Using Protective Motivation Theory: A Structural Equation Modeling Approach

Abstract

Background: Breast cancer is the most universal malignancy worldwide. Getting regular screening tests to detect early breast cancer is the surest way to reduce breast cancer deaths. The purpose of this study was to explore the predictors of breast cancer screening behavior among Chinese women using the protection motivation theory (PMT). Methods: This cross-sectional study included 895 women from eastern China. Data were collected using an online questionnaire that included sociodemographic information, PMT theoretical construction, and breast cancer screening behavior. Structural equation modeling was used to test predictive relations among the PMT model variables related to breast cancer screening behavior. Results: The results showed that response efficiency (β = 0.262, p < 0.001), screening motivation (β = 0.162, p < 0.001), and socioeconomic status (SES) (β = 0.556, p < 0.001) had a direct positive effect on screening behavior. Perceived severity, response cost, and self-efficacy can indirectly influence screening behavior through screening motivations. Notably, in the PMT substructure, response cost can directly and positively affect perceived severity and response efficacy has a direct positive effect on self-efficacy. Conclusions: PMT structure and SES are important predictors of screening behavior. The PMT substructure is not only directly related to screening behavior but also has indirect effects. The findings of this study suggest that PMT can effectively predict breast screening behavior, and interventions based on the substructure of PMT to develop screening behavior in women may be more effective.

Keywords

• breast cancer
• cancer screening
• protection motivation theory
• structural equation modeling