Demographic Disparities and Factors Influencing Cancer Treatment Decision-Making

This study aims to explore disparities in cancer treatment decision-making and the factors associated with the decision to pursue treatment. We used Behavioral Risk Factor Surveillance System (BRFSS) data collected between 2017 and 2022. We employed the PRECEDE-PROCEED model to guide our analysis of factors associated with treatment decisions. Descriptive statistics and multivariable logistic regression analysis were conducted to assess the association between treatment decision-making and the predisposing, enabling, and reinforcing factors (following the PRECEDE-PROCEED model). All analyses were weighted and adjusted for the demographic characteristics of the participants. Our sample included N = 19,388 cancer patients, 20.98% of whom refused treatment. American Indians, younger adults, and breast cancer patients were more likely to decide to go for treatment. Patients who had private insurance (OR = 1.25, P = .037) and those who did not have problems affording care (OR = 1.22, P = .02) were more likely to decide to get treatment. The more patients had regular doctors, the more they decided to continue to pursue treatment for cancer (Only one doctor: OR = 1.20, P = .042; More than one: OR = 1.28, P = .007). Finally, the more days patients experienced a bad health situation, the more they decided to have cancer treatment (for 14 + days with bad health: OR = 1.20, P < .001). The results suggest the need for enhanced patient education to improve cancer treatment adherence and informed decision-making. It highlights the importance of culturally tailored educational programs, age-related concerns, addressing financial barriers, and emphasizing the importance of regular healthcare visits for cancer patients.