Abstract Background: The current practice of counseling high-risk breast cancer patients using probabilistic risk estimates has not proven to be effective in engaging women, with less than 1% of eligible women participating in medical interventions to reduce breast cancer risk. Further, studies show that racial and ethnic minority women are under-represented in breast cancer prevention clinical trials (Cyrus-David, 2006), and they are less likely than whites to be aware of, discuss, or take chemoprevention agents (Kaplan et al., 2006). This study seeks to describe how a diverse group of women use explanatory models of risk to describe perceptions of breast cancer risk and make decisions about risk-reducing behaviors. Methods: 30 in-depth, qualitative interviews were collected at two US academic hospitals as part of a National Surgical Adjuvant Breast and Bowel Project mixed-methods study to oversample for racial and ethnic minorities. Women identified to have an elevated risk of developing breast cancer were interviewed following risk counseling with a medical provider. A thematic analysis informed by grounded theory methods was conducted. The explanatory model framework (Kleinman, 1978) guided formation of codes around explanatory model topic areas (etiology, symptoms, pathophysiology, course of illness, and treatment). These explanatory model codes were supplemented with inductive codes developed through open coding related to beliefs about cancer, risk, health, and social context. Results: Two key themes were identified as closely linked to women's explanatory models of risk: ‘risk perception’ and ‘control over risk’. These perceptions of risk and control were used to identify patterns in how women chose to manage their risk for breast cancer. Whether women had high or low perceptions of risk and control affected the ways in which they used explanatory models to describe their decisions. For example, women with perceptions of high risk and high control all discussed their social network as influential in modeling how they could reduce their own risk. These women adopted a variety of behaviors to gain control over risk, ranging from diet and exercise changes to the use of chemoprevention agents. Conversely, women with perceptions of high risk and low control based decisions much more closely on their general explanatory models of health, falling back on established philosophies in their decision-making. Women who opted for chemoprevention agents in this group discussed their philosophy of decision making as dependent on physician recommendations. How women interpreted ‘symptoms’ of risk was also essential to women's descriptions of their participation in risk-reduction behaviors. Those women who perceived their risk to be high interpreted symptoms such as ADH, ALH, or LCIS as a disease that required medical intervention. On the other hand, women with perceptions of low risk interpreted these symptoms as in the normal course of bodily changes, contrasting with information provided by physicians suggesting an increased risk for breast cancer. Discussion: There are important differences in how women use explanatory models of risk that contribute to the adoption of medical interventions. Risk counseling must address patient explanatory models, which influence both perceptions of risk and control over risk. These perceptions subsequently influence the ways in which women describe their decisions about participating in risk-reducing behaviors. New approaches are needed to address patient beliefs and perceptions about risk and prevention for breast cancer. Failing to acknowledge the experiences of patients threatens to marginalize minority groups from preventive care. Citation Format: Christine M. Gunn, Barbara Bokhour, Tracy A. Battaglia, Sarah Blakeslee, Christine Holmberg. Explanatory models of risk: The role of social context in breast cancer risk perception and decision making. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr B68.
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Dec 21, 2023
Shouyan Xiang + 6
Open Access