Abstract PO-045: Selected cognitive biases that influence the decision-making process in clinical trial enrollment of diverse patient populations
Authors: Milazzo JoAnne , Norton Deborah , Szelingowski Cristina , Urniasz-Lippel Alyson 
Published: December 2020

Background: Diverse populations of oncology patients are underrepresented in clinical trials. Barriers to clinical trial participation can be grouped into 2 categories: structural and procedural barriers (including but not limited to lack of public information, inadequate access, and poor insurance coverage) and cognitive and psychological barriers (biases or influences that may affect a patient’s decision to participate in a clinical trial). The focus of this project was to test psychological barriers to discover biases that may affect the decision-making process for clinical trial participation in a diverse oncology patient population. Methods: Oncology patients (n = 75) with various cancer types were recruited and surveyed to determine the influence of decision-making biases. The top 5 cancers represented were breast (n = 10), ovarian (n = 10), prostate (n = 10), non-Hodgkin lymphoma (n = 9), and lung (n = 8), with 13% of patients (n = 10) diagnosed prior to 2010 and 87% (n = 65) diagnosed in 2010 or later. Patients were 28% White (n = 21), 27% African American (n = 20), 23% Hispanic/Latino (n = 17), 9% Asian/Asian American (n = 7), and 13% other (n = 10). Among these patients, 44% had participated in a clinical trial (n = 33) while 56% had not (n = 42). From a database of &gt; 100 potential biases, 15 biases were selected based on potential actionability and testability with survey questions. Results: Five of the 15 biases selected were found to influence clinical trial participation decision-making with &gt; 90% confidence level (CL): generation effect (tendency to recall information generated by oneself compared with information received from others; 92% CL), social norms (informal understandings that govern behaviors in society; 93% CL), confirmation bias (tendency to interpret new information as confirmation of one’s own beliefs; 94% CL), false consensus effect (belief that one’s own beliefs/opinions are shared by others; 98% CL), and subadditivity effect (tendency to judge the whole as less than the sum of its parts; 100% CL). Based on these findings, 4 educational videos were developed and produced to address the actionable biases of generation effect, social norms, confirmation effect, and false consensus effect. Each video simulated an interview in which the health care provider (HCP) presented a clinical trial opportunity to patients of diverse backgrounds who may have been under-served. Videos captured the HCP recognizing the patient’s particular bias and then clarifying the patient’s questions or misconceptions. Conclusions: Generation effect, social norms, confirmation bias, false consensus effect, and subadditivity effect were 5 biases found to influence a patient’s decision-making process when considering clinical trial participation. This novel information was used to develop videos as educational tools to assist HCPs in overcoming these biases in diverse patient populations and ultimately to mitigate the effect of biases and improve enrollment of diverse patient populations in clinical trials.

Citation Format: JoAnne Milazzo, Deborah Norton, Cristina Szelingowski, Alyson Urniasz-Lippel. Selected cognitive biases that influence the decision-making process in clinical trial enrollment of diverse patient populations [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-045.