Discipline: Social, Behavioral, and Economic Sciences
Subcategory: Social Sciences/Psychology/Economics
Gabrielle Johnson - Bethune-Cookman University
Co-Author(s): Enmanuel A. Chavarria, PhD, MS, CHES; Shannon M. Christy, PhD; Kimberly Williams, MPH; Khaliah Fleming, MPH, CHES; Rania Abdulla, MS; Cathy D. Meade, PhD, RN, FAAN; and Clement K. Gwede, PhD, MPH, RN
Purpose: There are numerous barriers that influence the intentions and likelihood that an individual will get screened for colorectal cancer (CRC). The intentions and likelihood for participants within the next six months have been measured in community and clinical settings from two similar studies, Increasing Access to Colorectal Cancer Testing (I-ACT) and Colorectal Cancer Awareness, Research, Awareness, Research, Education and Screening (CARES). Participants for I-ACT were recruited in community settings; hence it is referred to as the community setting in this data analysis. Participants for CARES were recruited in clinical settings and are referred to as the clinical setting. The purpose of these analyses is to determine whether participants recruited in a clinical setting have greater intentions and is more likely to get screened for CRC compared to those in a community setting. I hypothesize that those in a clinical setting will have greater intentions because participants are in the healthcare seeking mindset and more receptacle for CRC screening. Methods: This is a secondary data analysis of 2 intervention studies on CRC screening, Increasing Access to Colorectal Cancer Testing (I-ACT) and Colorectal Cancer Awareness, Research, Awareness, Research, Education and Screening (CARES). I-ACT is a study where participants (N=331), aged 50-75, were recruited in a community setting. and (N=416) for the clinical setting were aged 50-70. All participants were at average CRC risk, non-adherent to CRC screening guidelines, and enrolled in a randomized controlled trial to promote CRC screening. Participants completed a baseline questionnaire including demographic, cognitive, prior screening test completion, and two intention variables (i.e., intention to schedule any CRC test in the next six months and likelihood of completing any CRC test in the next six months). Cognitive variables included Preventive Health Model (PHM) constructs, medical mistrust, perceived discrimination, and cancer fatalism. Variables significantly correlated with each intention outcome (r ≥.10, p<.05) were entered into two separate multivariable logistic regression models. Results: Most participants in the community setting were African American [Native-born Black American] (93.4%) and had health insurance (56.8%). Participants intended to schedule any CRC screening test (52.3%), and reported some likelihood of completing a test in the next six months (69.8%). Only having health insurance (OR: 1.94, CI=1.24-3.03, p=.004) was associated with the intention to schedule a CRC screening test in the next six months. Having health insurance (OR: 2.89, CI=1.76-4.73, p<.001) and higher PHM cancer susceptibility (OR: 2.11, CI=1.27-3.48, p=.004) were associated with likelihood of completing a CRC screening test in the next six months for the community setting. In contrast, most of the participants recruited in a clinical setting were White (65.9%) and (28.1%) Black, and had health insurance (61.5%). Participants intended to schedule any CRC screening test (40.6%), and reported some likelihood of completing a test within the next six months (64.4%). Similar to the community setting, health insurance (OR: 1.93, CI=1.22-3.07, p=<.01) associated with the intention to schedule a CRC screening test in the next six months. Social influence (OR: 1.08, CI=1.02-1.12, p=.01) was also associated in the clinical setting. Having health insurance (OR: 1.80, CI=1.14-2.82, p=.01) and social influence ((OR: 1.08, CI=1.02-1.15, p=.01) were associated with the likelihood of completing a CRC screening test in the next six months. My hypothesis was not supported, because the participants from the community setting had greater intentions and likelihood to get screened for CRC within 6 months. These analyses suggest that the setting of the study does not affect the likelihood and intentions of individuals being screened for CRC. Conclusions: After adjusting for other demographic or cognitive variables in the multivariable logistic regression model, having health insurance was independently positively associated with intentions to complete CRC screening in the next six months for both settings. However, increasing people’s feelings of cancer susceptibility and social influence may be important in shaping patients’ CRC screening intentions regardless of health insurance status. For the clinical setting, having health insurance and a higher PHM social influence were positively associated with both the intentions and likelihood for participants being screened for CRC within in the next six months. For the clinical setting, increasing social influence may be important in shaping the participants CRC screening intentions regardless of health insurance status. From this data analysis, the community setting has showed interest and intentions for being screened for CRC. Hence, in future studies for raising awareness for CRC screening should recruit in the community setting.
Funder Acknowledgement(s): The study was funded by 1U54 CA153509 from the Center toReduce Cancer Health Disparities at the National Cancer Institute (PIs: C.K. Gwede and C.D. Meade) RSGT-11- 012-01- CPPB from the American Cancer Society (PI: C.K. Gwede).
Faculty Advisor: Dr. Clement Gwede, firstname.lastname@example.org
Role: For this research project, I completed the secondary analysis for the two intervention studies, CARES and I-ACT. I also entered the variables that were significant into two separate multivariable logistic regression models.