Literacy and Knowledge, Attitudes, and Behavior About Colorectal Cancer Screening

ABSTRACT

This cross-sectional survey explored the association between functional health literacy and knowledge of, beliefs and attitudes about, and reported usage of colorectal cancer screening tests. The results indicate that functional health literacy, as assessed by the Short Test of Functional Health Literacy in Adults (STOFHLA), is not an independent predictor of colorectal cancer screening knowledge, beliefs, attitudes, or behavior. Latino ethnicity and education, however, often predicted screening responses, suggesting that efforts to improve communication about colorectal cancer screening with Latino patients and patients with low education clearly are needed to reduce the disparities in awareness and utilization of colorectal cancer screening tests. This study also explored influences on intended screening behavior. Physician recommendation was found to be a powerful motivator of intention to undergo colorectal cancer screening regardless of literacy level, indicating that interventions aimed at increasing physician recommendation of colorectal cancer screening may be an effective way of increasing screening rates.

The preliminary results of this study were presented in part at the National Meeting of the Society of General Internal Medicine, May 2, 2002, Atlanta, GA.

This study was supported by a Minority Supplement from the Agency for Health Care Quality and Research, Grant # R01 HS10299. The authors express their gratitude to the physicians who provided permission to contact their patients and collect the data for this study at their clinics: Dr. Bryan R. Hollinger, MD, MPH, Medical Director, Esperanza Health Clinic, Nuria Pajares, MD, of Temple University Community Health Center and the physicians of Maria De Los Santos Health Center and Norristown Regional Health Center.

Notes

*Based on χ² or Fisher exact test.

# Sex was not recorded for the first 26 interview.

The numbers do not add to equal n because of a small amount of missing data.

*Unadjusted (bivariate) analyses using χ²or Fisher exact test.

#Adjusted (multivariate) analyses using ethnicity, Medicaid status, insurance status, education, and income as covariates.

*Bivariate analyses based on χ² or Fisher exact test.