Developing a computer touch-screen interactive colorectal screening decision aid for a low-literacy African American population: lessons learned

Health Promot Pract. 2013 Jul;14(4):589-98. doi: 10.1177/1524839912463394. Epub 2012 Nov 6.

Abstract

African Americans have higher colorectal cancer (CRC) mortality than White Americans and yet have lower rates of CRC screening. Increased screening aids in early detection and higher survival rates. Coupled with low literacy rates, the burden of CRC morbidity and mortality is exacerbated in this population, making it important to develop culturally and literacy appropriate aids to help low-literacy African Americans make informed decisions about CRC screening. This article outlines the development of a low-literacy computer touch-screen colonoscopy decision aid using an innovative marketing method called perceptual mapping and message vector modeling. This method was used to mathematically model key messages for the decision aid, which were then used to modify an existing CRC screening tutorial with different messages. The final tutorial was delivered through computer touch-screen technology to increase access and ease of use for participants. Testing showed users were not only more comfortable with the touch-screen technology but were also significantly more willing to have a colonoscopy compared with a "usual care group." Results confirm the importance of including participants in planning and that the use of these innovative mapping and message design methods can lead to significant CRC screening attitude change.

Keywords: colonoscopy; colorectal cancer (CRC); computer touch-screen; perceptual mapping; screening.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Black or African American*
  • Colonoscopy
  • Colorectal Neoplasms / diagnosis
  • Colorectal Neoplasms / ethnology*
  • Colorectal Neoplasms / psychology
  • Computers*
  • Decision Support Techniques*
  • Early Detection of Cancer / methods*
  • Educational Status
  • Female
  • Health Knowledge, Attitudes, Practice
  • Humans
  • Male
  • Middle Aged
  • User-Computer Interface*