Predicting Colorectal Cancer Screening among Adults Who Have Never Been Screened: Testing the Interaction between Message Framing and Tailored Risk Feedback.

Journal Article (Journal Article)

Providing adults tailored risk estimates of getting colorectal cancer (CRC) can increase screening. A concern is that receipt of lower risk estimates will demotivate screening; this effect may be curbed by matching level of risk with message framing. Theoretically, pairing lower risk estimates with gain-frame messages, and higher risk estimates with loss-frame messages, should increase screening and screening intentions more than pairing lower risk estimates with loss-frame messages/higher risk estimates with gain-frame messages. These effects may be mediated by how screening is construed (e.g., to find health problems vs. to reaffirm one is healthy). These predictions were tested experimentally among 560 men and women ages 50-75 who have never screened. Participants at baseline received online a tailored comparative risk estimate with gain- or loss-frame information on screening. Screening was assessed six months later. Among the 400 reached at six months, 9.5% reported screening. There were no main effects or interactions between risk feedback and framing predicting construals, screening intentions, or screening. Worry about getting CRC and screening intentions predicted screening. While hypothesized interactions were not found, future research should explore further mechanisms through which online interventions utilizing risk feedback and framing motivate screening among adults who have never screened.

Full Text

Duke Authors

Cited Authors

  • Lipkus, IM; Johnson, C; Amarasekara, S; Pan, W; Updegraff, JA

Published Date

  • January 2019

Published In

Volume / Issue

  • 24 / 3

Start / End Page

  • 262 - 270

PubMed ID

  • 30958101

Pubmed Central ID

  • PMC6852613

Electronic International Standard Serial Number (EISSN)

  • 1087-0415

International Standard Serial Number (ISSN)

  • 1081-0730

Digital Object Identifier (DOI)

  • 10.1080/10810730.2019.1597950


  • eng