Effects of a risk-based online mammography intervention on accuracy of perceived risk and mammography intentions

Abstract

Objective This experiment tested the effects of an individualized risk-based online mammography decision intervention. The intervention employs exemplification theory and the Elaboration Likelihood Model of persuasion to improve the match between breast cancer risk and mammography intentions. Methods 2,918 women ages 35-49 were stratified into two levels of 10-year breast cancer risk (< 1.5%; ≥ 1.5%) then randomly assigned to one of eight conditions: two comparison conditions and six risk-based intervention conditions that varied according to a 2 (amount of content: brief vs. extended) × 3 (format: expository vs. untailored exemplar [example case] vs. tailored exemplar) design. Outcomes included mammography intentions and accuracy of perceived breast cancer risk. Results Risk-based intervention conditions improved the match between objective risk estimates and perceived risk, especially for high-numeracy women with a 10-year breast cancer risk <1.5%. For women with a risk < 1.5%, exemplars improved accuracy of perceived risk and all risk-based interventions increased intentions to wait until age 50 to screen. Conclusion A risk-based mammography intervention improved accuracy of perceived risk and the match between objective risk estimates and mammography intentions. Practice Implications Interventions could be applied in online or clinical settings to help women understand risk and make mammography decisions.

Effect of interventions including provision of personalised cancer risk information on accuracy of risk perception and psychological responses: A systematic review and meta-analysis

“…The observed discrepancy between the risk estimate and perceived risks may also reflect varying levels of numeracy and the difficulties people often have understanding risk information [53,54]. This is supported by the finding in this review that among women with an estimated risk <1.5%, those with high numeracy had greater increases in accuracy than those with low numeracy [36]. Numerical misunderstanding was also given as a reason for feeling that their risk was higher or lower by women who recalled their risk estimate correctly but gave a different response when asked about their perceived risk in the study by Lipkus et al [32].…”

“…In that study, Emmons et al showed that those who were randomised to have the opportunity to see how adopting or changing any of the risk factors would impact on their total risk profile had greater improvement in accuracy immediately post information for both comparative and absolute risk accuracy compared to those who did not [35]. A further study assessed the role of numeracy and found that among women with an estimated risk <1.5%, the degree to which participants overestimated their risk was moderated by numeracy, with women with high numeracy having greater increases in accuracy than women with low numeracy [36]. No significant moderation effects were seen for women with an estimated risk ≥1.5%.…”

Effect of interventions incorporating personalised cancer risk information on intentions and behaviour: a systematic review and meta-analysis of randomised controlled trials

“…The two studies reporting an effect were by Lipkus and Klein 30 and Seitz et al . 37 In Lipkus and Klein, intention to complete an FOBT that would be given to them within the following month was measured on a seven-point Likert scale. The intentions reported by participants who received absolute risk (mean 3.65, n = 40) or absolute plus either low (mean 6.43, n = 38) or high (mean 6.65, n = 39) comparative risk information were statistically significantly higher (P<0.05) than those participants in the control group who were provided with the same written information but without risk estimates (mean 2.21, n = 43).…”

Key Elements of Mammography Shared Decision-Making: a Scoping Review of the Literature

“…Sertz demonstrated in a RCT that the use of typical models or exemplars has been shown to increase accuracy of personal risk for breast cancer. 33 Women value grounding risk information into real-world examples and the connection of information to medical research for credibility. 25 Research has also identified specific language that is more favorable for discussing breast cancer risk factors.…”