Monday, October 19, 2015: 2:00 PM
Grand Ballroom B (Hyatt Regency St. Louis at the Arch)

Caroline Vass, BSc, MSc1, Dan Rigby, BSc, MSc, PhD2, Stephen Campbell, BA, MA, PhD3 and Katherine Payne, BPharm, MSc, PhD1, (1)Manchester Centre for Health Economics, The University of Manchester, Manchester, United Kingdom, (2)Department of Economics, The University of Manchester, Manchester, United Kingdom, (3)Centre for Primary Care, The University of Manchester, Manchester, United Kingdom
Purpose: To understand if, and how, the framing of risk in a discrete choice experiment (DCE) affects preferences for a national breast screening programme (NBSP).

Method: An online DCE was designed and piloted (n=124) to elicit the preferences of female members of the public (recruited via an internet panel provider) for a NBSP described by two risk attributes (probability of detecting a cancer and risk of unnecessary follow-up per 100 women screened) and a cost attribute (out-of-pocket expense). Two survey versions presented the risk attributes as: (A) percentage only or (B) percentage and an icon array. The unlabelled DCE was blocked into two surveys, each containing 11 sets of choices between two screening programmes and an opt-out. The design, generated using Ngene, included an internal validity test through the inclusion of a dominant choice set. The DCE data were analysed using heteroskedastic conditional logit (HCLM) and scale-adjusted latent class (SALC) models.

Result: 1007 women (version A =501; B=506) completed the DCE. The results of the HCLM suggested that all attribute coefficients, but no two-way interactions, were significant and had the expected signs. Interactions of attributes with risk framing version were not significant and the risk framing version had no significant impact on the scale parameter. SALC analysis revealed heterogeneity in preferences, with five latent classes and three scale classes providing the best fit. The class probabilities indicate 84% of respondents were members of three large classes where all scale-adjusted attribute coefficients were significant: 31% in class 1 (probability of detecting a cancer most important), 27% in class 2 (cost of screening most important), 25% in class 3 (risk of unnecessary follow-up most important). The remaining 17% were split between classes 4 (9%) and 5 (8%). Class 1 members tended to be aware and concerned about their risk of breast cancer. Class 2 members were less likely to be older (over 50). Class 3 individuals tended to be younger (25-34) and have experience of cancer in their family. Risk framing version was not a predictor of class membership.

Conclusion: This study found the framing of risk attributes did not impact respondents’ choices in a DCE. However, other sources of heterogeneity were found in women’s preferences for the balance between the risks and benefits of a NBSP.