Women’s preferences for cervical cancer screening methods: a discrete choice experiment in Estonia and France
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: This study explores women’s preferences for cervical cancer screening (CCS) in Estonia and France, particularly preferences for self-sampling (SS). Although many European countries have introduced organized CCS, screening behaviours still exhibit a strong social gradient, with CC disproportionately affecting populations facing barriers to access, such as low income, rural residence, migration status or low education. The WHO has set a goal of eliminating CC and has proposed different strategies of invitations, outreach campaigns and the introduction of SS as a potential lever to increase uptake. METHODS: To assess whether these CCS strategies align with women’s preferences, we conducted a discrete choice experiment (DCE) in Estonia and France. Pooling our data (N = 4774), we used a two-stage decision-making framework; first, intervention preferences were assessed, and then the willingness to participate if preferred interventions were implemented was measured. We also conducted a heterogeneity analysis via latent class analysis. The DCE has three attributes: invitation methods, sampling methods (physician-based sampling or self-sampling), and awareness-raising campaigns. The results were analysed using a mixed multinomial logit model to capture heterogeneity in preferences and explore factors influencing CCS participation. RESULTS: The results show that the implementation of SS would: 1) increase uptake among women facing geographical barriers to CCS, 2) help engage first-time screeners in a screening pathway and 3) possibly deter participation from women already engaged in their screening pathway if implemented as sole mean of screening. CONCLUSIONS: Our results thus advocate for tailored screening programs.
Source: BMC Women s Health
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,890
Funder: Horizon 2020 Framework Programme
Award: G4746943544
OpenAlex ID: W7155046069
