Background <p>This study aimed to understand the preferences of a sample of younger women (30–39 years) for the attributes of models of service delivery for a breast cancer risk-prediction service to identify how best to design a service to optimise uptake.</p> Methods <p>A discrete choice experiment was used to quantify the preferences of a purposive sample of younger women (aged 30–39) without prior knowledge of their risk of developing breast cancer. Respondents chose from a series of questions including two unlabelled alternatives, representing different models of a risk-prediction service, and an opt-out alternative. Data were analysed using random parameter logit and latent class models to explore potential heterogeneity in preferences for the intervention.</p> Results <p>The predicted uptake for a risk-prediction service ranged from 77 to 89%. Participants preferred a service with more flexible appointments which could be booked by the individual themselves. Latent class analysis suggested that around 7% of women would never have their risk predicted and for approximately 30% of women the choice would depend on the design of the service.</p> Conclusion <p>Younger women would be likely to choose to have their breast cancer risk predicted, although some groups were sensitive to the design of the prediction service.</p>

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Understanding the preferences of younger women for the delivery of a service to predict breast cancer risk: a discrete choice experiment

  • Stuart J. Wright,
  • Shabnam Thapa,
  • Amber Salisbury,
  • Sarah Hindmarch,
  • David P. French,
  • Sacha J. Howell,
  • Katherine Payne

摘要

Background

This study aimed to understand the preferences of a sample of younger women (30–39 years) for the attributes of models of service delivery for a breast cancer risk-prediction service to identify how best to design a service to optimise uptake.

Methods

A discrete choice experiment was used to quantify the preferences of a purposive sample of younger women (aged 30–39) without prior knowledge of their risk of developing breast cancer. Respondents chose from a series of questions including two unlabelled alternatives, representing different models of a risk-prediction service, and an opt-out alternative. Data were analysed using random parameter logit and latent class models to explore potential heterogeneity in preferences for the intervention.

Results

The predicted uptake for a risk-prediction service ranged from 77 to 89%. Participants preferred a service with more flexible appointments which could be booked by the individual themselves. Latent class analysis suggested that around 7% of women would never have their risk predicted and for approximately 30% of women the choice would depend on the design of the service.

Conclusion

Younger women would be likely to choose to have their breast cancer risk predicted, although some groups were sensitive to the design of the prediction service.