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What Factors Influence Non-Participation Most in Colorectal Cancer Screening? A Discrete Choice Experiment

Author

Listed:
  • Esther W. Bekker-Grob

    (Erasmus University Rotterdam
    Erasmus University)

  • Bas Donkers

    (Erasmus University
    Erasmus University)

  • Jorien Veldwijk

    (Erasmus University Rotterdam
    Erasmus University)

  • Marcel F. Jonker

    (Erasmus University Rotterdam
    Erasmus University)

  • Sylvia Buis

    (Gezondheidscentrum Ommoord)

  • Jan Huisman

    (Het Doktershuis)

  • Patrick Bindels

    (Erasmus MC-University Medical Centre Rotterdam)

Abstract

Background and Objective Non-participation in colorectal cancer (CRC) screening needs to be decreased to achieve its full potential as a public health strategy. To facilitate successful implementation of CRC screening towards unscreened individuals, this study aimed to quantify the impact of screening and individual characteristics on non-participation in CRC screening. Methods An online discrete choice experiment partly based on qualitative research was used among 406 representatives of the Dutch general population aged 55–75 years. In the discrete choice experiment, respondents were offered a series of choices between CRC screening scenarios that differed on five characteristics: effectiveness of the faecal immunochemical screening test, risk of a false-negative outcome, test frequency, waiting time for faecal immunochemical screening test results and waiting time for a colonoscopy follow-up test. The discrete choice experiment data were analysed in a systematic manner using random-utility-maximisation choice processes with scale and/or preference heterogeneity (based on 15 individual characteristics) and/or random intercepts. Results Screening characteristics proved to influence non-participation in CRC screening (21.7–28.0% non-participation rate), but an individual’s characteristics had an even higher impact on CRC screening non-participation (8.4–75.5% non-participation rate); particularly the individual’s attitude towards CRC screening followed by whether the individual had participated in a cancer screening programme before, the decision style of the individual and the educational level of the individual. Our findings provided a high degree of confidence in the internal–external validity. Conclusions This study showed that although screening characteristics proved to influence non-participation in CRC screening, a respondent’s characteristics had a much higher impact on CRC screening non-participation. Policy makers and physicians can use our study insights to improve and tailor their communication plans regarding (CRC) screening for unscreened individuals.

Suggested Citation

  • Esther W. Bekker-Grob & Bas Donkers & Jorien Veldwijk & Marcel F. Jonker & Sylvia Buis & Jan Huisman & Patrick Bindels, 2021. "What Factors Influence Non-Participation Most in Colorectal Cancer Screening? A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(2), pages 269-281, March.
    • Handle: RePEc:spr:patien:v:14:y:2021:i:2:d:10.1007_s40271-020-00477-w
    DOI: 10.1007/s40271-020-00477-w
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    References listed on IDEAS

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    1. David Revelt and Kenneth Train., 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Economics Working Papers E00-274, University of California at Berkeley.
    2. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, November.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, November.
    4. Célia Berchi & Maximilien Nayaradou & Olivier Dejardin & Guy Launoy, 2010. "Eliciting population preferences for mass colorectal cancer screening organization," Post-Print halshs-00478487, HAL.
    5. Jordan J. Louviere & Towhidul Islam & Nada Wasi & Deborah Street & Leonie Burgess, 2008. "Designing Discrete Choice Experiments: Do Optimal Designs Come at a Price?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(2), pages 360-375, March.
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    Cited by:

    1. Swait, J. & de Bekker-Grob, E.W., 2022. "A discrete choice model implementing gist-based categorization of alternatives, with applications to patient preferences for cancer screening and treatment," Journal of Health Economics, Elsevier, vol. 85(C).
    2. Huls, Samare P.I. & de Bekker-Grob, Esther W., 2022. "Can healthcare choice be predicted using stated preference data? The role of model complexity in a discrete choice experiment about colorectal cancer screening," Social Science & Medicine, Elsevier, vol. 315(C).

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