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Using a behaviour-change approach to support uptake of population genomic screening and management options for breast or prostate cancer

European Journal of Human Genetics volume 33, pages 108–120 (2025)Cite this article

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Abstract

As the possibility of implementing population genomic screening programs for the risk of developing hereditary cancers in health systems increases, understanding how to support individuals who wish to have genomic screening is essential. This qualitative study aimed to link public perceived barriers to a) taking up the offer of population genomic screening for breast or prostate cancer risk and b) taking up risk-management options following their result, with possible theory-informed behaviour-change approaches that may support implementation. Ten focus groups were conducted with a total of 25 members of the Australian public to identify and then categorise barriers within the behaviour-change Capability, Opportunity, Motivation - Behaviour (COM-B) model. Ten COM-B categorised barriers were identified as perceived influences on an individual’s intentions to take-up the offer, including Capability (e.g., low public awareness), Opportunity (e.g., inconvenient sample collection procedure) and Motivation (e.g., genomic screening not perceived as relevant to an individual). Ten barriers for taking up risk-management options included Motivation (e.g., concerns about adverse health impact) and Opportunity (e.g., social opportunity and cost incurred to the individual). Our findings demonstrate that a nuanced approach is required to support people to take-up the offer of population genomic screening and, where appropriate, to adopt risk-management options. Even amongst participants who were enthusiastic about a population genomic screening program, needs were varied, demanding a range of implementation strategies. Promulgating equitable uptake of genomic screening and management options for breast and prostate cancer risk will require a needs-based approach.

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Fig. 1: Systematic approach to designing implementation strategies utilising the COM-B model.
Fig. 2: COM-B model and matrix.

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Data availability

The dataset generated and analysed during the current study can be made available from the corresponding author on reasonable request.

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Funding

The National Precision Health Research Translation for Breast and Prostate Cancer Prevention and Early Detection (INTREPID), is funded by the Australian Government’s National Health and Medical Research Council (NHMRC) Synergy Grants (GNT 2011329).

Author information

Authors and Affiliations

  1. Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia

    Zoe Fehlberg, Louise Fisher, Cun Liu & Ilias Goranitis

  2. Australian Genomics, Murdoch Children’s Research Institute, Melbourne, VIC, Australia

    Zoe Fehlberg, Ilias Goranitis & Stephanie Best

  3. Genomics in Society, Murdoch Children’s Research Institute, Melbourne, VIC, Australia

    Nathasha Kugenthiran

  4. Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia

    Roger L. Milne & Melissa C. Southey

  5. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia

    Roger L. Milne

  6. Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia

    Roger L. Milne & Melissa C. Southey

  7. Clinical Translation & Engagement, Garvan Institute of Medical Research, Sydney, NSW, Australia

    Mary-Anne Young & Amanda Willis

  8. School of Clinical Medicine, Faculty of Medicine and Health, University of NSW, Sydney, NSW, Australia

    Mary-Anne Young & Amanda Willis

  9. Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, Australia

    Melissa C. Southey

  10. The University of Melbourne, School of Health Sciences, Melbourne, VIC, Australia

    Stephanie Best

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Contributions

Conceptualisation: ZF, CL, IG, SB; Methodology: ZF, CL, LF, IG, SB; Investigation: ZF, LF, CL, MCS, IG, SB; Formal analysis: ZF, LF, CL, SB; Interpretation of the results: ZF, NK, RLM, M-AY, AW, MCS, SB. Writing-original draft: ZF, SB; Writing-review & editing: ZF, NK, RLM, M-AY, AW, MCS, SB. All authors approved the final version and agreed to be accountable for all aspects of the work.

Corresponding author

Correspondence to Stephanie Best.

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The authors declare no competing interests.

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Ethical approval was provided by The University of Melbourne (ID:2023-26030-42732-6). Participants provided consent via an online form following the opportunity to view participant information and consent material.

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Supplementary information

41431_2024_1729_MOESM1_ESM.docx

Supplementary Material 1: Focus Group Guide: consumer views on uptake of population genomics risk screening for breast and prostate cancer

Supplementary Material 2: COM-B model coding guide with definition in literature and definition in context.

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Fehlberg, Z., Fisher, L., Liu, C. et al. Using a behaviour-change approach to support uptake of population genomic screening and management options for breast or prostate cancer. Eur J Hum Genet 33, 108–120 (2025). https://doi.org/10.1038/s41431-024-01729-1

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