Co-design of Lifestyle6, a digital tool targeting multiple health behaviour changes for cancer risk reduction and early detection support

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Abstract

Up to 40% of all cancers diagnosed could be prevented through the uptake of healthy lifestyle behaviours. This paper describes the co-design of a novel community-centric digital programme for cancer prevention and early detection support. Twenty-two community panel members partook in a series (i.e., three group-based sessions followed by one individual session) of iterative online workshops to co-design the programme. Based on established Design Thinking principles, the workshops aimed to i) identify barriers to access and use of existing cancer prevention information and support, ii) explore consumers’ needs and preferences for information and support related to cancer risk reduction and early detection, iii) generate ideas for a digital solution to address those, and iv) seek panel members’ feedback on a digital prototype developed in line with the insights from previous stages. The key barriers to accessing cancer prevention and screening support identified by the panel included limited availability and knowledge of cancer-specific resources alongside a paradoxical information overload regarding generic options. Panel members expressed concerns about information accuracy and relevance, while time constraints, financial limitations, and motivation deficits further impeded resource engagement. Regarding prototype preferences, participants prioritised accessibility, diversity, communication and connectedness, usability, and personal relevance as essential design elements. Digital solutions for cancer prevention and screening support should offer a customised experience, while catering for varying practical constraints and motivational challenges.

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APA

Murawski, B., Collins, K. E., Viljoen, B., Pearse, E. C., Vicario, J., Stiller, A., … Goodwin, B. (2026). Co-design of Lifestyle6, a digital tool targeting multiple health behaviour changes for cancer risk reduction and early detection support. PLOS ONE, 21(4 April). https://doi.org/10.1371/journal.pone.0347311

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