Tailoring visual communication of cardiovascular disease risk to diverse populations: supporting informed decision-making in primary care

Background: Cardiovascular disease (CVD) is the leading cause of global morbidity and mortality, with higher burden among socioeconomically disadvantaged populations. Risk prediction models embedded within patient decision aids aim to support informed decision-making in primary prevention. However, clinical tools use varied graphic formats with little consistency, and evidence on which visual formats best support comprehension and decision-making remain inconclusive due to substantial heterogeneity in study designs and outcome measures. Aim: This thesis aims to advance understanding of how visual – specifically graphic – communication of cardiovascular disease risk can support equitable informed decision-making in primary prevention. Methods: One conceptual and three empirical projects were conducted. First, a conceptual framework and taxonomies were developed for communicating health risks, addressing five domains: who (communicators), how (visual formats, design features), what (risk context and representation), why (outcome categories), and to whom (recipient characteristics). Second, a systematic review synthesised 53 studies (17,591 participants) on graphic communication of CVD and cancer risk, examining nine visual formats across five outcome categories. Third, qualitative interviews employing user-centred iterative design explored how diverse populations in Australia and the UK, including non-English speakers and economically deprived individuals, perceived multiple graphic formats. Fourth, a factorial randomised survey (n=2,333) evaluated graph types on informed decision-making, comprehension, and behavioural outcomes. Results: The systematic review found no single format universally optimal; bar graphs showed advantage over text for comprehension, and anthropometric iconography with red-amber-green colour schemes supported understanding, particularly for low numeracy individuals. The qualitative study demonstrated that everyday familiarity of gauges and colour-coded schemes supported intuitive understanding; iconography effectiveness varied by size and quantity; triple pie charts best supported non-English speakers. The survey confirmed graph type influences informed decision-making, attributable primarily to improvements in understanding of risks. Numerator-framed graphs (bar charts, gauges, risk ladders, visual analogue scales) better supported understanding than pie charts. Risk trajectory formats hindered understanding due to complexity. Risk numeracy and graph literacy represent distinct competencies. Conclusion: Graphic communication of CVD risks impacts decision-making, driven by improvements in understanding. Bar charts and gauges with red-amber-green colour schemes and clear numeric labels best support understanding and informed decision-making. No single format is optimal; strategic pairing of complementary formats and tailoring to recipient characteristics may optimise understanding while avoiding cognitive overload. Clinical risk prediction tools should adopt evidence-based graphic designs to support equitable informed decision-making in primary prevention.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2026

Author dc:creator

• Taylor, Owen Alexander

Advisors dc:contributor.advisor

• Dennison, Rebecca
• Wood, Angela Mary

• cardiovascular disease
• health risk communication
• informed decision-making
• primary prevention
• risk communication

Licence

• https://www.repository.cam.ac.uk/bitstreams/973f36a8-1ee3-46e8-9593-abccb34a4c7d/download
• http://purl.org/NET/rdflicense/allrightsreserved

Language dc:language

eng

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.131982

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/405857