ReviewWhat are effective strategies to communicate cardiovascular risk information to patients? A systematic review
Introduction
Although it is possible to quantitatively predict the risk of heart disease with increasing precision, such as Framingham, SCORE and QRISK2 [1], [2], [3], much less is known about how to make use of the risk prediction and how to portray and communicate the risk, in ways which motivate people to reduce their risk by modifiable factors. This paper reports a systematic review of studies which have compared different ways of communicating cardiovascular risk to patients.
There are various ways statistical risk information can be communicated to patients. Numerical expressions include percentages, natural frequencies and numbers needed to treat [4], [5]. Graphical representations can also be used. These include bar graphs and pictograms or icon arrays [6]. The effects of risk presentation on patients’ have been described previously [7], [8], [9], [10]. For example, understanding, perceptions and behaviour are sensitive to the way the risk information is formatted and framed [11], [12], [13], [14]. There is a call for this risk information to be presented in a simple and balanced way. Also, there is an emerging consensus that it is important to communicate risk appropriately and effectively, as poor representation of statistical information may result in sub-optimal choices and treatment [4], [5], [11]. We are not aware of any literature reviews that have focused on the effect of presentation formats for communicating cardiovascular risk to patients.
The communication of cardiovascular risk is particularly complex for a number of reasons. Firstly, there are multiple factors, such as age, cholesterol levels and smoking status that contribute to cardiovascular disease (CVD); with at least 80% of CVD, stroke and type 2 diabetes attributable to the existence of modifiable risk factors such as a poor diet, lack of physical activity and tobacco use [15].
Secondly, extended time horizons need to be considered. Heart disease is an insidious process and reducing its risk is work that has to be carried out over many decades, including multiple changes to lifestyle [16]. The optimum time to reduce risk is when aged in the early 20 s and certainly in the 30 s [17]. However, most risk calculations are done much later and the methods almost always assume that the issue of risk is addressed in later life. For example, CVD risk calculations usually present anticipated risk over the coming 10 years and are highly dependent on age as a variable. Age is the single strongest risk factor for future cardiovascular events, but by emphasising the impact of ageing in risk prediction models, modifiable risk factors, such as blood pressure are underemphasised [18].
Lastly, patients find CVD an abstract concept, they have difficulty interpreting personal candidacy for it and consider it a ‘sneaky disease’ [19]. Patients’ understanding of how CVD risk is made up is generally poor and insufficient; the risk presented in prediction tools is often misunderstood, which can lead to unrealistic perceptions [20]. Misperceptions occur when the perceived risk does not correspond with actual risk; this can be an under-estimation (incorrect optimism or optimistic bias) or over-estimation (incorrect pessimism) [21], [22]. In aggregate, then, CVD risk communication strategies need to help individuals better understand the multiplicity of risk factors and the contribution of ageing to future risk; as well as being able to promote perceptions of risk, in order to motivate behaviour change and for informed decisions to be made regarding cardiovascular health. A previous systematic review [23] on the effects of presenting coronary risk information has recently been conducted. It concluded that coronary risk information can improve accuracy of risk perceptions and increase intention to initiate prevention strategies. However, it did not focus on the differing forms that risk information can take.
The aim of this review was to compare the effectiveness of different interventions used to communicate cardiovascular risk and assess the impact of the formats used in these interventions, on patient related outcomes such as understanding, affect, intention to modify behaviour and reduction in actual risk.
Section snippets
Data sources and search strategy
Systematic searches of six electronic databases: ASSIA, EMBASE, MEDLINE, CINAHL, PsycINFO and Science Citation Index Expanded were conducted from January 1980 up to November 2008. Comprehensive search strategies (aiming for high recall, low precision) were adapted from Cochrane Heart Filter mesh terms. The search strategy included subject heading and keyword searching. Terms (such as cardiovascular disease; heart disease; risk communication; risk assessment) were combined. Searches were adapted
Included studies
Fig. 1 summarises the study selection and extraction process. 56 full papers were retrieved for further assessment and 29 were excluded. Of the 27 studies included for detailed data extraction, four were subsequently excluded because they only varied the degree of risk rather than the presentation or communication of risk formats [26], [27], [28], [29]. Another five were excluded because the risk communication elements were embedded in a decision aid that had other components, and therefore,
Discussion
This review demonstrates that compared to the intensive and ongoing investment in the calculation of cardiovascular risk estimates, there is a poverty of research on how to convey these estimates in a meaningful way, so as to motivate people to modify their risk of developing heart disease. We had broad inclusion criteria, yet only found 15 studies, 11 of which were analogue studies and only 4 studies which dealt with the presentation of actual risk to patients. The methodological quality of
Conclusion
This review demonstrates a lack of well-designed studies in cardiovascular risk communication. This has been due to a combination of diverse methodological quality and contradictory results. It is likely that the heterogeneity of study characteristics, such as the design, sample and type of cardiovascular risk presented have contributed to this. A wide range of outcomes have been measured and there has been little consistency in risk presentation formats used, therefore, it is difficult to draw
Acknowledgements
This study was funded by EPA Cardio and the Bertelsmann Foundation. The authors would like to thank Adrian Edwards, Professor of General Practice at Cardiff University; Julian Halcox, Professor of Cardiology at Cardiff University; and Fiona Morgan from the Support Unit for Research Evidence at Cardiff University, for their help and guidance.
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