Personalised risk communication for informed decision making about taking screening tests.
BACKGROUND
There is a trend towards greater patient involvement in healthcare decisions. Adequate discussion of the risks and benefits associated with different choices is often required if involvement is to be genuine and effective. Achieving both the adequate involvement of consumers and informed decision making are now seen as important goals for any screening programme. Personalised risk estimates have been shown to be effective methods of risk communication in general, but the effectiveness of different strategies has not previously been examined.


OBJECTIVE
To assess the effects of different types of personalised risk communication for consumers making decisions about taking screening tests.


METHODS
We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library Issue 4, 2004), MEDLINE (1985 to December 2005), EMBASE (1985 to December 2005), CINAHL (1985 to December 2005), and PsycINFO (1989 to December 2005). Follow-up searches involved hand searching Preventive Medicine, citation searches on seven authors, and searching reference lists of articles. For the original version of this review (Edwards 2003c) we also searched CancerLit (1985 to 2001) and Science Citation Index Expanded (searched March 2002).


METHODS
Randomised controlled trials addressing the decision by consumers of whether or not to undergo screening, incorporating an intervention with a 'personalised risk communication element' and reporting cognitive, affective, or behavioural outcomes. A 'personalised risk communication element' is based on the individual's own risk factors for a condition (such as age or family history). It may be calculated from an individual's risk factors using formulae derived from epidemiological data, and presented as an absolute or relative risk or as a risk score, or it may be categorised into, for example, high, medium or low risk groups. It may be less detailed still, involving a listing, for example, of a consumer's risk factors as a focus for discussion and intervention.


METHODS
Two authors independently assessed each trial for quality and extracted data. We extracted data about the nature and setting of the intervention, and relevant outcome data, along with items relating to methodological quality. We then used standard statistical methods of the Consumers and Communication Review Group to combine data using MetaView, including analysis according to different levels of detail of personalised risk communication, different condition for screening, and studies based only on high risk participants rather than people at 'average' risk.


RESULTS
Twenty-two studies were included, nine of which were added in the 2006 update of this review. There was weak evidence, consistent with a small effect, that personalised risk communication (whether written, spoken or visually presented) increases uptake of screening tests (odds ratio (OR) 1.31 (random effects, 95% confidence interval (CI) 0.98 to 1.77). In three studies the interventions showed a trend towards more accurate risk perception (OR 1.65 (95% CI 0.96 to 2.81), and three other trials with heterogenous outcome measures showed improvements in knowledge with personalised risk interventions. There was little other evidence from these studies that the interventions promoted or achieved informed decision making by consumers about participation in screening. More detailed personalised risk communication may be associated with a smaller increase in uptake of tests. That is, for personalised risk communication which used and presented numerical calculations of risk, the OR for test uptake was 0.82 (95% CI 0.65 to 1.03). For risk estimates or calculations which were categorised into high, medium or low strata of risk, the OR was 1.42 (95% CI 1.07 to 1.89). For risk communication that simply listed personal risk factors the OR was 1.42 (95% CI 0.95 to 2.12). Over half of the included studies assessed interventions in the context of mammography. These studies showed similar effects to the overall dataset. The five studies examining risk communication in high risk individuals (individuals at higher risk due to, for example, a family history of breast cancer or other conditions) showed larger odds ratios for uptake of tests than the other studies (random effects OR 1.74; 95% CI 1.05 to 2.88). There were insufficient data from the included studies to report odds ratios on other key outcomes such as: intention to take tests, anxiety, satisfaction with decisions, decisional conflict, knowledge and resource use.


CONCLUSIONS
Personalised risk communication (as currently implemented in the included studies) may have a small effect on increasing uptake of screening tests, and there is only limited evidence that the interventions have promoted or achieved informed decision making by consumers.
Edwards
A G K
AG
Cardiff University, Dept of General Practice, Centre for Health Services Research, 2nd Floor, Neuadd Meirionnydd, Heath Park, Cardiff, Wales, UK. edwardsag@cardiff.ac.uk
Evans
R
R
Dundon
J
J
Haigh
S
S
Hood
K
K
Elwyn
G J
GJ
D003142:Communication; D003256:Community Participation / Q000379:methods*; D003657:Decision Making; D006801:Humans; D008403:Mass Screening; D010353:Patient Education as Topic; D016032:Randomized Controlled Trials as Topic; D012306:Risk