How People Respond to Risk James Neuberger

Facts are stubborn things but statistics are plastic (Mark Twain) Errors using inadequate data are much less than those not using data at all (Charles Babbage) 99% of all statistics only tell 49% of the story (Ron Delease) Politicians use statistics like some alcoholics use lampposts – more for support than for illumination (Andrew Lang)

Communication is a two way process Failure of communication is not the fault of just one person

GMC Guidance You must not make assumptions about a patient’s understanding of risk or the importance they attach to different outcomes You must tell patients if … a treatment might result in a serious adverse outcome, even if the likelihood is very small. You should also tell patients about less serious complications if they occur frequently An adverse outcome resulting in death, permanent or long term physical disability or disfigurement, medium or long-term pain… or other outcome with a long-term effect on a patient’s employment, social or personal life

People’s response to risk is variable Response to risk depends on many factors including Familiarity Control Personal experience (and other heuristics) Dread Emotional state of person (valence theory)

Common biases and heuristics (Kahneman and Tversky) Availability Events that can be more readily brought to mind considered more likely Representativeness Insensitivity to prior, size, Anchoring Adjust unknown on basis of known Asymmetry Different approaches to gains and losses, preferring certain gain over gamble with higher utility Threshold Different choices for similar gain

People’s response to risk is variable “I am going horse riding but won’t sit in row 13 on the bus” After 9/11, more people in US drove than flew, resulting in an estimated 1000 excess deaths “I will not eat beef (because of vCJD) but will continue to smoke”

Presentation Be aware that the order in which risks and benefits are presented may affect risk perceptions Be aware that comparative risk information is persuasive and not just informative Repeatedly draw attention to the time interval over which the risk occurs

From RCoA

NHS Booklet on Breast Screening

How to phrase the risk Framing is important Response to surgery There is a 90% chance that you will be alive 1 year after bypass surgery There is a 10% chance you will die from the surgery

so Data can be presented in many ways Avoid using % Avoid using terms like common or rare Put the figures in context 1 in 100 rather than 1% 1 person in a town like Warwick rather than 1 in 30000

Explaining risk 5% risk 1 in 20 chance 5 out of 100 people like you 5 out of 100 ways things may turn out for you

Be careful More information and information that is understandable to the patient is associated with a greater wariness to the treatment and tests Deaths rates of 1286 out of 10000 were rated as more risky than 24.14 out of 100

Other tips People’s biases Understanding of figures ‘Now that I know of confirmation bias, I see examples all around me’ (Jon Ronson) Understanding of figures Many people think a risk of 1:25 is greater than 4:100 Those people tend to be less interested in shared-care / informed-choice Many suggest written information should aim for those with a reading age of 8-10

The micromort: unit of risk (Spiegelhalter) A 1 in 1000000 chance of sudden death

Conclusions Use plain language Present data using absolute risks and frequencies Consider use of images such as pictographs Consider use tables that include tables summarising all benefits and risks Consider using incremental formats where appropriate Consider presenting information that is most critical for decision making at the expense of completeness

References and thanks Fagerlin A, et al. JNCI 2011 Edwards et al, BMJ 2002 Yamagishi Appl Cog Psyhcol 1997 Galesic Health Psychology 2011 Sir David Spiegelhalter Prof Chris Watson NHSBT Alex Hudson Dr Matthew Robb