In the first article in this series we looked at the dimension of risk. Expression of risk in terms of an unwanted outcome or event can be described with descriptions or distinctions based on both its quality or on its quantity. The probability can be described in qualitative terms such as rare or infrequent or expressed quantitatively such as 1 in 1000. What is important to acknowledge that patients differ in what they like.

For example, in the context of a study on an invasive diagnostic procedure, 467 patients varied in terms of the way the risk was told to them: 43 % preferred qualitative (verbal expressions) disclosure of information vs. 36% preferring quantitative. The exact number varies form study to study, but roughly it is about half and half for each type of disclosure. In terms of influenza vaccines for children, slightly more parents preferred quantitative information (60%). It is often interesting how we come to decisions without knowing the basic quantitative risk. For instance, ask yourself the question: What is the risk of death from swine flu compared to seasonal flu? Qualitative descriptions are often foremost in our minds and very few will be able to give quantitative information. To be honest, I think I’ve shot myself in the foot as I don’t know the answer to this question myself. But, my premise is correct, as words like rare and infrequent are what come to my mind.

The most useful strategy identified in a systematic review of effective formats for communicating probabilistic information, including 15 randomized controlled trials found for both written and verbal information, patients have a more accurate perception of risk if probabilistic information is presented as numbers rather than words. That means that it is all right to say words like rare or infrequent but without a quantitative number such as 1 in a million people find it difficult to correctly perceive the actual probability.

How to present qualitative information

Qualitative descriptions are appealing because they use common words that seem to be generally well understood. However, qualitative words, of which there are many, have no generally accepted anchoring at specific quantitative levels of frequency, despite efforts to promote such anchoring.

Data about actions sometimes bear little relation to the statistics. Saxe found no connection between the probabilities provided to couples during genetic counselling and the decisions they made. The use of verbal categories with scales of risk, such as very unlikely, was easier to use and represented better their true feelings.

Proposals have been made to standardise the language of risk with standardised terms for specified frequencies ("high" for risks 1 in less than 100 and "moderate" for between 1 in 100 and 1 in 1000). However, it’s all in the interpretation and patients would probably not understand such standardised terms consistently.

There are a number of simple recommendations worth incorporating based on this article:
In describing risk choose either:

1) numeric probabilities, or
2) numeric and qualitative information together

Qualitative descriptions should use common words that seem to be generally understood.

Next time you are met with a risk, whether presenting or reading about another scare story in the media, you might want to consider whether some of these issues outlined have been met. They probably won’t have.

In 1980 Richard Peto explained to ordinary people the quantitative dangers of smoking:

“Among an average 1000 young men who smoke cigarettes regularly – about one will be murdered, about six will be killed on the roads, and about 250 will be killed before their time by tobacco.”

There are many good attributes to this explanation that can be followed when trying to communicate risk. The concept of risk acknowledges every course of action or inaction in clinical care may be associated with risks and/or benefits. Risk can be thought of as an unwanted outcome or as an uncertainty about the occurrence of that outcome. In defining risk we therefore can think of it as either an unwanted outcome and/or the probability of that unwanted outcome occurring.

Bogardus’ work highlights risk has five basic fundamental dimensions, and understanding these dimensions may help when trying to communicate risk more effectively:

1. Identity: Some risks may not even be known about and sometimes it may be hard to quantify whether the exposure is a risk or a benefit.
2. Permanence: Requires an understanding whether the risk is temporary or permanent and how long it will occur for. For example, if you have some numbness after a hip operation the question you want answered is: How long will it last for? Or, if I do get numbness, is it permanent?
3. Timing: When will the risk occur, does it occur early compared to late after a procedure - does an infection after an operation occur early just after the operation or later, like when I have left hospital?
4. Probability: Will it occur in all patients, how likely is it? If I get it once will I get it all the time?
5. Value: How important is the risk to the patient given his current ideals and lifestyle?

Ultimately what we want to know is "What is the best way to communicate to patients the chances of a ‘bad’ event occurring?" Although this is not exclusive to patients, we face risks every day about which we want better and more informed communication. For instance, as a parent you make decisions daily about what your children may or may not do based on risks about which we often want better information. In pondering why the uptake of the current swine flu vaccine is proving so controversial, does the current debate provide adequate information on the benefits and risks?

When deciding about the pros and cons of a given risk the fifth and perhaps most important dimension of risk is therefore its value, its subjective “badness”. Some people, no matter how small the risk – for example flying – may perceive the subjective badness to be so impelling that no matter how well you communicate the quantitative aspects of the risk, which are incredibly small when it comes to flying, they still won’t fly. Although, most clinicians make amiable attempts to quantify the amount of risk, the ultimate determination of importance is its level of subjectiveness. In effect the first four dimensions of risk identity, permanence, timing, and probability are there to help determine our own personal value to be associated with the risk. These dimensions should be thought of at the outset when communicating risk whether verbal or written.

The next time you see an article outlining risk see to what extent the dimensions have been incorporated into the communication, and in the next articles on this series we will consider the expression of risk, both qualitatively and quantitatively.

It is often hard to figure out the findings of health research because of jargon and the numbers. However, I reckon most of that research can be understood by anybody with 4 simple concepts. I am going to cover one of these concepts each day using stories from this week’s press relating to health to show how often these numbers appear in the press. Hopefully these 4 keys will allow more people to open the door and to question the numbers we read about in health research.

LESSON 1: CLINICAL SIGNIFICANCE IS ALL ABOUT RISK

For over 2000 years, two principles have formed the basis of medical practice: “primum non nocere” (first do no harm) and “succurrere” (do good). If we want to measure “the good” or “the harm” associated with a treatment or an exposure, we have to know how it changes the chance or risk of a disease compared to another treatment or exposure. Chance or risk is usually expressed as a percentage, and tells us about the number of people who develop a disease out of a population.

In absolute terms, this change is simply the difference between the risk associated with the first, or control, treatment and the risk associated with the new treatment. This difference is sometimes called the absolute risk difference. In relative terms, this same change can be expressed as the risk associated with the new treatment divided by the risk associated with the control treatment, known as the relative risk.

In this week’s British Medical Journal, Dutch researchers looked at whether 15 minutes of immobilisation increased the chance of successful pregnancy after artificial insemination . 199 couples received the new treatment (15 minutes immobilisation) and 192 couples had standard treatment (they were allowed to mobilise immediately after insemination- the control group). In the immobilisation group, 54 couples had pregnancies. Therefore the chance or risk of pregnancy was 54/199= 27% in this group. In the control group, 34 out of 192 couples had pregnancies, and so the risk of pregnancy was 34/192=18%.

The absolute risk difference is 27%-18%=9%. In other words, immobilisation increased the risk of pregnancy by 9%, compared with controls. Put another way, the relative risk was 27/18=1.5. This means that compared to standard practice, immobilisation leads to a 50% increased chance of pregnancy after insemination. You might have spotted that a 50% increase sounds a lot more impressive than a 9% increase! Therefore, scientists should either report both absolute and relative risks, so that we can understand the size of the risk, or report absolute risk because it is more useful. As readers, we should also look for these numbers before making any conclusions about harm and good. The terms, “hazard” and “odds” are sometimes used in research, but they are just slightly different measures of chance. The message is still the same: absolute changes caused by a treatment are often smaller than the relative changes.

Lesson 2