A. Introduction

Risk homeostasis is a controversial theory. It suggests that individuals have an implicit, preferred or target level of risk. One consequence of this theorem is that any safety improvements that reduce the risk exposure of an indiviudual will potentially lower the perceived threat below the target level. This creates the opportunity for people to alter their behaviour. In particular, they may trade performance objectives for a slightly increased level of risk. For example, car drivers that have access to advanced braking systems and other protection mechanisms may drive faster and brake later than drivers whose cars do not offer this higher degree of protection. Many people disagree with the basic ideas behind risk homeostasis theory. Does anyone really have an implicit target level of risk? Is anyone calculating enough to identify performance benefits that can be precisely traded off against safety improvements? Your task is to select an appropriate analytical technique to gather evidence about this theory. Gerald Wilde provides an on-line introduction to Risk Homeostasis. Be aware, however, that there are different perspectives on this issue and that you should also read more widely about the subject.

B. Your Task

C. Methodologies for Examining Risk Homeostasis

There are many different ways in which you can provide or disprove assertions about risk homeostasis theory. These are summarised in the following paragraphs:

• Experimental techniques. A number of objections can be made about the use of experimental techniques to examine issues in risk and decision making. In particular, expressed preferences in the laboratory may provide poor predictions of individual behaviour in the `real world'. However, many researchers have simulated situations in which people make `risky' decisions under laboratory conditions. These laboratory experiments are used to provide insights into elements of risk homeostasis theory. In order for these experiments to be valid you must consider the experimental design, including issues such as dentifying dependent and independent variables, counterbalancing etc. You must also choose an appropriate statistical test with which to analyse any results that you might obtain. Some of these issues are mentioned in Chapter 9 of Wilde's book but you will also have to read more widely into experimental design. For example, there is an introduction to experimental design at William Trochim's site at Cornell and another by Paul Cohen at Colorado State In particular, you should note that Chapter 9 of Wilde's book covers the ways in which primitive (and more advanced) forms of computer games are commonly used to examine risk homeostasis theory. One way in which you could actively extend research in this area would be to write a computer game to test risk homeostasis theory under laboratory conditions. Do NOT simply copy the games in the Wilde book.

• Epidemiological techniques. One way of finding evidence for and against risk homeostasis is to gather data about incidents and accidents before and after some safety innovation is introduced. For example, if cycle helmests are made compulsory then we can look to see what impact that has on injuries to cyclists who wear these hats. Problems arise in trying to interpret the statistics. If injuries rise does this support the homeostasis theory and show that cyclists misjudge their target level of risk, In other words, they do more dangerous things beyond the benefits provided by a helmet. Alternatively, we might see that they types of injuries changes. The helmets have the effect of increasing the frequency of incidents because cyclists ride more recklessly but that the outcomes are less severe because the helmets intervene to prevent head injuries. In any event, if you choose the epidiemiological approach you must find a NEW data soure General pointers to this data are available via OSHA, the HSE and other regulatory organisations via the links page. Gerald Wilde's book has several examples of this approach being applied to safety data, especially Chapter 5.

• Other approaches. This assessment is deliberately open-ended. It is intended to provide scope for individual initiative and research. I would strongly encourage any other ideas about techniques that might be used in this open assessment. However, I would also urge you to email me or discuss them after a lecture to ensure that they will provide credible evidence about risk homeostasis.

D. Transferable Skills

E. Assessment Criteria and Submission Details

This exercise is degree assessed. It contributes 30% to the total marks associated with this course. The body of the report should not exceed fifteen A4 pages. The report must be printed out and must be submitted in a secure binder (i.e., one that will keep the pages together and in the correct order). It must include:

1. A title page containing your student as well as your contact details (email address etc);
   
2. A table of contents and appropriate page numbers;
   
3. A section on the methodology that you used. This should begin with a statement of the hypothesis that you chose to prove or disprove. Please note that your project might look only at a specific aspect of risk homeostasis, such as the existinace of implicit risk targets rather than behaviour changes. This should include some consideration of alternative approaches and a considered justification of the reasons why you chose the method that you did.
   
4. A results sections. This should describe the findings that you obtained. It should also discuss any problems that arose during the study that might make it difficult to interpret your findings.
   
5. Conclusions. You must provide a clear statement about whether or not your study supports the ideas behind risk homeostasis. If your study indicates a mixed set of conclusions then you should state which aspects of the theory you are willing to support. You should also identify the limitations of the theory as it currently exists,

1. the listing of any code used during the study together with suitable acknowledgements for the source of code that has been borrowed from other programmers;
   
2. source data for any statistical study. The intention is that another analysts should be able to recreate your results in order to validate your findings. If the source data comes from the web or is available in another electronic form it is acceptible to simply provide a reliable URL or a disk.

The following marking scheme will be applied:

• 15 for the method;
• 10 for the results;
• 15 for the conclusion;
• 10 for the technical documentation.

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