Behavioral Avoidance, How do we Prove an ‘Unknown’?

Many social development programs want to achieve behavior change. Yet, not all forms of behavior change are the same. In fact, the forms of behavior change can be quite different and can all have different implications when it comes to measuring.

Consider the following examples that illustrate different types of behavior change: mosquito nets, safety helmets, rhino horn, smoking cessation, safe migration, and prevention of trafficking in persons (TIP).

How are they different?

The first two examples represent how most people think about behavior change, a situation where we want people to adopt new behavior. This could represent completely new behavior for some and adopting a more regular routine for others. Rhino horn consumption and smoking, on the other hand, represent dysfunctional behavior. Since negative behavior has already been adopted, these examples call for a reverse engineering exercise to influence people to stop.

What about safe migration and TIP prevention? The challenge here is that it becomes difficult to define specific behaviors. The issue is not about adopting or stopping a particular behavior but rather avoiding certain risks. Some examples include: not trusting job agents blindly, not giving up personal ID documents, not accepting a job without a proper contract, and so on. So the issue becomes behavioral avoidance and taking measures to ensure the work opportunity is real. From a behavior change point of view, safe migration and TIP prevention present a more complex situation.


When we want beneficiaries to adopt new behaviors, the focus for behavior change measurement will be around how regularly the new behavior is adopted. Behavior may, at first, be occasional or non-existent. Following an intervention or other activity we hope to see behavior become more regular. It would not be reasonable to expect behavior to be adopted 100%; instead, it is the degree of regularity that needs to be taken into consideration.

Rhino horn consumption and smoking are dysfunctional behaviors we want consumers to stop. When someone tries to stop smoking they often have to stop several times before they stop completely. Rhino horn consumption is often occasional, especially if consumed for medical reasons (Note: scientists have very little evidence to support the medical efficacy of rhino horn). Hence, the focus for behavior change measurement will be on future consumption intentions. However, the advantage of behavioral adoption and stopping dysfunctional behavior is that behavior, in many instances, can be observed. It may not always be practical, but the option for verification through observation can be available.

Behavioral avoidance is a different matter. When looking at issues like safe migration and human trafficking, there is no one particular behavior that beneficiaries need to adopt. Instead, there are a host of issues that need to be considered and many of them relate to risk avoidance. In this situation, proving behavior change becomes very difficult, if not impossible. How do we prove an ‘unknown’? If we educate a group of beneficiaries on how to migrate safely and as a result none of them end up being trafficked, this does not prove that the education program worked. This is the dilemma when dealing with this form of behavior change. As such, developing proxy measures becomes important. Knowledge, attitudes, and behavioral intentions all need to be considered and measured within the context of the situation facing beneficiaries. This shall be discussed in a future blog.

For those who want to read more about this subject, please see our previous blogs in our behavior change series.

Behavior Change is Not Black&White

Measuring Behavior Change, Effectively


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About the Author: Daniel Lindgren is the Founder of Rapid Asia Co., Ltd., a management consultancy firm based in Bangkok that specializes in evaluations for programs, projects, social marketing campaigns and other social development initiatives. Learn more about our work on: