When researchers conduct an experiment, they’re often interested in understanding whether a certain “treatment” affects an outcome. To test this, they’ll often recruit a random sample of individuals to be part of a control group and another random sample of individuals to be part of a treatment group.
At the end of the experiment, they’ll record the outcomes for each group and conduct some statistical test to determine if the treatment significantly affected the outcome.
One potential issue that researchers could run into when conducting an experiment is treatment diffusion.
Treatment diffusion: When the control group in an experiment is affected by the treatment in some way.
In this post we’ll share:
- An example of treatment diffusion
- Why treatment diffusion can be a serious problem
- How to prevent treatment diffusion from occurring
An Example of Treatment Diffusion
Suppose researchers are interested in finding out if a certain studying technique leads to a significant improvement in exam scores among students at a certain school. To test this, they may recruit the following two random samples:
Control group: 25 students who are told to continue to use their current studying technique.
Treatment group: 25 students who are taught how to use the new studying technique.
After one month, each of the students take the same exam. The researchers had planned on conducting a two sample t-test to determine if their was a significant difference in mean exam scores between the two groups, but it was discovered that students in the treatment group were sharing the studying technique with students in the control group during lunch.
Because the students in the control group found out about the exact studying technique that students in the treatment group were using, it’s possible that they also started using the technique to potentially boost their own exam scores.
This is an example of treatment diffusion – the individuals in the control group became affected by the treatment. Thus, the researchers will have a much harder time determining if any differences in exam scores can be attributable to the studying technique because students in both groups likely used the technique.
Why treatment diffusion can be a serious problem
When treatment diffusion occurs, it causes two specific problems:
1. It makes it difficult for researchers to know if the difference in outcomes between two groups can be attributed to the treatment.
2. It makes it difficult for researchers to quantify how much of an impact that a treatment had on the outcome.
Essentially, treatment diffusion threatens the overall validity of the experiment and makes it hard for researchers to be confident in the conclusions that they draw.
How to prevent treatment diffusion from occurring
Treatment diffusion is typically a problem in experiments when researchers provide some type of training or information to the individuals in the experiment.
In these situations, there’s always a possibility that information can spread from individuals in the treatment group to individuals in the control group. Individuals may talk to each other about the information they learned, or even share information via texting, emailing, or calling. And when individuals in the control group learn about this information, they may decide to modify their own behavior.
To prevent treatment diffusion from occurring, researchers may decide to place the control group and the treatment group in two different locations to prevent the spread of information. For example, researchers may decide to use a group of students at one school as the control group and a group of students from a different school as the treatment group. This makes it much less likely for treatment diffusion to occur.
One drawback of separating individuals based on location is that it’s possible that the two groups aren’t similar enough to each other. For example, students at one school might have a different socioeconomic background, educational standards, and even school hours compared to students at the other school. This increases the chances that any differences in exam scores could be due to other factors besides the studying technique.