If your research project involves a treatment, intervention, or some kind of experimental manipulation, you may consider using a pre-test/post-test design (known more generally as a repeated-measures design). In a pre-test/post-test design, the same participants are measured on the variables of interest at multiple points in time. For instance, if you wanted to test the effectiveness of an advertising campaign on people’s attitudes towards a product, you could have a group of participants take a survey that assesses their attitudes before the campaign started, and then have the same participants take the survey again after they see the campaign. You could then conduct a repeated-measures analysis (such as a dependent samples t-test) to see if the participants’ attitudes significantly change from before the campaign (the pre-test) to after the campaign (the post-test). One of the main advantages of pre-test/post-test designs is that the associated repeated-measures statistical analyses tend to be more powerful, and thus require considerably smaller sample sizes, than other types of analyses.
However, there are important considerations to take into account before deciding on a pre-test/post-test design. Among the most important, but easily overlooked, considerations are the logistics of collecting the data. First you need to determine if it will be possible to survey or measure the same individuals multiple times. This can be tricky if participants are providing their responses completely anonymously (e.g., through an online survey).
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Even if you are able to contact the same participants multiple times, you will need a way to link their responses from pre-test to post-test. In other words, you need to be able to pair each person’s responses on the pre-test to their responses on the post-test. This step is absolutely crucial in order to be able to conduct repeated-measures analyses on your data. If the participants are to remain anonymous, you will need to assign each participant a unique, de-personalized identifier such as an ID number or code. The participants will then need to provide their unique identifier each time they complete the survey. One of the simplest ways to do this is to have participants create their own unique identifier the first time they take the survey. You should instruct your participants to create identifiers that they will be able to readily recall, but at the same time do not contain enough information to personally identify them. For example, you could instruct participants to enter the last four digits of their phone number followed by their middle initial. Importantly, you need to make sure the participant provides this identifier each time they take the survey.
These logistical considerations are important to think about before finalizing your study design and methodology. It best to be aware of the potential issues and roadblocks of data collection early in the process so that you can design a good, feasible study.