13.5: Non-experimental designs

Learning Objectives

Learners will be able to...

• Describe non-experimental designs in social work research
• Discuss how non-experimental research differs from true and quasi-experimental research
• Demonstrate an understanding the different types of non-experimental designs
• Determine what kinds of research questions non-experimental designs are suited for
• Discuss advantages and disadvantages of non-experimental designs

The previous sections have laid out the basics of some rigorous approaches to establish that an intervention is responsible for changes we observe in research participants. This type of evidence is extremely important to build an evidence base for social work interventions, but it's not the only type of evidence to consider. We will discuss qualitative methods, which provide us with rich, contextual information, in Part 4 of this text. The designs we'll talk about in this section are sometimes used in [pb_glossary id="851"]qualitative research, but in keeping with our discussion of experimental design so far, we're going to stay in the quantitative research realm for now. Non-experimental is also often a stepping stone for more rigorous experimental design in the future, as it can help test the feasibility of your research.

In general, non-experimental designs do not strongly support causality and don't address threats to internal validity. However, that's not really what they're intended for. Non-experimental designs are useful for a few different types of research, including explanatory questions in program evaluation. Certain types of non-experimental design are also helpful for researchers when they are trying to develop a new assessment or scale. Other times, researchers or agency staff did not get a chance to gather any assessment information before an intervention began, so a pretest/post-test design is not possible.

 

One-on-one assessments are a key part of pre- and non-experimental designs.

 

A significant benefit of these types of designs is that they're pretty easy to execute in a practice or agency setting. They don't require a comparison or control group, and as Engel and Schutt (2017)\(^3\) point out, they "flow from a typical practice model of assessment, intervention, and evaluating the impact of the intervention" (p. 177). Thus, these designs are fairly intuitive for social workers, even when they aren't expert researchers. Below, we will go into some detail about the different types of non-experimental design.

 

One group pretest/post-test design

Also known as a before-after one-group design, this type of research design does not have a comparison group and everyone who participates in the research receives the intervention (Figure 13.8). This is a common type of design in program evaluation in the practice world. Controlling for extraneous variables is difficult or impossible in this design, but given that it is still possible to establish some measure of time order, it does provide weak support for causality.

Figure 13.7 One group pretest/post-test design

 

Imagine, for example, a researcher who is interested in the effectiveness of an anti-drug education program on elementary school students’ attitudes toward illegal drugs. The researcher could assess students' attitudes about illegal drugs (O₁), implement the anti-drug program (X), and then immediately after the program ends, the researcher could once again measure students’ attitudes toward illegal drugs (O₂). You can see how this would be relatively simple to do in practice, and have probably been involved in this type of research design yourself, even if informally. But hopefully, you can also see that this design would not provide us with much evidence for causality because we have no way of controlling for the effect of extraneous variables. A lot of things could have affected any change in students' attitudes—maybe girls already had different attitudes about illegal drugs than children of other genders, and when we look at the class's results as a whole, we couldn't account for that influence using this design.

All of that doesn't mean these results aren't useful, however. If we find that children's attitudes didn't change at all after the drug education program, then we need to think seriously about how to make it more effective or whether we should be using it at all. (This immediate, practical application of our results highlights a key difference between program evaluation and research, which we will discuss in Chapter 23.)

 

After-only design

As the name suggests, this type of non-experimental design involves measurement only after an intervention. There is no comparison or control group, and everyone receives the intervention. I have seen this design repeatedly in my time as a program evaluation consultant for nonprofit organizations, because often these organizations realize too late that they would like to or need to have some sort of measure of what effect their programs are having.

Because there is no pretest and no comparison group, this design is not useful for supporting causality since we can't establish the time order and we can't control for extraneous variables. However, that doesn't mean it's not useful at all! Sometimes, agencies need to gather information about how their programs are functioning. A classic example of this design is satisfaction surveys—realistically, these can only be administered after a program or intervention. Questions regarding satisfaction, ease of use or engagement, or other questions that don't involve comparisons are best suited for this type of design.

 

Static-group design

A final type of non-experimental research is the static-group design. In this type of research, there are both comparison and experimental groups, which are not randomly assigned. There is no pretest, only a post-test, and the comparison group has to be constructed by the researcher. Sometimes, researchers will use matching techniques to construct the groups, but often, the groups are constructed by convenience of who is being served at the agency.

 

Conclusion

Non-experimental research designs are easy to execute in practice, but we must be cautious about drawing causal conclusions from the results. A positive result may still suggest that we should continue using a particular intervention (and no result or a negative result should make us reconsider whether we should use that intervention at all). You have likely seen non-experimental research in your daily life or at your agency, and knowing the basics of how to structure such a project will help you ensure you are providing clients with the best care possible.

 

Key Takeaways

• Non-experimental designs are useful for describing phenomena, but cannot demonstrate causality.
• After-only designs are often used in agency and practice settings because practitioners are often not able to set up pre-test/post-test designs.
• Non-experimental designs are useful for explanatory questions in program evaluation and are helpful for researchers when they are trying to develop a new assessment or scale.
• Non-experimental designs are well-suited to qualitative methods.

 

Exercises

• If you were to use a non-experimental design for your research project, which would you choose? Why?
• Have you conducted non-experimental research in your practice or professional life? Which type of non-experimental design was it?