11.5: Summary of Small-N Design

Key Takeaways

• Small-N designs, which involve experimentally testing a small number of participants and focusing intensively on the behavior of each individua, is an important alternative to group research in psychology.
• Small-N design studies must be distinguished from qualitative research (discussed in detail next) on a single person or small number of individuals. Unlike more qualitative research, Small-N design research focuses on understanding objective behavior through experimental manipulation and control, collecting highly structured data, and analyzing those data quantitatively.
• Small-N research has been around since the beginning of the field of psychology. Today it is most strongly associated with the behavioral theoretical perspective, but it can in principle be used to study behavior from any perspective.
• Small-N designs typically involve measuring the dependent variable repeatedly over time and changing conditions (e.g., from baseline to treatment) when the dependent variable has reached a steady state. This approach allows the researcher to see whether changes in the independent variable are causing changes in the dependent variable.
• In a reversal design, the participant is tested in a baseline condition, then tested in a treatment condition, and then returned to baseline. If the dependent variable changes with the introduction of the treatment and then changes back with the return to baseline, this provides strong evidence of a treatment effect.
• In a multiple-baseline design, baselines are established for different participants, different dependent variables, or different settings—and the treatment is introduced at a different time on each baseline. If the introduction of the treatment is followed by a change in the dependent variable on each baseline, this provides strong evidence of a treatment effect.
• Small-N designs are typically analyzed by graphing the data and making judgments about whether the independent variable is affecting the dependent variable based on level, trend, and latency.
• Differences between small-N designs and large-N research sometimes lead to disagreements between researchers. These disagreements center on the issues of data analysis and external validity (especially generalization to other people).
• Small-N design and large-N research are probably best seen as complementary methods, with different strengths and weaknesses, that are appropriate for answering different kinds of research questions.

What's Next?

You've read about many of the common types of experimental designs in the social sciences. Now, we will focus on nonexperimental designs. While we can't show cause-and-effect with these types of designs, they provide important information. Just like small-N designs are complementary to large-N designs, experimental and nonexperimental research can provide insight and context to each other.

Exercises

• Practice: Find and read a published article that reports new small-N research. (An archive of articles published in the Journal of Applied Behavior Analysis can be found at http://www.ncbi.nlm.nih.gov/pmc/journals/309/) Write a short summary of the study.
• Practice: Come up with three outcome behaviors (DVs) related to helping clients in your future career that would work well in a small-N design. These behaviors should be easy to observe, and would change quickly based on whether they are observed in the baseline or treatment condition.
• Practice: Come up with three treatments (IVs) related to helping clients in your future career that would work well in a small-N design. These interventions should be something that we expect to affect the outcome right away and also may quickly fade so that we can see changes in the DV based on the IV easily.
• Practice: Using one of the treatments and one of the behaviors that you listed above, design a simple small-N study (using either a reversal or multiple-baseline design) to answer a question to help clients in your future career. Be sure to specify the treatment, operationally define the dependent variable, decide when and where the observations will be made, and so on.
• Practice: Create a graph that displays the hypothetical results for the study you designed above, then write a paragraph in which you describe what the results show. Be sure to comment on level, trend, and latency.
• Discussion: Imagine you have conducted a small-N study showing a positive effect of a treatment on the behavior of a man with social anxiety disorder. Your research has been criticized on the grounds that it cannot be generalized to others. How could you respond to this criticism?
• Discussion: Imagine you have conducted a large-N study showing a positive effect of a treatment on the behavior of a group of people with social anxiety disorder, but your research has been criticized on the grounds that “average” effects cannot be generalized to individuals. How could you respond to this criticism?
• Discussion : Redesign as a group study the study by Hall et al. (1968) described at the beginning of this chapter. List the strengths and weaknesses of each study, and decide which type of study is most appropriate for this topic.
• Discussion: The generation effect refers to the fact that people who generate information as they are learning it (e.g., by self-testing) recall it better later than do people who simply review information. Design a small-N study on the generation effect applied to university students learning brain anatomy, then design a large-N study on the same topic. List the strengths and weaknesses of each study, and decide which type of study is most appropriate for this topic.

References

Hall, R. V., Lund, D., & Jackson, D. (1968). Effects of teacher attention on study behavior. Journal of Applied Behavior Analysis, 1, 1–12.