Reference no: EM133352283

What are some of the drawbacks for using single-case experimental designs? Can you think of any for the specific case of children with ASD?

Although large studies tend to be more popular and provide more sophisticated statistical analysis, studies using one or just a few individuals continue to make important contributions to our knowledge of behavior (Goodwin & Goodwin, 2017). Because in large groups the averages can disguise differences among the individuals composing those groups, researchers have argued that group data may often describe a process, or a functional relation, that has no validity for any individual (Goodwin & Goodwin, 2017)

Small N designs are needed sometimes because potential research participants can be rare or a challenge to find. One example of a small N design using applied behavioural analysis is a single case experimental design. This design is a type of interrupted time-series design where other control variables or randomization is not appropriate or possible (Batley, 2022). For example, consider a child with autism spectrum disorder (ASD) or a patient with a rare disease, it is not only challenging to gather participants to be analyzed for statistically significant results, but it would also be inappropriate to collect these individuals into a homogenous group (Batley, 2022). Further, while one child with ASD might show symptoms of hyperactivity, another might show self-injury behaviors, while yet another might show eating or sleeping problems where in fact, all these children may have different triggers for these behaviors (Batley, 2022). A one-size-fits-all type intervention would be a waste of time and resources.