Table Of Content
Wacker and colleagues (1990) conducted dropout-type component analyses of functional communication training (FCT) procedures for three individuals with challenging behavior. The data presented in Figure 6 show the percentage of intervals with hand biting, prompts, and mands (signing) across functional analysis, treatment package, and component analysis phases. The functional analysis results indicated that the target behavior (hand biting) was maintained by access to tangibles as well as by escape from demands. In the second phase, a treatment package that included FCT and time-out was implemented. By the end of the phase, the target behavior was eliminated, prompting had decreased, and signing had increased. To identify the active components of the treatment package, a dropout component analysis was conducted.
Multiple-Treatment Designs
An excellent discussion of this issue can be found in the exchange of letters to the editor by Hoodin (1986) [Article] and Rubow and Swift (1986) [Article]. Single-subject studies should not be confused with case studies or other non-experimental designs. One of the biggest mistakes, that is a huge problem, is misunderstanding that a case study is not a single-subject experimental design.
XII. Chapter 12: Descriptive Statistics
Structure and Phases of the DesignSingle-subject designs are typically described according to the arrangement of baseline and treatment phases. Single Subject Research Designs (SSRDs) work by designing an experiment where, instead of a control group of subjects and an experimental group of subjects whose results are compared to one another, the control and experimental measurements come from a single subject. Researchers measure the metric of interest before introducing the experimental factor for a control measurement, and measure the metric of interest after introducing the experimental factor for the experimental measure.
The Role of SSEDs in Evidence-Based Practice
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The basics of SSED methodology are described, followed by descriptions of several commonly implemented SSEDs, including their benefits and limitations, and a discussion of SSED analysis and evaluation issues. A set of standards for the assessment of evidence quality in SSEDs is then reviewed. Finally, a number of current issues in SSEDs, including effect size calculations and the use of statistical techniques in the analysis of SSED data, are considered. In this design, multiple baselines are either established for one participant or one baseline is established for many participants. The level of responding before any treatment is introduced and therefore acts as a kind of control condition.
IX. Chapter 9: Factorial Designs
Group methodology often requires great time and resources in order to produce properly powered experiments. This can lead to problems with rigor, particularly in contexts of limited funding and publish-or-perish job demands (Bernard, 2016; Button, 2016). Thus, both cost and rigor could be served by conscientiously adding single-subject methodology to the neuroscience toolbelt. In this design two or more treatments are alternated relatively quickly on a regular schedule. In the late 1800s, one of psychology’s founders, Wilhelm Wundt, studied sensation and consciousness by focusing intensively on each of a small number of research participants.
Numerous criteria have been developed to identify best educational and clinical practices that are supported by research in psychology, education, speech-language science, and related rehabilitation disciplines. Some of the guidelines include SSEDs as one experimental design that can help identify the effectiveness of specific treatments (e.g., Chambless et al., 1998; Horner et al., 2005; Yorkston et al., 2001). F. Skinner clarified many of the assumptions underlying single-subject research and refined many of its techniques (Skinner, 1938)[2]. He and other researchers then used it to describe how rewards, punishments, and other external factors affect behavior over time. This work was carried out primarily using nonhuman subjects—mostly rats and pigeons. This approach, which Skinner called the experimental analysis of behavior—remains an important subfield of psychology and continues to rely almost exclusively on single-subject research.
Precedent of within-subject methods
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For excellent examples of this work, look at any issue of the Journal of the Experimental Analysis of Behavior. By the 1960s, many researchers were interested in using this approach to conduct applied research primarily with humans—a subfield now called applied behavior analysis (Baer, Wolf, & Risley, 1968)[3]. Applied behavior analysis plays an especially important role in contemporary research on developmental disabilities, education, organizational behavior, and health, among many other areas. Excellent examples of this work (including the study by Hall and his colleagues) can be found in the Journal of Applied Behavior Analysis.
In the end, effect detection is determined by data patterns in relation to the phases of the experimental design. It seems that the clearer one is about the logic of the design and the criteria that will be used to determine an effect in advance, the less one needs to rely on searching for a “just-in-case” test after the fact. Overall, visual inspection of these data provides a strong argument for the necessity of both the FCT and time-out components in the effectiveness of the treatment package, and no indications of noneffect are present in the data.
The dependent variable ranges between 12 and 16 units during the baseline, but drops down to 10 units with treatment and mostly decreases until the end of the study, ranging between 4 and 10 units. Again, single-subject research involves studying a small number of participants and focusing intensively on the behavior of each one. There are several important assumptions underlying single-subject research, and it will help to consider them now. Sometimes behaviors come and go over time (such as being off task in a classroom or not listening during a coaching session). The way we can record these is to select a period of time (say 5 minutes) and mark down every 10 seconds whether our participant is on task. We make a minimum of three sets of 5 minute observations for a baseline, implement an intervention, and then make more sets of 5 minute observations with the intervention in place.
Is a type of quantitative research that involves studying in detail the behavior of each of a small number of participants. Note that the term single-subject does not mean that only one participant is studied; it is more typical for there to be somewhere between two and 10 participants. The majority of this book is devoted to understanding group research, which is the most common approach in psychology. But single-subject research is an important alternative, and it is the primary approach in some areas of psychology. The logic of the ATD is similar to that of multiple-treatment designs, and the types of research questions that it can address are also comparable.
Well-considered statistical best practices for various forms of group analysis (e.g., Moen et al., 2016) can help a researcher to address limitations. For a clear example, interested readers are referred to Silberglitt and Gibbons’ (2005) documentation of a slope-standard approach to identifying, intervening, and monitoring reading fluency and at-risk students. Of course, the approach (relying on slope values from serially collected single-subject data) is not without its problems. Depending on the frequency and duration of data collection, the standard error of the estimate for slope values can vary widely (Christ, 2006), leading to interpretive problems for practice.
The greater the percentage of nonoverlapping data, the stronger the treatment effect. Still, formal statistical approaches to data analysis in single-subject research are generally considered a supplement to visual inspection, not a replacement for it. The mean and standard deviation of each participant’s responses under each condition are computed and compared, and inferential statistical tests such as the t test or analysis of variance are applied (Fisch, 2001)[3]. (Note that averaging across participants is less common.) Another approach is to compute the percentage of non-overlapping data (PND) for each participant (Scruggs & Mastropieri, 2001)[4].
So, if I were doing a group treatment study, I would not necessarily be able to see or to understand what was happening with each individual patient, so that I could make modifications to my treatment and understand all the details of what’s happening in terms of the effects of my treatment. An advantage of using an SSRD is that, instead of comparing the percentage of people that responded to an experimental factor to the percentage of people that did not, the study examines how an individual subject, with his own unique characteristics, responds to the experimental factor. This is particularly useful when studying specific subsets of a population, rather than the population as a whole.
This is because (a) the final two final treatment phases do not include the minimum of three data points and (b) the individual treatment component phases (FCT only and time-out/DRO) were implemented only once each. As a result, the data from this study could not be used to support the treatment package as an evidence-based practice by the IES standards. Additional data points within each phase, as well as replications of the phases, would strengthen the study results. When selecting conditions for a multiple-baseline (or multiple-probe) design, it is important to consider both the independence and equivalence of the conditions.
But there are important differences between these approaches too, and these differences sometimes lead to disagreements. It is worth addressing the most common points of disagreement between single-subject researchers and group researchers and how these disagreements can be resolved. As we will see, single-subject research and group research are probably best conceptualized as complementary approaches. The advantages highlighted above suggest not only compatibility between single-subject and group approaches, but a potential advantage conferred by an order of operations between methods.
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