“Single subject research (also known as single case experiments) is popular in the fields of special education and counseling. This research design is useful when the researcher is attempting to change the behavior of an individual or a small group of individuals and wishes to document that change. Unlike true experiments where the researcher randomly assigns participants to a control and treatment group, in single subject research the participant serves as both the control and treatment group. The researcher uses line graphs to show the effects of a particular intervention or treatment. An important factor of single subject research is that only one variable is changed at a time. Single subject research designs are “weak when it comes to external validity….Studies involving single-subject designs that show a particular treatment to be effective in changing behavior must rely on replication–across individuals rather than groups–if such results are be found worthy of generalization” (Fraenkel & Wallen, 2006, p. 318).
Suppose a researcher wished to investigate the effect of praise on reducing disruptive behavior over many days. First she would need to establish a baseline of how frequently the disruptions occurred. She would measure how many disruptions occurred each day for several days. In the example below, the target student was disruptive seven times on the first day, six times on the second day, and seven times on the third day. Note how the sequence of time is depicted on the x-axis (horizontal axis) and the dependent variable (outcome variable) is depicted on the y-axis (vertical axis).
Once a baseline of behavior has been established (when a consistent pattern emerges with at least three data points), the intervention begins. The researcher continues to plot the frequency of behavior while implementing the intervention of praise.
In this example, we can see that the frequency of disruptions decreased once praise began. The design in this example is known as an A-B design. The baseline period is referred to as A and the intervention period is identified as B.
Another design is the A-B-A design. An A-B-A design (also known as a reversal design) involves discontinuing the intervention and returning to a nontreatment condition.
Sometimes an individual’s behavior is so severe that the researcher cannot wait to establish a baseline and must begin with an intervention. In this case, a B-A-B design is used. The intervention is implemented immediately (before establishing a baseline). This is followed by a measurement without the intervention and then a repeat of the intervention.
Sometimes, a researcher may be interested in addressing several issues for one student or a single issue for several students. In this case, a multiple-baseline design is used.
“In a multiple baseline across subjects design, the researcher introduces the intervention to different persons at different times. The significance of this is that if a behavior changes only after the intervention is presented, and this behavior change is seen successively in each subject’s data, the effects can more likely be credited to the intervention itself as opposed to other variables. Multiple-baseline designs do not require the intervention to be withdrawn. Instead, each subject’s own data are compared between intervention and nonintervention behaviors, resulting in each subject acting as his or her own control (Kazdin, 1982). An added benefit of this design, and all single-case designs, is the immediacy of the data. Instead of waiting until postintervention to take measures on the behavior, single-case research prescribes continuous data collection and visual monitoring of that data displayed graphically, allowing for immediate instructional decision-making. Students, therefore, do not linger in an intervention that is not working for them, making the graphic display of single-case research combined with differentiated instruction responsive to the needs of students.” (Geisler, Hessler, Gardner, & Lovelace, 2009)
Regardless of the research design, the line graphs used to illustrate the data contain a set of common elements.
I have created a PowerPoint about SingleSubject.
I have also created instructions for creating single-subject research design graphs with Excel.
Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in education (6th ed.). Boston, MA: McGraw Hill.
Geisler, J. L., Hessler, T., Gardner, R., III, & Lovelace, T. S. (2009). Differentiated writing interventions for high-achieving urban African American elementary students. Journal of Advanced Academics, 20, 214–247.
Del Siegle, Ph.D.
University of Connecticut
In design of experiments, single-subject design or single-case research design is a research design most often used in applied fields of psychology, education, and human behavior in which the subject serves as his/her own control, rather than using another individual/group. Researchers use single-subject design because these designs are sensitive to individual organism differences vs group designs which are sensitive to averages of groups. Often there will be large numbers of subjects in a research study using single-subject design, however—because the subject serves as their own control, this is still a single-subject design. These designs are used primarily to evaluate the effect of a variety of interventions in applied research.
The following are requirements of single-subject designs:
- Continuous assessment: The behavior of the individual is observed repeatedly over the course of the intervention. This ensures that any treatment effects are observed long enough to convince the scientist that the treatment produces a lasting effect.
- Baseline assessment: Before the treatment is implemented, the researcher is to look for behavioral trends. If a treatment reverses a baseline trend (e.g., things were getting worse as time went on in the baseline but the treatment reversed this trend) then this is powerful evidence suggesting (though not proving) a treatment effect.
- Variability in data: Because behavior is assessed repeatedly, the single-subject design allows the researcher to see how consistently the treatment changes behavior over time. Large-group statistical designs do not typically provide this information because repeated assessments are not usually taken and the behavior of individuals in the groups are not scrutinized; instead, group means are reported.
Phases within single-subject design
- Baseline: this phase is one in which the researcher collects data on the dependent variable without any intervention in place.
- Intervention: this phase is one in which the researcher introduces an independent variable (the intervention) and then collects data on the dependent variable.
- Reversal: this phase is one in which the researcher removes the independent variable (reversal) and then collects data on the dependent variable.
It is important that the data are stable (steady trend and low variability) before the researcher moves to the next phase. Single-subject designs produce or approximate three levels of knowledge: (1) descriptive, (2) correlational, and (3) causal.
Flexibility of the design
Single-subject designs are preferred because they are highly flexible and highlight individual differences in response to intervention effects. In general, single-subject designs have been shown to reduce interpretation bias for counselors when doing therapy.
Interpretation of data
In order to determine the effect of the independent variable on the dependent variable, the researcher will graph the data collected and visually inspect the differences between phases. If there is a clear distinction between baseline and intervention, and then the data returns to the same trends/level during reversal, a functional relation between the variables is inferred. Sometimes, visual inspection of the data demonstrates results that statistical tests fail to find.
Researchers utilizing single-subject design begin with graphic analysis. During the baseline, data are repeatedly collected and then graphed on the behavior of interest. This provides a visual representation of the subject's behavior before application of the intervention. It is critical that several (three to five is often recommended) data points are collected during baseline to allow the researcher to describe the effects on the target behavior during intervention.
In interpreting, the general strategy of all single-subject research is to use the subject as their own control. Experimental logic argues that the subject's baseline behavior would match its behavior in the intervention phase unless the intervention does something to change it. This logic then holds to rule out confound, one needs to replicate. It is the within-subject replication and allows for the determination of functional relationships. Thus the goal is:
Research designs are traditionally preplanned so that most of the details about to whom and when the intervention will be introduced are decided prior to the beginning of the study. However, in single-subject designs, these decisions are often made as the data are collected. In addition, there are no widely agreed-upon rules for altering phases, so—this could lead to conflicting ideas as to how a research experiment should be conducted in single-subject design.
The major criticism of single-subject designs are:
- Carry-over effects: Results from the previous phase carry-over into the next phase.
- Order effects: The ordering (sequence) of the intervention or treatment affects what results.
- Irreversibility: In some withdrawal designs, once a change in the independent variable occurs, the dependent variable is affected. This cannot be undone by simply removing the independent variable.
- Ethical problems: Withdrawal of treatment in the withdrawal design can at times present ethical and feasibility problems.
Historically, single-subject designs have been closely tied to the experimental analysis of behavior and applied behavior analysis.
- Kazdin, Alan (1982). Single-Case Research Designs. New York: Oxford University Press. ISBN 0-19-503021-4.
- ^Cooper, J.O.; Heron, T.E.; Heward, W.L. (2007). Applied Behavior Analysis (2nd ed.). Prentice Hall. ISBN 0-13-142113-1.
- ^Kazdin p. 191
- ^Kazdin, pp. 103–10
- ^Tripodi, T. (1998). A Primer on Single-Subject Design for Clinical Social Workers. Washington, DC: National Association of Social Workers (NASW) Press
- ^Thompson, C.K. (1986). Flexibility of Single-subject Experimental Designs. Part III: Using Flexibility to Design or Modify Experiments. The Journal of Speech and Hearing Disorders, 51(3), 214–25
- ^Moran, D.J. & Tai, W. (2001). Reducing Biases in Clinical Judgment with Single-Subject Treatment Design. The Behavior Analyst Today, 2(3), 196–206 BAO
- ^Backman, C.L. & Harris, S.R. (1999). Case Studies, Single-Subject Research, and N of 1 Randomized Trials. Comparisons and Contrasts. American Journal of Physical Medicine & Rehabilitation, 78(2), 170–6.
- ^Bobrovitz, C.D. & Ottenbacher, K.J. (1998). Comparison of Visual Inspection and Statistical Analysis of Single-Subject Data in Rehabilitation Research. Journal of Engineering and Applied Science, 77(2), 94–102.
- ^Nishith, P.; Hearst, D.E.; Mueser, K.T. & Foa, E. (1995). PTSD and Major Depression: Methodological and Treatment Considerations in a Single-Case Design. Behavior Therapy, 26(2), 297–9
- ^Alberto, P.A. & Troutman, A.C. (2006). Applied behavior analysis for teachers (7th ed.). Upper Saddle River, NJ: Pearson Education, Inc.
- ^Kazdin, p. 284
- ^Kazdin, p. 291