A single-subject design is an experimental design where one participant is used as both the control and treatment groups. It is important to distinguish a single-subject design from a case study design. Case studies also use one participant who is analysed, however case studies are descriptive methods and are often used for forming hypotheses and are often qualitative, whereas cause-and-effect can be established using a quantitative single-subject design as it is experimental.
A series of observations are made over time of one participant during various phases. In most cases an ABAB design is used, where phases will alternate between the baseline phase and the treatment phase. This alternating treatments design can often be used to compare different treatments as well as recurrence of one treatment, as discussed by Barlow and Hayes (1979). In the baseline phase observations are made when there is no treatment. This serves as the control condition for the participant. Once a treatment has been administered this becomes the treatment phase. Many observations are made during this phase to establish the effect of the treatment in comparison to the baseline phase. This treatment is then removed, thus returning to the baseline phase again. The aim of this phase is to establish if the effects in the treatment condition were due to the intervention or due to a different confounding variable. It is expected that if the effect was due to the intervention then this second baseline phase should be equivalent to the first baseline phase as the effects of treatment have been removed. Sometimes this is not shown when a treatment has long lasting effects on a patient. After this second baseline phase the treatment is administered again to compare to the other treatment phase to ensure that it was the treatment causing the effects for the first interval. The image below, taken from Horner, Carr, Halle, McGee, Odom and Wolery (2005), shows an example of an ABAB design.
Single-subject designs are not usually analysed using the traditional statistical methods used for many other methods of research. The data is frequently presented graphically for visual inspection. The graph is measured on 2 main features, its level and trend. A level is the magnitude of the participant’s responses, which should be approximately a horizontal line. A trend is when differences from one measurement to the next follow the same direction and magnitude. On a graph this would be shown by clustering points along a sloping line. These 2 features are described in terms of stability, based on the consistency of levels and trends.
A main practical use of a single-subject design is the N of 1 trial. This is a clinical trial where the participant serves as both the control and the patient. This can be used in a similar way to the ABAB design as described above, or can be adapted to establish the effects of various types of a drug, or to test a drug against a placebo. These trials are flexible towards the individual, and the rate of success for each individual is much higher than that of using traditional group methods of testing, see Kravitz et al. (2008). However, this trial is not used very often in today’s society, even though it has the potential to be much more effective than other methods of treatment. It is very costly and time-consuming to perform long-term and detailed examination of each individual’s reactions to certain drugs in order to provide the appropriate care required, however it could be argued that in many cases drugs are being prescribed on the basis of group research when an individual may benefit more from a different drug which is produced more cheaply, and may not require the drug for as long as the average patient, therefore money could also be saved. Kravitz et al. (2008) argue that it is unjust that methods such as X-rays are used for diagnostic precision, however clinicians will not readily use the N of 1 trial to increase therapeutic precision and to facilitate modern clinical care.
Single-subject designs have several advantages, the main one being that it has the potential to increase the success of treatments for individuals. Cause-and-effect can be established using this method, and only 1 participant is needed, thus reducing the need of standardized treatments like in group research. It is also helpful to observe long lasting effects which would not usually be tested using group research. However there are also many limitations for using this research design. As the research is only using one participant it is difficult to generalise as individual differences could have a major impact on the effectiveness of the intervention. Also, multiple observations can lead to sensitization and carry over effects which can alter the measurements of behaviour. Reliance on a graph for interpretation can also limit the effectiveness of the research as it can be based on individual interpretation and can require large and immediate changes in order to perceive any effects. However, it is possible to do statistical analysis along with visual representation.
So, to conclude, single-subject designs can be very useful, especially in the clinical field, to find cause and effect relationships using few participants and to establish longer term results than usually investigated in traditional group methods, however it is hard to generalise these results for the research to have an impact on a larger population.
For more information see Gravetter & Forzano (2009), Research methods for the behavioural sciences, chapter 14.