Applied Behavior Analysis (ABA)

What is Applied Behavior Analysis (ABA)[1]

Applied Behavior Analysis (ABA) has been defined as the systematic application and evaluation of principles of behavior analysis for the improvement of specific behaviors (Baer, Wolf, & Risley, 1987). The terms and principles of behavior management most often used in ABA include learning, stimuli, responses, consequences, positive reinforcement, negative reinforcement, punishment, and extinction. The techniques used in ABA include prompting, modeling, chaining, differential reinforcement, and fading. Applied behavior analysis (ABA) is a set of procedures drawn from the discipline of behavior analysis that allows for an understanding of the reasons that certain behaviors may occur.

Specifically, Applied Behavior Analysis involves the principles of learning theory. That is, the contingent use of reinforcement and other important principles to increase behaviors, generalize learned behaviors or reduce undesirable behaviors is fundamental to ABA. Applied Behavior Analysis also involves the notion of demonstrating efficacy. It is essential that individuals using ABA evaluate the interventions to determine their efficacy and make modifications as needed to insure consistent and ongoing progress. The most important component of ABA involves the notion of “socially significant behaviors to a meaningful degree”. It is imperative that programs and interventions focus on outcomes for the learners that will have socially significant consequences and that this change is to a meaningful degree.[2]

Characteristics of Applied Behavior Analysis (ABA)[3]

Baer, Wolf, and Risley's 1968 article are still used as the standard description of ABA. It lists the following seven characteristics of ABA.

  • Applied: ABA focuses on the social significance of the behavior studied. For example, a non-applied researcher may study eating behavior because this research helps to clarify metabolic processes, whereas the applied researcher may study eating behavior in individuals who eat too little or too much, trying to change such behavior so that it is more acceptable to the persons involved, to others, and to society as a whole.
  • Behavioral: ABA is pragmatic; it asks how it is possible to get an individual to do something effectively. To answer this question, the behavior itself must be objectively measured. A behavior scientist cannot resort to the measurement of non-behavioral substitutes, such as a verbal description.
  • Analytic: Behavior analysis is successful when the analyst understands and can manipulate the events that control the behavior. This is relatively easy to do in the lab, where a researcher is able to arrange the relevant events, but it is not always easy, or ethical, in an applied situation. Baer et al. outline two methods that may be used in applied settings to demonstrate control while maintaining ethical standards. These are the reversal design and the multiple baseline design. In the reversal design, the experimenter first measures the behavior of choice, introduces an intervention, and then measures the behavior again. Then, the intervention is removed or reduced, and the behavior is measured yet again. The intervention is effective to the extent that the behavior changes and then changes back in response to these manipulations. The multiple baseline method may be used for behaviors that seem irreversible. Here, several behaviors are measured and then the intervention is applied to each in turn. The effectiveness of the intervention is revealed by changes in just the behavior to which the intervention is being applied.
  • Technological: The description of analytic research must be clear and detailed so that any competent researcher can repeat it accurately. Cooper et al. describe a good way to check this: Have a person trained in applied behavior analysis read the description and then act out the procedure in detail. If the person makes any mistakes or has to ask any questions then the description needs improvement.
  • Conceptually Systematic: Behavior analysis should not simply produce a list of effective interventions. Rather, to the extent possible, these methods should be grounded in behavioral principles. This is aided by the use of theoretically meaningful terms, such as "secondary reinforcement" or "errorless discrimination" where appropriate.
  • Effective: Though analytic methods should be theoretically grounded, they must be effective. If an intervention does not produce a large enough effect for practical use, then the analysis has failed
  • General: Behavior analysts should aim for interventions that are generally applicable; the methods should work in different environments, apply to more than one specific behavior, and have long-lasting effects.

See Also

Behavioral Data


Further Reading