# Overview of Withdrawal Designs

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Overview of Withdrawal Designs
Chapter 5

Withdrawal Designs Withdrawal- refers to the withdrawal of treatment during one or more phases of a study to demonstrate the effects that it has on the target behavior Typically represented by the letters A-B-A-B (A represents baseline, B represents intervention). Its more common name is reversal design.

A-B Design Most basic of all single subject designs
In this design the researcher collects baseline data (A) and then implements a treatment (B). This is done to determine its effect on target behavior.

Weakness of A-B Design Most weakest of all single subject designs since the functional relationship between the dependent and independent variables are not firmly established. There are several factors that can play a role on the dependent variable (e.g. maturation, practice effects).

Mechanics of Withdrawal Designs
The goal of withdrawal designs is to show a functional relationship between the target behavior and the intervention. This occurs when the experimental control is increased when the intervention is subsequently withdrawn so that baseline conditions are again in effect resulting in A-B-A design.

A-B-A Design First step Second step Third step
Define both the target behavior to be altered and the treatment to be implemented. Second step Collect baseline data (A) for at least 5 consecutive days or until baseline trend is established. Third step Introduce treatment (B) or intervention and collect continuous data either until a specific criterion has been met or until a stable mode of responding in the desired direction is recorded.

A-B-A Design cont. Fourth step
Withdraw treatment or return to baseline phase (A). If the target behavior improves in the desired direction during the intervention phase and changes toward baseline levels once the treatment is withdrawn, the experimenter can conclude that treatment was responsible for the improvement of target behavior.

A-B-A-B Design In this design experimenter must define the target behavior and the intervention to be used before collecting data. Involves a no-intervention baseline(A1) and an intervention phase (B1), with each phase being repeated (A2 & B2). The logic is to strengthen or validate the functional relationship between target behavior and treatment

Prediction, Verification, & Replication
Describes A-B-A-B design Predict- after stable baseline (A1) data are collected, one would predict that the same pattern would remain under the same conditions. However, if the treatment (B1)has an effect, one would predict that a different pattern would emerge.

Prediction, Verification, & Replication cont.
Verification- occurs when the change from baseline to intervention phase results in a change in responding. In other words it occurs when return to the baseline condition (A2) results in a pattern similar to the original baseline condition (A1).

Prediction, Verification, & Replication cont.
Replication- occurs when second treatment phase (B2) results in a similar response pattern as the previous treatment phase (B1). The reintroduction and withdrawal of the introduction more than once strengthens the evidence of prediction, verification, and replication.

Is one of the easiest single subject designs to implement. Possess great flexibility Can be used when the withdrawal of a particular treatment will reverse the target behavior to baseline, or pre-intervention levels.

When to use the withdrawal design:
When a clear functional relationship between the independent and dependent variables needs to be demonstrated When the nature of the target behavior is such that it can be reversed when the treatment is withdrawn When the nature of the treatment is such that its effects are not present on the target behavior after it’s withdrawn When withdrawal of treatment does not compromise ethics

The goal of the withdrawal design is antithetical to educational or clinical goals. Resentful Demoralization may occur,which means that individuals’ behaviors during subsequent baseline conditions might be negatively affected by resentment over having the treatment withdrawn. A great concern is using the withdrawal design with dangerous behaviors.

When not to use the Withdrawal Design
When the target behavior is not reversible. When the treatment effects will continue after the treatment is withdrawn When it is not educationally or clinically desirable for the behavior to return to baseline levels When the target behavior is such that withdrawal of effective treatment would be unethical (e.g. dangerous behavior).

Adaptations of the Typical Withdrawal Design
B-A-B Design: When the use of A-B-A or A-B-A-B design are not appropriate, the B-A-B design can be used. In this design the experimenter begins with the application of the independent variable (B phase). Once intervention phase produces stable responding at an acceptable level, the treatment is withdrawn.

The A-B-A-B-A-B (Repeated Withdrawals)
In this design the treatment variable is introduced and withdrawn repeatedly. Repeated withdrawals increase confidence in the functional relationship between the treatment and the target behavior.

The A-B-C (Changing Conditions)
In this design (A) represents baseline, B would indicate treatment 1, and C would indicate treatment 2. Any number of treatment conditions could be introduced (A-B-C-D or A-B-C-D-E) with the goal to end the design in an effective treatment condition.

The A-B-A-C Design (Multiple Treatments)
In this design, the C phase may be an alteration to the original treatment introduced in the B phase or it may represent a new treatment altogether. Investigator collects baseline data (A), introduces the intervention variable (B), and then withdraws it as in an A-B-A design. Then the investigator introduces a second intervention.

Multiple Treatment Design Considerations
Make sure that only one variable at a time is changed from one phase to the next. Understand limitations of the functional relationships established The time necessary to complete many experiments using this design with many phases can result in threats to internal validity. Note that a treatment that is offered only in combination with another cannot be adequately evaluated for its effectiveness alone.