Research methods commonly employed by behavior analysts.

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Read through these scenarios. Each scenario corresponds to one of the single-subject research methods commonly employed by behavior analysts.
Scenario 1 Multiple Baseline Design: Suppose you have two preschool students who engage in disruptive behavior in the classroom, and you want to evaluate an intervention to decrease the disruptive behavior. Describe how you would use a multiple baseline across subjects design to evaluate the intervention in this scenario.
Scenario 2 Withdrawal Design: Juan acts out in class and makes jokes at inappropriate times. The teacher believes that he is exhibiting this behavior to gain her attention. How would you use a withdrawal design to determine if, in fact, Juan is trying to gain the teacher’s attention?
Scenario 3 Alternative Treatments Design: Susan is trying to develop an exercise routine for herself. She wants to determine if she does better sticking to a routine if she participates regularly in a structured class, or if she exercises alone using equipment she has in the home, like workout videos, weight bench, bicycle, et cetera. How would you use an alternating treatment design to determine which type of exercise routine is most effective for Susan?
Scenario 4 Changing Criterion Design: Bob is a heavy smoker. He has chosen to try to stop smoking gradually instead of cold turkey. He has set a quit date for the end of the month. How would Bob use a changing criterion design to help track his progress as he attempts to quit smoking?
Complete the following for each scenario:
Describe how you would apply that design to achieve the desired results.

Sample Solution

Scenario 1: Multiple Baseline Design

Applying the design:

  1. Baseline: Collect data on the disruptive behavior of both students for a consistent period (e.g., number of disruptive incidents per hour).
  2. Intervention: Introduce the intervention to decrease disruptive behavior for Student A while continuing to collect data on both students’ behavior.
  3. Evaluation: If Student A’s disruptive behavior decreases significantly while Student B’s behavior remains unchanged, it suggests a functional relationship between the intervention and the decrease in disruptive behavior for Student A.
  4. Introduce intervention for Student B: After demonstrating effectiveness for Student A, introduce the same intervention for Student B and continue data collection for both students.
  5. Evaluation: If Student B’s disruptive behavior also decreases following the introduction of the intervention, it further strengthens the evidence for the intervention’s effectiveness.

Key point: The staggered introduction of the intervention across subjects allows for a strong demonstration of causality by ruling out alternative explanations for behavior change.

Scenario 2: Withdrawal Design

Applying the design:

  1. Baseline: Collect data on the frequency of Juan’s inappropriate jokes during class.
  2. Intervention: Implement an intervention where the teacher completely ignores Juan’s inappropriate jokes (extinction).
  3. Evaluation: If Juan’s joke-telling behavior decreases significantly, it supports the hypothesis that he was seeking attention.
  4. Withdrawal: Return to baseline conditions by providing attention to Juan’s inappropriate jokes.
  5. Evaluation: If Juan’s joke-telling behavior increases, it further strengthens the evidence that attention was reinforcing the behavior.

Note: A withdrawal design can be ethically challenging, especially if the behavior is harmful. It’s essential to consider alternative designs or to implement the intervention continuously if it’s effective.

Scenario 3: Alternating Treatments Design

Applying the design:

  1. Identify conditions: Establish two treatment conditions: structured exercise class and home-based exercise.
  2. Alternate conditions: Randomly alternate between the two exercise conditions on different days.
  3. Data collection: Collect data on exercise adherence (e.g., days attended, duration, intensity) for each condition.
  4. Evaluation: Compare the data for both conditions to determine which condition results in higher adherence.

Key point: Rapidly alternating between treatments allows for direct comparison and helps control for extraneous variables.

Scenario 4: Changing Criterion Design

Applying the design:

  1. Baseline: Establish a baseline of Bob’s daily cigarette consumption.
  2. Set criteria: Set progressively decreasing criteria for daily cigarette consumption (e.g., 20 cigarettes per day, then 15, then 10, etc.).
  3. Intervention: Implement strategies to meet the changing criterion (e.g., nicotine replacement therapy, behavioral strategies).
  4. Evaluation: Monitor Bob’s cigarette consumption daily to determine if he meets the specified criteria.
  5. Adjust criteria: Once Bob consistently meets a criterion, lower it to the next level.

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