1. ABAB Design Ethical considerations
Is it ethical to remove a treatment that appears to be beneficial (i.e., implement the second “A” baseline stage)?
Dilemma between goal of understanding and goal of creating change.

2. Multiple-Baselines Design
The multiple-baselines design solves this ethical problem.
Also uses a comparison between baseline and treatment
Does not withdraw treatment
establish several baselines
implement treatment in one baseline at a time
Multiple baselines can be implemented
across situations
One individual observed in several situations
across individuals
Several individuals are observed
across behaviors
Several behaviors of one individual are measured

3. Multiple-Baselines Design
Comparing baseline to treatment
Observing individual(s) behavior(s) across time to establish baselines
Implement treatment when there is a steady baseline
Only implement one treatment at a time for a particular baseline
To interpret the treatment
If treatment is effective, behavior changes when the treatment is implemented and does not change for the remaining baselines.
Behavior changes only when the treatment is implemented and directly following the introduction of treatment.

4. Multiple-Baselines Design
Multiple baseline across situations
Example of Leslie with selective mutism
Would speak at home but not in other situations
Target several situations; restaurant, meeting adults, playing with peers
Start collecting baseline data in these situations
Several baselines started around the same time
Apply treatment to one situation at a time
In this case treatment was role playing with reinforcement at home

6. Multiple-Baselines Design
Multiple baselines across individuals
Example: Allison and Ayllon (1980)
evaluating the effectiveness of a behavioral coaching on athletics
procedures included systematic verbal feedback, positive and negative reinforcement
Establish baselines for each of the individuals
Start baselines around the same time
When the behavior has stabilized
An intervention is introduced one individual at a time

7. Multiple-Baselines Design

8. Multiple-Baselines Design
Multiple baseline across behaviors
Example:
A schoolteacher is using a behavioral intervention that will help manage the behavior of a problem child in the classroom.
The child does not stay at her desk when asked to do so, does not remain quiet during “quiet times,” and exhibits other behaviors that disrupt the teaching environment.
Use a positive reinforcer such as tokens or small toys in a multiple-baseline across behaviors design to improve the child’s behavior.

9. Multiple-Baselines Design
Multiple-baselines across behaviors:
Behavior #1: Leaving desk.
Implement treatment (reward system) on Day 3
Behavior improves (decrease in frequency)

10. Multiple-Baselines Design
Multiple-baselines across behaviors:
Behavior #2: Blurt out questions without raising hand
Implement treatment (reward system) on Day 6
Behavior improves (decrease in frequency)

11. Multiple-Baselines Design
Multiple-baselines across behaviors:
Behavior #3: Not quiet during quiet times
Implement treatment (reward system) on Day 8
Behavior improves (decrease in frequency)

12. Multiple-Baselines Design
How many baselines are needed?
A minimum of two; three or four are recommended.
FIGURE 9.3 Frequency of spoon-banging responses across baseline, treatment, and follow-up phases of study
What if behavior changes before the intervention?
The reasons for behavior change become hard to interpret; researchers analyze the situation to see if some aspect of treatment generalized.
What if the treatment generalizes to other behaviors, situations, or individuals?
Researchers should try to anticipate when generalization may occur and modify their research design accordingly.

13. Problems with All Single-Subject Designs
Problems with Baseline Records
Unstable baselines
increasing, or decreasing trends in behavior, the effects of treatment are hard to interpret.
Extreme variability in baseline behavior
difficult to detect a clear discontinuity in behavior when treatment is implemented.
Solutions:
Look for factors that may contribute to variability
wait for baseline behavior to stabilize
average baseline data points across observations.

14. Problems with All Single-Subject Designs Problems with Baseline Records

15. Problems with Single-Subject Designs
Baseline Records,
Whether increasing or decreasing baseline trends are a problem depends on the desired direction of behavior change.
Suppose the goal is to increase the frequency of a behavior.
If the baseline shows an increasing frequency of behavior, determining whether behavior increases following treatment will be difficult.
However, if the baseline shows a decreasing trend and treatment reverses this trend, we can be confident about the effect of the treatment.

16. Problems with Single-Subject Designs
External Validity
Single-subject designs are frequently criticized for their limited external validity.
Will treatment effects observed for one individual generalize to other individuals?
Reasons why external validity may not be limited:
Treatments are usually powerful.
Multiple-baselines designs can be used to demonstrate generality of effects.
Group treatment can be used to demonstrate effectiveness of treatment.

17. Quasi-Experimental Designs Chapter Ten
Goal: To improve the conditions in which people live and work.
Natural settings: Messy, “real world” — hard to establish experimental control.
Quasi-experiments: Experimental procedures that approximate the conditions of highly controlled laboratory experiments.
Program Evaluation: Applied research used to learn whether real-world treatments work.

18. Experiments in Natural Settings.
Researchers do experiments in natural settings for several reasons
Test the external validity of a laboratory finding
Attempt to improve conditions under which people live and work
Determining if a treatment is effective
make decisions about continuing the treatment
make decisions about spending money
make decisions about investing more time and effort
Natural Settings: such as schools, work place, government, hospitals, playground, etc.

19. Characteristics of True Experiments
True experiments have a high degree of control
manipulate an independent variable
random assignment to conditions
hold conditions constant
Allows comparison of treated to untreated groups
A true experiment is one that leads to an unambiguous outcome regarding what caused a result on the dependent variable.
However, this much control usually can not be done in a natural setting so there is less internal validity.
A trade off between better external validity and less internal validity

20. Differences between experiments in the lab and in natural settings
Experiments that are conducted outside the laboratory are likely to differ in a number of significant ways from those done in the laboratory.
Control in experiments from
manipulation of I.V.
random assignment of participants
hold other factors constant
External validity
Better in natural settings then the laboratory
Goals
basic laboratory research to understanding how things work will have very good internal validity
Applied research in natural settings tries to improve the lives of people and has internal validity
Consequences
Applied research in a natural setting can impact large numbers of people
For example: Head Start program, Sesame Street program
Sometimes referred to as “social experiments”

21. FIGURE 10.1 As a social experiment, Sesame Street was designed to improve the education of hundreds of thousands of children.

22. Obstacles to Conducting True Experiments in Natural Settings
Obtaining permission and gaining access to participants
Can not get a random sample of participants
Random assignment of participants
Random assignment is the best way to determine if a new treatment really is effective
May not be able to use random assignment because of intact groups such as classrooms of children
Also can be viewed as unfair because some people who may need treatment don’t receive it.
A waiting-list control group may be used so that people randomly assigned to the control group receive treatment after the study is completed.