D.7 Distinguish among reversal, multiple-baseline, multielement, and changing-criterion designs
Single-subject experimental designs are research designs commonly used in applied behavior analysis (ABA) to investigate the effects of interventions or treatments on an individual subject. These designs allow researchers to establish a functional relationship between the independent variable (intervention) and the dependent variable (behavior) within a single participant. Here are some examples of single-subject experimental designs.
Distinguishing among reversal, multiple-baseline, multielement, and changing-criterion designs involves understanding the unique characteristics of each experimental design used in single-case research to evaluate the effects of an intervention on behavior. Each design has its own structure and is applied in different scenarios based on the research question or clinical needs.
Multiple Baseline Design
This design involves sequentially implementing the intervention across different baselines or behaviors. The intervention is introduced at different times for each baseline, allowing for comparison of behavior change across baselines. For example, in a study on the effectiveness of a reading intervention, the intervention may be introduced to one student in a staggered manner across different subjects or reading skills.
Strengths of Multiple Baseline Design
Control over extraneous variables: By sequentially implementing the intervention across different baselines, the multiple baseline design allows for control over extraneous variables that could influence the behavior. This design minimizes the likelihood that other factors, such as maturation or history, are responsible for observed changes in behavior.
Demonstrates functional relationship: The design provides strong evidence of a functional relationship between the intervention and the behavior change. If the behavior consistently changes only after the introduction of the intervention across different baselines, it supports the claim that the intervention caused the behavior change.
Ethical considerations: In situations where it may be ethically inappropriate or impractical to withdraw an effective intervention, the multiple baseline design offers a way to assess the effects of the intervention without removing it. This makes it particularly useful when studying interventions that have positive ethical implications.
Generalization of effects: By implementing the intervention across different behaviors, individuals, or settings, the multiple baseline design allows for the examination of generalization effects. It helps determine if the behavior change is specific to the target behavior or if it extends to other related behaviors or settings.
Weaknesses of Multiple Baseline Design
Limited experimental control: While the multiple baseline design offers some control over extraneous variables, it is less rigorous than designs with random assignment or control groups. The lack of a concurrent control group limits the ability to confidently establish a cause-and-effect relationship.
Practical limitations: Implementing the intervention across multiple baselines may require more time, resources, and coordination compared to other designs. It can be challenging to ensure the intervention is implemented consistently across the different baselines, which may introduce variability in the results.
Potential for contamination: There is a risk of contamination between baselines, especially if the participants or settings are closely related. If participants or settings interact or share information during the study, the intervention’s effects may inadvertently spread to the other baselines, which can compromise the internal validity of the design.
Limited inference to within-subject effects: The multiple baseline design primarily allows for inferences within the individual subject, rather than making broader population-based inferences. It is more suitable for investigating individual behavior change rather than generalizing to a larger population.
Delayed Multiple Baseline
A delayed multiple baseline design is similar to the multiple baseline design, but with a delay in the introduction of the intervention across baselines. This design allows for replication and control of the intervention’s effects. For instance, in a study on the effectiveness of a math intervention, the intervention may be introduced to three students, but with a delay of one week between each student.
Strengths of Delayed Multiple Baseline Design
Control over confounding variables: Similar to the multiple baseline design, the delayed multiple baseline design allows for control over confounding variables. By introducing the intervention at different times across baselines, researchers can assess whether the observed behavior change is indeed a result of the intervention rather than other factors.
Replication and internal validity: The delayed multiple baseline design offers the opportunity to replicate the effects of the intervention across multiple baselines. By implementing the intervention sequentially with a delay, researchers can establish a strong internal validity by demonstrating consistent behavior change across different contexts or individuals.
Practical considerations: The design may be more feasible in situations where implementing the intervention simultaneously across multiple baselines is not practical. It allows researchers to stagger the intervention introduction, potentially reducing the burden of implementing the intervention simultaneously across multiple settings or participants.
Ethical considerations: Similar to the multiple baseline design, the delayed multiple baseline design is advantageous when it may be ethically inappropriate or impractical to withdraw an effective intervention. It allows researchers to assess the effects of the intervention without removing it, providing a balance between ethical considerations and scientific inquiry.
Weaknesses of Delayed Multiple Baseline Design
Limited experimental control: The delayed multiple baseline design lacks the strict experimental control of designs with random assignment or control groups. It is vulnerable to potential confounding factors or alternative explanations for the observed behavior change.
Potential for contamination: As with the multiple baseline design, contamination between baselines is a concern in the delayed multiple baseline design. If participants or settings interact or share information during the study, the effects of the intervention may unintentionally spread across baselines, undermining the internal validity of the design.
Limited generalizability: The delayed multiple baseline design primarily focuses on within-subject behavior change rather than making population-based inferences. While it provides valuable insights into individual behavior change, its applicability to a broader population may be limited.
Time and resource requirements: Implementing the delayed multiple baseline design can be time-consuming and resource intensive. The staggered introduction of the intervention across baselines may prolong the duration of the study, requiring additional resources and participant commitment.
Researchers should consider these strengths and weaknesses when deciding to use the delayed multiple baseline design. It is crucial to evaluate the research question, practical constraints, and the balance between experimental control and ecological validity in determining the most appropriate design for a specific study.
Multiple Baseline Probe Design
In this design, multiple behaviors or settings are assessed during a baseline phase, and the intervention is introduced simultaneously across all behaviors or settings. The effects of the intervention are then measured. For example, in a study on the effects of a communication training program for a child with autism, the child’s communication skills may be assessed across different settings (e.g., home, school, clinic), and the intervention is implemented in all settings simultaneously.
Strengths of Multiple Probe Design
Practicality and efficiency: The multiple probe design is often considered practical and efficient, particularly in situations where it may be challenging or impractical to implement a traditional baseline phase for each behavior or setting. Instead, the behaviors or settings are assessed during a baseline probe, reducing the time and resources required.
Flexibility in implementation: This design allows for flexibility in implementing the intervention across multiple behaviors or settings simultaneously. Researchers can introduce the intervention in all behaviors or settings once the baseline probe phase is completed, facilitating a quicker assessment of the intervention’s effects.
Generalization and ecological validity: By assessing multiple behaviors or settings during the baseline probe phase, the multiple probe design provides an opportunity to examine the generalization of effects. It helps determine if the intervention’s effects extend to various contexts, settings, or behaviors, enhancing ecological validity.
Demonstrates functional relationship: Similar to other single-subject experimental designs, the multiple probe design allows researchers to demonstrate a functional relationship between the intervention and behavior change. The intervention is implemented after a stable baseline probe phase, providing evidence that the behavior changes as a result of the intervention.
Weaknesses of Multiple Probe Design
Potential for limited control: Compared to designs with a traditional baseline phase, the multiple probe design may have less experimental control over confounding variables. Since the intervention is implemented after the baseline probe phase, there is a possibility that other factors may influence the behavior during that time.
Vulnerable to maturation or history effects: The absence of a baseline phase for each behavior or setting makes the design susceptible to maturation or history effects. Changes in behavior observed during the baseline probe phase may be attributed to factors other than the intervention itself, limiting the internal validity of the design.
Limited data during baseline: The multiple probe design typically involves a shorter baseline probe phase compared to traditional baseline phases. This results in a limited amount of data collected during the baseline, which may affect the stability of the behavior and the accuracy of assessing the intervention’s effects.
Potential for reactivity: Participants may become aware of the upcoming intervention due to the repeated assessment of the baseline probe phase. This awareness can lead to reactivity, where participants may alter their behavior in anticipation of the intervention, potentially confounding the results.
Reversal Design (ABA Design)
This design involves systematically withdrawing the intervention (A) after a stable baseline phase (B) and reintroducing the intervention (A) again. This allows researchers to evaluate whether the behavior changes as a result of the intervention. For instance, in a study on the effectiveness of a self-monitoring intervention for increasing study time, the intervention may be withdrawn during a specific phase to observe if the behavior decreases.
Strengths of Reversal Design
Strong demonstration of experimental control: The reversal design allows researchers to establish a strong cause-and-effect relationship between the intervention and behavior change. By systematically withdrawing the intervention (A) after a stable baseline phase (B) and then reintroducing the intervention (A) again, researchers can demonstrate that the behavior changes correspond to the presence or absence of the intervention.
Internal validity: The design helps address concerns about internal validity by controlling for potential confounding variables. By replicating the baseline and intervention phases, researchers can determine if the observed behavior changes are indeed a result of the intervention and not influenced by other factors.
Within-subject comparison: The reversal design enables researchers to compare behavior within the same individual. This within-subject comparison enhances the design’s sensitivity to detecting intervention effects because it accounts for individual differences that might exist between participants.
Ethical considerations: The design is particularly advantageous in situations where it may be ethically inappropriate or impractical to withdraw an effective intervention. Instead of removing the intervention completely, the design allows for temporary withdrawal, minimizing ethical concerns while still assessing the intervention’s effects.
Weaknesses of Reversal Design
Ethical considerations: While the reversal design offers ethical advantages in some situations, there are instances where withdrawing a beneficial intervention may not be ethically justifiable. It is crucial to carefully consider the potential impact on participants and ensure that their well-being is prioritized.
Limited generalizability: The reversal design primarily focuses on within-subject behavior change, which may limit its generalizability to broader populations. The design does not account for individual differences that may exist between participants, making it challenging to generalize findings beyond the specific individual studied.
Practical constraints: Implementing the reversal design can be time-consuming and resource-intensive. The design requires multiple phases and repetitions, which may increase the duration of the study and the burden on participants and researchers.
Potential for carryover effects: Carryover effects occur when the effects of the intervention persist or influence subsequent phases of the study. These effects can impact the accuracy of evaluating behavior changes during different phases and may introduce confounding factors that affect the design’s internal validity.
Alternating Treatment Design (AKA Multielement Design)
This design involves rapidly alternating between two or more interventions to compare their effects. Each intervention is implemented in a separate condition, and the impact on the behavior are assessed. For example, in a study comparing two different teaching methods for teaching vocabulary, the methods are alternated within sessions to evaluate their impact on learning.
Strengths of Alternating Treatment Design
Efficiency and practicality: The alternating treatment design is often considered efficient and practical, particularly when comparing the effects of multiple interventions or treatments. It allows for rapid alternation between different treatments within the same session or observation period, reducing the time required to assess the effects of each intervention.
Direct comparison of interventions: This design enables researchers to directly compare the effects of different interventions within the same individual. By alternating treatments, researchers can evaluate the immediate impact of each intervention on the target behavior, allowing for a more direct and comparative analysis.
Individualized assessment: The alternating treatment design allows for individualized assessment and identification of which intervention is most effective for a particular individual. It recognizes that different interventions may work better for different individuals and provides a means to determine the most effective intervention for each person.
Ecological validity: By implementing multiple interventions in a naturalistic and real-world context, the alternating treatment design enhances ecological validity. It reflects the variability of treatment options available in real-life situations, providing a more accurate representation of the treatment effects in everyday settings.
Weaknesses of Alternating Treatment Design
Limited experimental control: The design may have less experimental control compared to other designs that involve a single treatment or control group. Factors such as carryover effects or order effects could influence the results, making it challenging to establish a clear cause-and-effect relationship between the interventions and behavior changes.
Limited experimental control: The design may have less experimental control compared to other designs that involve a single treatment or control group. Factors such as carryover effects or order effects could influence the results, making it challenging to establish a clear cause-and-effect relationship between the interventions and behavior changes.
Limited generalization: The alternating treatment design primarily focuses on within-subject comparisons, limiting its generalizability to broader populations. The results may not be applicable to individuals who were not directly involved in the study, as individual differences and specific contextual factors may play a significant role in the outcomes.
Potential for reactivity: Participants may become aware of the alternating treatment design and alter their behavior accordingly. They may exhibit reactivity or respond differently to interventions due to the awareness of the intervention alternation, potentially confounding the results.
Changing Criterion Design
In this design, the intervention is implemented in phases with progressively changing criteria for success. The behavior is evaluated as the criteria change to assess the effects of the intervention. For instance, in a study on the effects of a self-reinforcement program for increasing physical exercise, the criteria for successful exercise may be gradually increased over time.
Strengths of Changing Criterion Design
Experimental control: The changing criterion design allows for strong experimental control over the intervention and its effects. By systematically and gradually changing the criteria for behavior change, researchers can establish a clear cause-and-effect relationship between the intervention and the behavior.
Gradual behavior change: This design allows for a gradual and systematic change in behavior, which can be particularly useful when the behavior change needs to be achieved incrementally. The design provides a structured approach to shaping behavior by setting specific criteria for progress.
Flexibility in criterion implementation: Researchers have flexibility in setting and adjusting the criteria for behavior change in the changing criterion design. They can tailor the criteria to match the specific needs and capabilities of the individual or situation, allowing for a more individualized approach to behavior change.
Generalization of behavior change: The changing criterion design facilitates the examination of generalization effects. By systematically increasing the criteria in multiple behaviors, settings, or individuals, researchers can determine if the behavior change extends beyond the initial target behavior, indicating broader generalization of the intervention effects.
Weaknesses of Changing Criterion Design
Time and resource-intensive: Implementing the changing criterion design can be time-consuming and resource-intensive. Gradually increasing the criteria for behavior change requires multiple measurement points and a longer study duration, which may pose practical challenges in terms of participant commitment and resource allocation.
Limited control over external factors: While the design provides experimental control over the intervention, it may have limited control over external factors that could influence the behavior change. Factors such as concurrent interventions or external events may impact the behavior during the study, potentially confounding the results.
Potential for reactivity: Participants may become aware of the changing criterion design and alter their behavior in response to it. This reactivity can affect the internal validity of the design and introduce biases in the observed behavior change.
Limited generalizability: The changing criterion design primarily focuses on within-subject behavior change, which may limit its generalizability to broader populations. The design may not capture individual differences or account for contextual factors influencing behavior change in different individuals or settings.
BAB Design
This design is similar to the reversal (ABA) design, but without reintroducing the intervention. The behavior is measured during a baseline phase (B), followed by an intervention phase (A), and then another baseline phase (B). This design allows for assessing the intervention’s effect by comparing the behavior during the intervention phase with the two baseline phases.
Strengths of BAB Design
Strong demonstration of experimental control: The BAB design allows for a strong demonstration of experimental control by systematically manipulating the intervention and observing the corresponding changes in behavior. The design includes a baseline phase (B), an intervention phase (A), and a return to baseline phase (B), allowing researchers to establish a cause-and-effect relationship between the intervention and behavior change.
Replication and internal validity: By replicating the baseline and intervention phases, the BAB design enhances internal validity. The design demonstrates that the behavior changes when the intervention is introduced and returns to baseline levels when the intervention is removed, providing evidence of the intervention’s influence on behavior.
Ethical considerations: The BAB design is advantageous when withdrawing an effective intervention may be ethically inappropriate or impractical. Instead of permanently removing the intervention, the design allows for a temporary return to the baseline phase, minimizing ethical concerns while assessing the intervention’s effects.
Individualized assessment: The BAB design allows for an individualized assessment of behavior change. Each participant serves as their own control, which accounts for individual differences and increases the design’s sensitivity to detecting intervention effects.
Weaknesses of BAB Design
Ethical considerations: While the BAB design offers ethical advantages in some situations, there are instances where withdrawing a beneficial intervention may not be ethically justifiable. It is crucial to carefully consider the potential impact on participants and prioritize their well-being.
Limited generalizability: The BAB design primarily focuses on within-subject behavior change, which may limit its generalizability to broader populations. The design does not account for individual differences between participants, making it challenging to generalize findings beyond the specific individual studied.
Potential for carryover effects: Carryover effects occur when the effects of the intervention persist or influence subsequent phases of the study. These effects can impact the accuracy of evaluating behavior changes during different phases and may introduce confounding factors that affect the design’s internal validity.
Time and resource requirements: Implementing the BAB design can be time-consuming and resource-intensive. It requires multiple phases and repetitions, which may increase the duration of the study and the burden on participants and researchers.