Single-Case Experimental Research Design — ABAB Reversal, Multiple-Baseline, and Component Analysis | Chapter 14 of Research Methods for the Behavioral Sciences

Chapter 14 of Research Methods for the Behavioral Sciences focuses on single-case experimental designs, an alternative strategy to group-based research that allows researchers to establish cause-and-effect relationships through intensive study of individuals. Unlike traditional experiments that rely on group averages, single-case designs use repeated measurements across baseline and treatment phases, making them especially valuable in applied and clinical settings.

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Single-Case Designs vs. Other Methods

Single-case designs are distinct from both group experiments and case studies. While case studies provide descriptive, qualitative insight into one individual, single-case designs involve systematic manipulation and control to demonstrate causal effects, making them experimental rather than purely descriptive.

Core Features of Single-Case Designs

These designs rely on repeated measures across phases, which include:

• Baseline phase (A): Behavior is measured without treatment to establish stability.
• Treatment phase (B): The independent variable is introduced and its effects measured.

Key evaluation criteria include level, trend, stability, latency of response, and immediacy of change following intervention.

ABAB Reversal Design

In the ABAB reversal design, researchers alternate between baseline and treatment phases:

• A = Baseline (no treatment)
• B = Treatment
• A = Return to baseline
• B = Reintroduction of treatment

This repeated cycle helps confirm that observed changes are truly due to the treatment rather than external factors. Ethical concerns may arise when withdrawing an effective treatment, particularly in clinical contexts.

Multiple-Baseline Designs

Instead of withdrawing treatment, researchers may stagger treatment across different baselines:

• Across subjects: Apply treatment to different participants at different times.
• Across behaviors: Apply treatment to different behaviors within the same participant.
• Across settings: Introduce treatment in different environments or contexts.

This method avoids ethical problems of reversal designs while still demonstrating treatment effects.

Component-Analysis Designs

These designs evaluate the effectiveness of individual elements within a treatment package. By adding or removing components systematically, researchers can identify which aspects of an intervention drive behavior change.

Visual Inspection and Data Analysis

Single-case research relies primarily on visual inspection of graphed data rather than statistical tests. Researchers examine:

• Average level changes across phases
• Shifts in trend direction
• Latency of behavioral changes after treatment introduction
• Immediacy and strength of observed effects

While this approach emphasizes clinical significance, it lacks the statistical precision of group-based designs and may require strong, visible effects to draw firm conclusions.

Strengths and Weaknesses

Strengths:

• Flexible and adaptable to clinical settings
• Allows demonstration of treatment efficacy with a single participant
• Supports individualized, real-time decision-making

Weaknesses:

• Limited external validity and generalizability
• Lack of formal statistical analysis
• Relies on strong, observable effects for conclusions

Conclusion

Chapter 14 demonstrates how single-case experimental designs provide powerful tools for applied psychology and clinical research. Through structures such as ABAB reversal, multiple-baseline, and component-analysis designs, researchers can establish causal effects in individual cases. While limited in generalizability, these designs excel in practical applications where group studies are not feasible, offering meaningful evidence of treatment effectiveness in real-world contexts.

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