Single-Subject Design

Overview of Single Case Research Methodology in Psychology and Behavior Analysis

These notes outline the key features, designs, and evaluation methods of single case research methodologies, often used within psychology and behavior analysis.

Terminology and Definitions

  • APA and APA Style: The style guide adopted by the American Psychological Association.

  • Participants vs. Subjects: The terminology shifted from "subjects" to "participants" in research studies.

  • Single Subject Design: A method of research that focuses on individual cases or a small number of cases (N=1). It includes various synonymous terms:

    • Single participant design

    • Intra subject replication design

    • N equals one research

    • Intensive designs

    • Repeated measures designs

    • Clinical research model/design

    • Time series design/analysis

General Features of Single Case Design

  1. Continuous Assessment:

    • Emphasis on repeated measurements over time during different phases (baseline, intervention, follow-up).

    • Distinction from traditional pre-post measures in psychological studies, which may only compare performance once before and once after an intervention.

  2. Baseline Assessment:

    • Baseline Phase (A phase): Observations collected at multiple time points before the intervention begins (minimum of three measurements required).

    • Measurements should use the same methodology consistently (e.g., partial interval recording across all observations).

    • Importance of the baseline: A stable baseline allows for more confident conclusions regarding intervention effectiveness.

    • Labeling: The baseline is designated as "A" and the intervention as "B" for sequential clarity: A (baseline phase), B (intervention phase).

  3. Trend Observation:

    • Critical in discerning patterns across observed phases.

    • The requirement for at least three measures allows for the calculation of trends in data during both baseline and intervention phases.

Examples of Behavior Trends

1. Stable Baseline:

  • Description of an ideal stable baseline in behavior (e.g., self-injurious behavior).

  • Observations showed consistent measurements across multiple days.

2. Increasing Baseline:

  • An increasing trend prior to the intervention can complicate conclusions regarding the efficacy of the intervention.

  • When behavior naturally increases before an intervention is implemented, attributing changes to the intervention becomes problematic.

3. Decreasing Baseline:

  • Similarly, if behavior is already decreasing before the intervention, it can challenge the clarity of causality regarding the intervention.

4. Variable Baseline:

  • Describes variability in measurements that may reflect different environmental influences at certain times.

  • Emphasizes the need to observe patterns to inform potential problem-solving interventions (e.g., changing seating arrangements).

Types of Single Case Designs

  1. AB Design:

    • Simplest design: Baseline followed by treatment.

    • Limited experimental rigor; practical for individual clients.

    • Not substantial for publication due to lack of control over external variables.

  2. ABAB Design (Reversal Design):

    • Extends AB design by including a return to baseline (A) and a return to the treatment phase (B).

    • Implements a stronger claim of intervention effects by demonstrating behavior returns upon removal of treatment.

    • Ethical considerations involved regarding removal of effective interventions.

  3. Multiple Baseline Design:

    • Involves multiple participants (e.g., P1, P2, P3) and staggered start points for interventions across individuals.

    • Enhances reliability of results by minimizing external factors impacting all subjects simultaneously.

Data Evaluation in Single Case Research

Visual Analysis:

  • Changes in Means:

    • Comparison of mean performance across phases (baseline vs. intervention).

    • Documenting changes in level provides insights into intervention efficacy.

  • Trends:

    • Identifying upward or downward trends during intervention phases relative to baseline data.

  • Changes in Latency:

    • Time taken for changes to manifest post-intervention.

    • Faster changes can underscore intervention effectiveness.

  • Non-Overlapping Data Points (NDP):

    • Percentage of intervention data points that do not overlap with baseline data points.

    • Higher percentages indicate stronger intervention effects.

Statistical Techniques

  • Effect Size (Cohen's d):

    • Magnitude of change expressed in standard deviation units derived from the mean differences between phases.

    • Important for contextualizing results, especially in academic research settings.

Cautions and Considerations

  • Blocking Data:

    • Avoid blocking data to oversimplify or misrepresent variability.

  • Graphical Representation:

    • The type of graph (line vs. bar) can influence interpretations significantly.

Conclusion

  • This summary touched on crucial elements of single case research methodologies, including definitions, designs, observations of behavior trends, and methodologies for evaluating data. These components are essential for effectively conducting and interpreting single case research in psychology and behavior analysis.

  • Ethical implications and understanding practical versus scientific rigor are fundamental considerations during intervention assessments.

  • Future discussions in research design classes will delve deeper into these complexities and their applications within practical settings.