Understanding Description, Prediction, and Control in Applied Behavior Analysis

Welcome to a comprehensive exploration of the core goals in Applied Behavior Analysis (ABA) as a science: description, prediction, and control. These goals are foundational in our pursuit to understand and influence behavior effectively. Let’s delve into each concept, providing definitions, examples, and distinctions to clarify their roles in ABA.

Levels of Understanding in ABA

Description

Description involves collecting and documenting facts about observed events. This foundational level provides the raw data that can be quantified, classified, and examined for relationships with other known facts. It is through description that we form hypotheses and guide further research

Examples of Description in ABA:

• Direct Observation: Collecting ABC (Antecedent-Behavior-Consequence) data to identify patterns.
• Baseline Data Collection: Recording behavior frequency before intervention to understand the initial state.
• Indirect Observation: Conducting interviews and reviewing records to gather contextual information.

These methods help behavior analysts gather comprehensive information about the behavior of interest, setting the stage for deeper analysis.

Prediction

Prediction is achieved when there is a systematic covariation between two events. By identifying these patterns, we can predict the likelihood of one event occurring based on the presence of another. However, predictive studies do not involve the manipulation of variables and thus cannot establish causality.

Examples of Prediction in ABA:

• Steady State Responding: Achieving consistent behavior patterns during baseline data collection allows for predictions about future behavior if no intervention is applied.
• ABC Observation Data: Correlating specific consequences with behaviors to hypothesize about their functions.

Predictive data guide the design of interventions by providing a basis for understanding how behavior might change under different conditions

Control

Control represents the highest level of understanding in ABA. It is achieved when specific changes in one event (the dependent variable) are reliably produced by manipulations of another event (the independent variable), while ruling out the influence of extraneous factors.

Examples of Control in ABA:

• Experimental Designs: Utilizing single-subject designs such as ABAB (reversal), multiple baseline, and changing criterion designs to demonstrate that behavior changes are due to the intervention.
• Functional Analysis: Manipulating environmental variables to confirm hypotheses about behavior functions derived from prediction data.

Control is the ultimate goal in ABA, as it confirms that the intervention directly influences behavior change.

Applying Description, Prediction, and Control

In practice, ABA professionals utilize these levels of understanding to create effective behavior change programs. Description provides the necessary groundwork by offering a detailed account of the behavior and its context. Prediction uses this data to forecast future behavior patterns, guiding intervention planning and providing a comparison for data gathered within an intervention. Control ensures that the interventions produce effective and reliable behavior changes.