SPED 8013 | Chapter 7: Analyzing Behavior Change-Basic Assumptions and Strategies

Concepts & Assumptions Underlying the Analysis of Behavior

  • Determinism
  • Empiricism
  • Experimentation
  • Replication
  • Parsimony
  • Philosophic Doubt

“The overall goal of science is to achieve an understanding of the phenomena under study”

In applied behavior analysis – the phenomena of interest is socially significant behavior

  • Science enables various degrees of understanding at three levels
    • Description
    • Prediction
    • Control

Experimental Control: The Path to and Goal of Behavior Analysis

  • Experimental control (defined)
    • A predictable change in behavior (dependent variable) can be reliably produced by the systematic manipulation of some aspect of the person’s environment (independent variable)
  • Experimental analysis (defined)
    • Experimentally determining the effects of environmental manipulation on behavior and demonstrating that those effects can be reliably produced
    • Can be achieved when
      • A reliable functional relation between behavior and some specified aspect of the environment has been demonstrated convincingly
  • Internal Validity
    • The extent to which an experiment shows convincingly that changes in behavior are a function of the independent variable and not the result of uncontrolled or unknown variables
    • Studies without a high degree of internal validity
      • Yield no meaningful statements about functional relations
      • Lack generality
    • Confounding variables are those variables known or suspected to exert an uncontrolled influence on the dependent variable
    • The effects of confounding variables must be evaluated and eliminated to demonstrate experimental control

“the goal of experimental design is to eliminate as many uncontrolled variables as possible and to hold constant the influence of all other variables except the independent variable, which is purposefully manipulated to determine its effects”

Behavior: Defining Features and Assumptions that Guide its Analysis

  • Defining Features
    • Behavior is an individual phenomenon
      • Behavior
        • a person’s interaction with the environment
      • Groups of people do not behave
      • Experimental strategy of ABA is based on within-subject (single-subject) methods of analysis.
    • Behavior is a dynamic, continuous phenomenon
      • Changes over time
      • Requires continuous measurement over time
        • Complete record of behavior as it occurs in context
        • Systematic repeated measurement is the “hallmark” of ABA
  • Assumptions
    • Behavior is determined
      • The occurrence of any event is determined by the functional relations it holds to other events
      • Behavior is a natural phenomenon
    • Behavior variability is extrinsic to the organism
      • Variability is the result of environmental influence such as,
        • The independent variable under investigation
        • Some uncontrolled aspect of the experiment
        • Uncontrolled or unknown factor outside of the experiment

Behavioral Variability: Most Commonly Held Assumption in Psychology and Other Social/Behavioral Sciences

  • The assumption of intrinsic variability
    • An intrinsic characteristic of the organism
    • Distributed randomly among individuals in any given population
      • In ABA we make the assumption that behavioral variability is the result of environmental influence
  • Methodological Implication
    • Attempting to experimentally control or investigate variability is a waste of time
    • By averaging the performance of individual subjects within large groups — the random nature of variability can be statistically controlled or cancelled out
    • Experimental manipulations of the factors suspected of causing variability
      • Search for causal factors
  • In practice
    • Applied behavior analysis seek treatment variables robust enough to overcome variability

Component of Experiments in ABA

  • At least one
    • Subject or participant
    • Behavior (dependent variable)
    • Setting
    • Treatment or intervention condition (independent variable)
  • A system for measuring the behavior and ongoing analysis of the data
  • Manipulations of the independent variable so that its effects on the dependent variable, if any, can be detected
    • experimental design
  • Research Question
    • “A brief but specific statement of what the researcher wants to learn from conducting the experiment” -Johnston & Pennypacker, 1993b, p.366
    • What are the effects of the independent variable on the dependent variable
      • For what population and in what setting?
  • Subject(s)
    • In single-subject research the subject is employed as his or her own control
      • Measures of the subject’s behavior during each phase of the study provide the basis for comparing experimental variables as they are presented or withdrawn in subsequent conditions
  • Behavior(s)
    • Dependent variable(s)
  • Reasons for multiple dependent measures
    • Provide data patterns that can serve as controls for evaluating and replicating the effects of an independent variable
    • Assess the presence and the extent of the independent variable’s effect on behaviors other than the response class to which it was directly applied
    • Determine whether changes in the behavior of a person other than the subject occur during the course of an experiment and if such changes can explain changes in the subject’s behavior
  • Setting
    • “Control the environment and you will see order in behavior” -Skinner, 1967, p. 399
  • Control two sets of environmental variables to demonstrate experimental control
    • Independent variable
      • Presenting, withdrawing, or varying its value
    • Extraneous variables
      • Prevent unplanned environmental variation

Measurement System and Ongoing Visual Analysis

  • Observation and recording procedures must be conducted in a standardized manner
  • Standardization involves every aspect of he measurement system
    • Definition of the target behavior to scheduling of observations
  • Behavior analysts must develop skills in the detection of changes in the level, trend, and degree of variability in behavioral data

Intervention or Treatment: Independent Variable

  • Independent variable (defined)
    • The particular aspect of the environment that the experimenter manipulates to find out whether it affects the subject’s behavior
    • The researcher controls or manipulates this variable independent of the subject’s behavior or any other event

Experimental Design

  • Experimental Design– Defined
    • The particular arrangement of conditions in a study so that meaningful comparisons of the effects of the presence and absence of the independent variable can be made
  • Nonparametric Study
    • Independent variable is either presented or absent during a time period or phase of the study
  • Parametric Study
    • The value of the independent variable is manipulated
    • Seeks to discover the differential effects of a range of values

Fundamental Rule

  • Change only one variable at a time
    • Experimenter can attribute any measured changes to a specific independent variable
    • If investigating the effects of a “treatment package”
      • Ensure that the entire package is presented or withdrawn each time a manipulation occurs

Some Additional Rules

  • Don’t get locked into “Textbook” designs
    • Often require priori assumptions about the nature of the functional relations one seeks to investigate
    • May be insensitive to unanticipated changes in behavior
  • Select and combine experimental tactics that best fit the research question

Steady State Strategy & Baseline Logic

  • “A pattern of responding that exhibits relatively little variation in its measured dimensional quantities over a period of time” – Johnston & Pennypacker, 1993a, p.199 (In other words behavior is stable)
  • Provides the basis for baseline logic
  • Steady State Strategy
    • Repeated exposure of a given subject to a given condition while trying to eliminate or control extraneous influences on behavior and obtaining a stable pattern of responding before introducing the next condition

Nature and Function of Baseline Condition

  • Serves as a control condition
  • Does not imply the absence of intervention
    • Absence of a specific independent variable
  • Why?
    • To establish a baseline level of responding to use the subject’s performance in the absence of the independent variable as an objective basis for detecting change
  • Applied benefits of establishing a baseline level of responding
    • To obtain descriptions of antecedent-behavior-consequence correlations for the planning of an effective treatment
    • Valuable guidance in setting initial criteria for reinforcement
    • Baseline data may reveal the behavior targeted for change does not warrant intervention

Types of Baseline Data Patterns

  • Stable Baseline (A)
  • Ascending baseline (B and C)
  • Variable baseline (D)

Prediction

“The anticipated outcome of a presently known or future measurement. It is the most elegant use of quantification upon which validation of all scientific and technological activity rests” – Johnston & Pennypacker, 1980

Prediction is (indicated in the chart to the left), having the known Steady State Response, predicting that this will be the outcome, and the outcome resulting in that state. In other words:

Affirmation of the Consequent: Inductive logic – If the independent variable were not applied, the behavior, as indicated by the baseline data path, would not change. If A-then-B statement.

 

So then, when the behavior does not follow the A-then-B path, this allows the experimenter to begin to affirm that the manipulation of the independent variable has led to a change in behavior (as reflected in chart right). Because if the variable hadn’t been manipulated (If we hadn’t intervened) the behavior wouldn’t have changed.

 

 

Verification

  • Verification of a previously predicted level of baseline responding by termination or withdrawal of the treatment variable (indicated in below chart)

So we are making an assumption that the target behavior would have stayed at baseline if we hadn’t intervened, but we do not know that for certain. So we need verification. So in order to get verification, we go back to baseline. In other words…

  1. Step one is baseline with the prediction that without intervention behavior will stay at baseline
  2. Step two is introduction of the treatment. If the behavior changes than we can begin to assume that the intervention may have caused the change but we do not know this for certain so we must continue to step three.
  3. Step three reintroduce baseline with the prediction that the behavior will remain the same as it did in the treatment phase. If the behavior once again drops to the original baseline level verification has occurred that manipulation of the independent variable (treatment) was the cause of the behavior change. However, this is only strong evidence and not enough. More is needed….

Replication

“Replication is the essence of believability” Baer, Wolf, & Risley, 1968, p.95

  • Replication of the experimental effect accomplished by reintroducing the treatment variable (indicated in below chart)