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What is “Analysis of Behavior”? Functional Analysis of Behavior • Two ways to classify behavior: – Structurally: • what are the components of the behavior; what is its structure? • What is the topography of the behavior – Functionally: • what is the function of the behavior? What is its purpose? • What is the behavior gaining the organism? • What is the behavior’s reinforcement history/ Response Functions • Think of behavior as a performance that follows a specific stimulus and results in a particular consequence: • S+: R C (Sr or P) – – – – S+ = predictive stimulus (S- predicts the contingency won’t happen) R = response Sr = reinforcer P = punishment • Can analyze behavior using 3-step analysis: the ABCs of Behavior! – A: antecedents: what are the setting conditions/stimuli – B: Behavior: what is the structure/topography of the response – C: Consequences: what reinforcer or punisher follows the behavior • Determining the ABCs of behavior help determine the function of the response But what is a Response? • Response (R)= an integrated set of movements or a behavioral performance. • Two basic classes of responses – Respondent: really classical conditioning – Operant: instrumental or operant conditioning But what is a Response? Functional Responses Classes Response Class Respondent Operant Function Controlling Event Elicited Stimulus(event) preceding the response Emitted Stimulus or event FOLLOWING the response Responses • Elicited Responses: – No consequence controls this behavior – Classical conditioning – Often reflexive or innate behaviors (but not always) • Emitted Responses: – Operant behavior: consequence controls this behavior – Will have a reinforcement function (what does it get you?) – Discriminative function: Can come under discriminative control by a discriminative stimulus or stimuli Stimulus Classes • Stimuli have different functions, as well – Defined by common effect on behavior – Not defined by the similarity of the stimuli, but on their FUNCTION • Discriminative stimuli: – Serve as a cue for particular behaviors – Bring that behavior under stimulus control – E.g.: Stop signs result in a particular behavior • Reinforcing stimuli – Again defined by their function, not their similarity – Here we get a four-square of behavior • Reinforcement: positive and negative • Punishment: positive and negative Motivation of Behavior • Context of behavior matters: – Stop signs: • if walking, typically don’t STOP at a stop sign • Driving: do STOP at a stop sign • Using Normal Theater as lecture hall: any problems with context of behavior? – Deals with setting conditions: – What conditions “set” the contingency? • Motivational operation (MO): – any environmental change that has a motivational operation has 2 major effects – any event that alters the reinforcement effectiveness of behavioral consequences and – changes the frequency of the behavior maintained by those consequences Two basic kinds of MOs • Establishing operation: EO: – Change increases the momentary effectiveness of reinforcement supporting operant behavior – Change increases momentarily the responses that had in the past produced such reinforcement • Abolishing operation: AO: – Decreases momentary effectiveness of reinforcement and – Momentarily decreases rate of response Conducting Behavioral Research from a Behaviorist Perspective • Make use of basic tactics of research: – Independent variable; Dependent variable – Correlational research or experimental method – But: use SMALL N Designs rather than group designs! • Interested in behavior change in an individual – Use individual as own control – In ABA, important that behavior change is functional and clinically significant – Allows evaluation of small groups and individuals – NOT interested in the mean, but in individual behavior change Small N designs • Small N designs use a small number of subjects: – Also called single- case designs – Research designs that use the results from a single participant or small number of subjects to establish the existence of cause- and- effect relationships. • Does not provide researchers with a set of scores from a group of subjects, but examines change in behavior of an individual across a set of conditions. • Presentation and interpretation of results from a small N design experiment are based on – Visual inspection of a simple graph of the data – In experimental analysis, also statistical analysis 11 Example 12 Limitation • With just a baseline/intervention phase, the results as presented do not represent a true experiment because there is no control over extraneous variables. • Showed a change, but cannot conclude causation just yet….. 13 Phases and phase changes • A phase: series of observations of the same individual under the same conditions. • Baseline: observations when no treatment is being administered • Treatment: Observations when the treatment IS administered 14 3 types of baseline • Stable level – Data generally flat, no high/low – May bounce around a bit, but can show no gains or losses • Stable trend: – Data show a stable upward or downward trend – Importance is in stability of the trend. • Unstable data: – No consistency – This is undesirable for a baseline! 15 3 types of baseline 16 Dealing With Unstable Data • The researcher can simply wait; occasionally, a participant reacts unpredictably to the novelty of being observed. • Consider the average of a set of two (or more) observations. • Look for patterns within the inconsistency. – For example, a researcher examining disruptive classroom behavior may find that a student exhibits very high levels of disruption on some days and very low levels on other days. – E.g., days she has a swimming lesson 17 Next: Apply an Intervention • Implement for several observations • Again, establish stability in your data to demonstrate change Length of a Phase • To establish a pattern ( level or trend) within a phase and to determine the stability of the data within a phase, a phase must consist of a minimum of three observations. • Why? Three points make a line! – Allows you to (hopefully) determine the direction of behavior change – May need more if data are unstable 19 When to Change Phases • Wait: • When the data in a baseline phase show a trend indicating improvement in the client’s behavior • a researcher should not intervene by introducing a treatment phase. • Don’t Wait: • If baseline data indicate a seriously high level of dangerous or threatening behavior. • Researcher probably should not wait for the full set of five or six observations necessary to establish a clear pattern. • Stopping Treatment: – If a treatment appears to produce an immediate and severe deterioration in behavior, – Stop the treatment IMMEDIATELY 20 Visual Inspection Techniques • Unfortunately, there are no absolute, objective standards for determining how much of a change in pattern is sufficient to provide a convincing demonstration of a treatment effect. • The most convincing results occur when the change in pattern is immediate and large. 21 4 types of change • Change in average level: – change in average baseline rate and average treatment rate • Immediate change in level – Compare the last point in one phase with the first point in the following phase • Change in trend: – Compare the slope of the trend in baseline with the shape of the trend in treatment • Latency of change. – Compare the latency of change in baseline with latency of change in treatment. 22 23 2- immediate change in level 24 Change in Trend 25 Latency in change 26 The problem with single subject design: Need to find a way to show causation 27 THE ABAB REVERSAL DESIGN • The majority of small N research studies use some form of the ABAB design • Consists of four phases: – – – – A baseline phase ( A) Followed by treatment ( B) Then a return to baseline ( A) Finally a repetition of the treatment phase ( B). • Why end with a treatment? 28 Effective 29 Not Effective 30 Limitations of the ABAB Design • The implemented treatment has corrected a problem behavior, and when the treatment is removed, the correction continues. • A second problem with an ABAB design concerns the ethical question of withdrawing a successful treatment. 31 Variations on the ABAB Design 32 B not working, introduce C 33 B not working add C B= Graduated exposure C= Reinforcement 34 MULTIPLE- BASELINE DESIGNS • Uses multiple baselines and multiple interventions (hence the name!) – – – – Across stimuli Across environments Across individuals Across behaviors • Eliminates the need for a return to baseline and therefore • Is particularly well suited for evaluating treatments with long- lasting or permanent effects. 35 Person1 Person2 2 different students 36 Yelling Crying 2 different behaviors 37 School Home 2 different situations. 38 Weaknesses of the Multiple- Baseline Design • Risk that a treatment applied to one behavior may generalize and produce changes in the second behavior. • E.g., Treating stuttering may help treating aggressive behavior • Or: getting a great “down” for your dog results in loss of the “sit” • Solution: chart and monitor behavior change in both • This could be good OR bad change 39 Weaknesses of the Multiple- Baseline Design • One behavior may show a large and immediate change, but the second behavior may show only a minor or gradual change when the treatment is introduced. • Floor and ceiling effects • Treatments may have different levels of effect on different behaviors • Can convert data to proportions to see if it is a measurement issue • The same problem can occur with research involving different participants with similar behavior problems. 40 Dismantling design • Dismantling design – Also called a component- analysis design – Consists of a series of phases in which each phase adds or subtracts one component of a complex treatment – Allows one to determine how each component contributes to the overall treatment effectiveness. 41 Example 42 The Changing- Criterion Design • The criterion level is changed from one phase to the next. • Add to, take away or change criterion – E.g., out of seat behavior: • Phase 1: 5 out of seats/day • Phase 2: 3 out of seats/day • Phase 3: 1 out of seat/day 43 Smoking Treatment 44 The Alternating- Treatments Design • Also called a discrete-trials design, • Two ( or more) treatment conditions – Randomly alternated from one observation to the next. – No set schedule; subject doesn’t know which is coming when • E.g., scent enrichment in zoo animals 45 Example 1- Alternate weeks 46 Example 2- 9 cases for each method 47 GENERAL STRENGTHS OF SMALL N DESIGNS • Conducted with only one participant or a very small (N~5) group. • Tends to be much more flexible than a traditional group study. • Single- subject designs require continuous assessment. 48 General Weaknesses Of Single- Subject Designs • Participant’s behavior may be affected not only by the treatment conditions but also by the assessment procedures. – Sometimes measuring behavior changes it – Draws attention to the behavior; subject alters behavior • Another concern for single- subject designs can be absence of statistical controls. – Can address this with additional statistical measures designed for behavior analysis – Typically included in EAB research; now seeing more and more in ABA research 49 In Summary • Functional analysis is determining the function of the behavior: What purpose is the behavior serving for the person? • Behaviorists tend to use small N or single subject designs focusing on individual behavior change • Behaviorists use different forms of the experimental method but CAN show cause and effect! • The behavioral approach is not “instead of” the traditional experimental approach, but provides an alternative level of analysis.