Disequilibrium Approaches
A newer model!
Goal of behavior analysis/operant
conditioning
• Clarify control of human behavior by reinforcement contingencies
– many techniques have been developed
– used in wide variety of settings
• Problem: specifying ahead of time what works:
– no a priori way of determining what will be a reinforcer
– makes for problems in applied settings
– even lab research affected by this
• what usually do: reinforcer assessments
– time consuming
– not very accurate
Successful approach to a priori assessment
should satisfy 3 practical requirements
Identification of Rs circumstances should involve:
• a small number of simple, nonintrusive procedures
– must be widely applicable
– require no special apparatus
– no novel or disruptive stimuli to be introduced
• must be accurate and complete
• result should be adaptable to variety of situations,
rather than limited to small number of stimuli,
responses or settings
Transituational Solution:
conceptual Analysis
• Meehl, 1950: Transituationality of Reinforcement
– simplest method for figuring out what works: use what circumstances
have worked in the past
– if works in one setting, should work in others
• Three important assumptions about reinforcing stimuli and their "setting
conditions"
– reinforcers and punishers form unique, independent sets of
transituationally effective stimuli
– essential function of the contingency = produce temporally proximate
pairings between response and reinforcer
– deprivation schedule specifying long-term denial of access to
reinforcer = critical setting condition
Transituational Solution:
conceptual Analysis
• Problem:
– none of these holds up to data
– The assumptions are incorrect!
• reinforcers and punishers are not mutually exclusive nor are they
transituational
• eg. Premack: drinking and wheel running could reinforcer each
other
• applied settings see this all the time
• temporal contiguity not sufficient to produce reinforcement:
• Premack (1965): pairing wheel running w/drinking had no effect in
absence of contingency schedule
• appear that contingency is key, not time
• long term deprivation not necessary nor sufficient: short term deprivation
works
Application problems w/this approach:
• STILL is most often used technique
• Assessment techniques are intrusive
• Often NOT effective: reinforcers change over time
– Does not account for satiation effects, etc.
– Not account for different situations
– In applied world, do a reinforcer assessment once and assume it stays!
• Lacks flexibility, accuracy
• Ethical questions when using food, certain punishments
Premack's Probability Differential
Hypothesis: (Grandma’s Law)
• Premack (1959; 1965): distinct improvement over transituational view
– schedule in which a higher probability response is contingent upon a lower
probability response will result in reinforcement
– if you eat your peas (low prob) then you can have chocolate pudding (high
prob)
• important change in concept of reinforcement in several ways:
– reinforcement is related to access to a response
– probability of response determined by probability (duration) of that response
in FREE BASELINE
• shows that transituational situation is special case of probabilitydifferential:
– highest probability response contingent upon a lower probability response
– as long as is highest probability- should be transituational
Premack's Probability Differential
Hypothesis: (Grandma’s Law)
• Some problems, however:
– incomplete and unclear about several things:
– fails to specify conceptual rules for setting values of
contingency schedule:- pair 1:1, 5:1 or what?
• Unclear about role of reduction in contingent
responding relative to baseline that typically
accompanies an increase in instrumental responding
• Unclear about role of long-term deprivation
Application
• Probably most widely used behavioral technique
• Popularity due to several desirable characteristics:
– procedures for identification are clear, relatively non-disruptive
– more accurate than transituational method
– allows for far wider choices of Sr's and P's
• Problems even in applied arena:
– duration of discrete response hard to measure
– duration not always a good measure
– problem in that must always use higher probability responses as
reinforcers
– time consuming to measure baselines
Response Deprivation and
Disequilibrium Approach
• Assumption: reinforcement results from adaptation of motivational
processes underlying free baseline responding to the performance
constraints imposed by a contingency schedule
• What's that?
– are constraining behavior that would naturally occur in free baseline
to a set contingency schedule
– only allowing free baseline behavior to occur at certain levels, rates,
times
– restrict via a contingency schedule
• really looking at molar equilibrium theory:
– free baseline = equilibrium state
– disrupt this equilibrium state via a contingency schedule
– assumes assessment of free-baseline of instrumental and contingent
responding before imposition of contingency schedule
Response Deprivation and
Disequilibrium Approach
• does NOT view baseline as stable hierarchy of
reinforcement value:
– estimate of relative motivation underlying different
responses
– that is- can change from situation to situation
– Idea that just must disrupt baseline ratio and you create
behavioral effects
• by imposing different contingencies- can create
reinforcement and punishment conditions:
– response deficit: reinforcement
– response excess: punishment
Definitions
• I = instrumental response:
– The response you have to do to get the “reinforcer”
– Putting dishes in the dishwasher
• C = contingent response
– The response that serves as the reinforcer
– Watching TV
• Oi = amount of instrumental response that you will do with NO
contingency (free baseline)
– If no contingency, how often would you freely load the dishwasher?
• Oc = amount of contingent response that you will do with NO
contingency (free baseline)
– If no contingency, how often would you freely watch TV
Response deficits
• Response deficit: I/C >Oi/Oc
– If individual maintains instrumental responding at
baseline level, would engage in less of baseline level
of contingent responding
– thus: if I continue to eat my baseline level of peas, I
would engage in less chocolate pudding eating (than
baseline)
– I/C = 1/25
• 2 peas; 50 spoonful chocolate pudding
– Oi/Oc: 1/100
– 1 pea; 100 cc’s of chocolate pudding
– Thus: 1/25 > 1/100
Response satiation
• Response excess: I/C < Oi/Oc
– Is the individual maintains instrumental responding at
baseline level, would engage in too much of baseline
level of contingent responding
– if I hit my sister at baseline levels, I would engage
in/receive more spankings than I engaged in/received
during baseline
– I/C: 1/1
• 1 hit; 1 spanking =
– Oi/Oc: 1000/1
• 1000 hits; 1 spankings
– Thus: 1/1 < 1000/1
Why an improvement?
•
improvement for several reasons:
– specifies rules for setting terms of schedule:
– I/C > Oi/Oc for reinforcement effects
– I/C < Oi/Oc for punishment effects
•
•
•
•
I = instrumental response
C = contingent response
Oi = baseline rate of instrumental response
Oc = baseline rate of contingent response
•
no limitations on units for measuring baseline behaviors, as long as keep same in
contingency setting and ratio
•
sets NO restrictions on what can be a reinforcer or a punisher
•
note: lower probability response can reinforcer higher probability response, as
long as setting conditions are met
•
shows that long term denial is NOT necessary:
– Critical: allows for deprivation or disequilibrium within a session
– long term denial is special case of this
Applications
•
Several desireable reasons for using:
–
–
–
–
•
procedures specific
relatively non-disruptive
more accurate
allows incredible flexibility- no set reinforcers or punishers
Examples: Konarski (1980):
– grade school kids
– free baseline of coloring or working simple arithmetic problems
•
Konarski (1985): EMH classroom
– retarded children
– working arithmetic problems and writing
•
incidental teaching
– behavior contracting: Dougher study (1983)
– good behavior game
– overcorrection: punishment technique
Incidental teaching and the Minimum bliss
point model
Farmer-Dougan, 1998
• Bitonic relationship between rate of reinforcement
imposed by a schedule and strength of reinforcement effect
– Response rate first increase then decrease as reinforcer rate
increases
– When schedule provides very high rate of reinforcement
(disrupts disequilibrium only slightly) – little change in
instrumental responding
– When schedule provides very low rate of reinforcement
(disrupts disequilibrium to high degree), little net reinforcement
effect
• Thus, extreme rates of reinforcement should be less
effective than moderate rates
Can mathematically predict
reinforcement effects!
• Simple FR schedule: according to minimum distance
models, R rate that produced by ratio schedule is equal
to:
–
–
–
–
R1 = predicted rate of response
Oi is rate of unconstrained instrumental response
Oc is rate of unconstrained contingent response
K is number of units reinforcement/response (inverse of FR
requirement)
Predict an Inverted U-shaped function
Incidental teaching
• Accurately IDs reinforcers and increases generalization and
maintenance via use of naturalistic teaching
• Involves capturing a teaching moment (Hart and Risley, 1980)
– Subject initiates (verbally/physically) toward an item or activity
– Teacher immediately imposes contingency such that access to the
item/activity is blocked until the contingent response is emitted
– Immediate assessment of baseline and immediate imposition of
momentary disequilibrium
• Question: how often to disrupt?
– Minimum bliss models suggest that moderate amounts should be
better than high interruption or very low interruption
Method
•
4 head start preschoolers
•
Worked 1:1 in workroom at Head
Start
•
Set of toy items for each child, and
set of 26 flash cards containing letters
A to Z
Task: ID letter expressively to gain
access to toy
•
•
Manipulated rate of disruption:
–
–
–
–
–
Baseline (0)
25%
50%
75%
100%
Results!
• Little academic behavior
when did not disrupt (
– surprisingly, there was
some
– but differed by child
– Shows differences in
baseline rates
• Too much disruption = no
academic responding!
• Moderate levels worked
best!!
Limitations on/Extensions of
Disequilibrium approach
• not completely accurate
– how to measure baseline for individual subjects
– time consuming nature of measuring baseline
– only takes into account 2 behaviors (I and C), while
many more behaviors occur in any contingency setting
• Question of time frames: do baselines change
w/time?
– Does constraining baseline affect or reset baseline?
Conclusions
• Strong need to predict reinforcement ahead of
time
– if can't- not very usable concept
– early theories did not do this very well
• Reinforcers and punishers aren't things:
– no magic wand
– reinforcement/punishment effects depend upon
extent to which contingency schedule constrains the
free distribution of responding