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Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine the Effects of an Intervention with an Aggressive Adolescent male

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Page 1: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Linda Heitzman-PowellUniversity of Kansas Medical Center

Rachel WhiteIntegrated Behavioral Technologies, Inc.

Data-Based Decisions: Using Data to Determine

the Effects of an Intervention with an

Aggressive Adolescent male

Page 2: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Despite the efficacy of employing function-based treatments, non-specific strategies designed to decrease challenging behaviors are implicated under certain conditions:◦ when maintaining variables cannot be identified or

controlled, ◦ when the challenging behavior must be reduced

rapidly, ◦ when function based treatment is not sufficient

enough (Lerman & Vorndran, 2002), or◦ when the target behaviors are unresponsive to

reinforcement techniques (Luiselli, 1984).

Introduction

Page 3: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Jonathan received a diagnosis of Autism when he was four years old. Jonathan has a history of severe aggression, observed both in home and at school. He also has a history of chronic ear infections. His aggression appears to escalate when he is experiencing an infection in his ears. His school aggression was severe enough to warrant a placement in LakeMary Center, an alternative placement for children whom are not able to be served in their home school setting. His home aggression was severe enough that a case manager recommended therapeutic foster-care placement. In June, his current case manager began the reintegration process with in-home behavioral supports. Jonathan currently is on multiple medications to manage his aggressions.

Meet Jonathan

Page 4: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Interview◦ Parent◦ Caregivers◦ School

Observation◦ School◦ Home

Real-time data collection Frequency Duration Intensity

ABC data

Page 5: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Operational Definitions

Intensity Scale

Defining Data

Page 6: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Jonathan engages in a series of behaviors that disrupt his, and others, environments. These behaviors include repetitive vocalizations, hitting, spitting, self-injury, injury to others and property destruction. An event will be considered over when Jonathan has exhibited a quiet body (hands, feet, mouth, and voice) for at least 5 minutes. A new event will be recorded if at least 5 minutes have passed since the end of a previous event.

Page 7: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

1 = pacing or perseverative statements (“moo moo”)

2 = crying or whining 3 = jumping or stomping 4 = screaming or yelling 5 = kicking or tripping 6 = property damage or slamming objects 7 = hitting, grabbing or pushing 8 = scratching or pinching 9 = biting 10 = self-injurious behavior

Intensity Scale

Page 8: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Frequency◦ Number per day

Intensity◦ Based on scale with behavioral anchors

Duration◦ Based on time

Page 9: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine
Page 10: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine
Page 11: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Function-based Intervention◦Possible functions (suggested by observation and ABC data) Escape from non-preferred activities Access to tangible reinforcers

Page 12: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Functional Communication Training ◦ Escape

“No thank you” for immediate removal of non-preferred activities

◦ Access “Water (or any other item he might want)

please” ◦ However, escape and access to reinforcers were

not always plausible (e.g., activities regarding personal hygiene, access to dangerous materials)

Page 13: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine
Page 14: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine
Page 15: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Access to reinforcers not contingent upon any particular behavior – delivered on a continuous schedule

No-demand

Page 16: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

BL FCT NCR/No Demand

Page 17: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine
Page 18: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine
Page 19: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine
Page 20: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

BL FCT NCR/No Demand In-Patient Schedule Extinction Quiet Room

Page 21: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

BL FCT NCR/No Demand In-Patient Schedule Extinction Quiet Room

Page 22: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

One of the more acceptable and less aversive procedures to de-escalate challenging behavior is contingent effort (Luce, Delquadri, & Hall, 1980).

Several studies demonstrated the effectiveness of contingent effort in decreasing challenging behavior beyond or in the absence of reinforcement based intervention. (Experiment I; Luce et al., 1980).

Additionally, contingent effort (stacking rings) significantly decreased aggression in both residential and classroom settings (Jackson, Tyminski, Frederick, Neary, & Luce, 2005).

Contingent Effort

Page 23: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Despite successful uses of de-escalation procedures, these studies were conducted at residential or school settings and the extent to which the effectiveness and utility of contingent effort as a de-escalation procedure at home setting has not been well reported.

Therefore, the present study examined the effectiveness of an existing de-escalation procedure (Jackson et al., 2005) modified for use in the home.

Contingent Effort (cont.)

Page 24: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Intervention was conducted at home and during family community outings

Materials: ◦1 ring stacking base◦5 color rings

Setting and Materials

Page 25: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Design◦ Baseline (non-effective contingency

management & FCT) Alternating Treatments

◦ Treatment Changing Criterion

Initially, during the treatment phase, on the first occurrence of aggression, the child was:◦ Prompted to move to a designated room by

parents or staff ◦ Instructed to sit down and engage in a de-

escalation contingent effort (i.e., stacking rings).

◦ Required to complete the task calmly (no incidents of aggression) for a period of two minutes.

Procedures

Page 26: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

As aggression began to decrease, the criterion for contacting “ring stacking” changed:◦ Pre-cursor behaviors were targeted

1st criterion change targeted 3 instances of verbal escalation 2nd criterion change targeted 2 instances of verbal escalation 3rd criterion change targeted 1 instance of verbal escalation

If any incidents of aggression occurred during all criterion phases, the task was re-presented until he completed the task with no aggressive incidents for two minutes.

Rings and the stacking base were available when the child went on an outing

Procedures (cont.)

Page 27: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

An Antecedent-Behavior-Consequence (ABC) chart was filled out by parents or staff upon the occurrence of aggression.

Aggression was defined as any attempt to hit, scratch, pinch, bite, kick, grab or push a person.

◦Intensity of each aggressive episode was scored on a scale of 1 to 10

◦Duration data was also recorded

Data Recording

Page 28: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

-505

101520253035404550556065707580859095

100

Jul-0

4Aug Sep Oct Nov

Dec

Jan-

05Feb M

ar AprM

ay Jun Ju

lAug Sep Oct Nov

Dec

Jan-

06Feb M

ar Apr

04 av

e.

Months

Num

ber

of I

ncid

ence

s

-1

0

1

2

3

4

5

6

7

8

9

10

Number of aggressive episodes

Average intensity

True BL (Med change only)

Med. Changes, FCT, No DemandAntecedent Control, Consequential Control, etc., Time-out

Contingent EffortBaseline for Contingent Effort

Intervention - Changing Criterion

Aggressions Pre-Cursors 3 2 1

All Recorded Incidents

Page 29: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Behaviors◦ Silliness◦ Non-compliance◦ Inappropriate Language

Conditions◦ Access

Contingent upon expression of the behavior, the student was given the item for 15s

◦ Escape Contingent upon expression of the behavior, the

materials were removed and the student was given escape from the task 15s

◦ Play No demands; free access to reinforcers

Page 30: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Attention◦ Noncontingent Reinforcement

Timer set for 20m When the timer goes off, Mom/Dad spend 2-3 minutes

◦ Functional Communication Teaching

Teach phrases such as “look at me”, “play with me” etc. In the presence of a NO-demand situation (free-time)

Model functional communication Require an imitative response

Escape◦ Extinction

In the presence of a demand: Do not attend or respond Continue to present demand

Page 31: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Fre

quen

cyFunction-based Intervention

0

2

4

6

8

10

12

14

16

June06

July Aug Sept Oct Nov Dec Jan'07

Feb March April May June July Aug Sept Oct Nov Dec

Aggression

Precursors

Page 32: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Reduced overall number of aggressive behaviors from around 4 episodes per month to 0-6 (first month only) by the end of the reporting period.

The intervention also reduced pre-cursor behaviors from between 10 and 14 to between 0 and 4 per month.

Results – Function-based Intervention

Page 33: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Contingent effort can be effectively implemented in a home setting even when trained staff are not readily available.

The same procedure has been successfully implemented at his school given the success at home.

As the challenging behavior is decreasing, the focus of the intervention needs to shift from decreasing challenging behavior to function-based interventions.

Discussion

Page 34: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Staffing needs◦ 2004-2005

1:1 25+ hours per week 8-10+ hours per month from consultant

◦ 2005-2006 1:1 15-25 hours per week 4-6 hours per month from consultant

◦ 2007 1:1 10-15 hours per week 2-4 hours per month from consultant

◦ 2008-2009 1:1 <10 hours per week As needed (approximately 2 visits in 2 years)

Discussion (cont.)

Page 35: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Jackson, A., Tyminski, J., Frederick, L., Neary, P., & Luce, S. (2005, May). Decreasing aggressive behavior: Utilization of contingent effort as a de-escalation procedure. Poster session presented at the annual meeting of the Association for Behavior Analysis, Chicago, IL.

Lerman, D. C. & Vorndran (2002). On the status of knowledge for using punishment: Implications for treating behavior disorders. Journal of Applied Behavior Analysis, 35, 431-464.

Luce, S. C., Delquadri, J., & Hall, R.V. (1980). Contingent exercise: A mild but powerful procedure for suppressing inappropriate verbal and aggressive behavior. Journal of Applied Behavior Analysis, 13, 583-594.

Luiselli, J. K. (1984). Therapeutic effects of brief contingent effort on severe behavior disorders in children with developmental disabilities. Journal of Clinical Child Psychology, 13, 257-262.

References

Page 36: Linda Heitzman-Powell University of Kansas Medical Center Rachel White Integrated Behavioral Technologies, Inc. Data-Based Decisions: Using Data to Determine

Contact InformationLinda Heitzman-Powell

[email protected] of Kansas Medical Center

3901 Rainbow Blvd. Phone (913) 945-6604

Rachel [email protected]