The Effects of Delayed Reinforcement Through a Token Economy on the Treatment of Escape-Maintained Problem Behavior Without

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The Effects of Delayed Reinforcement Through a Token Economy on The Treatment of Escape-Maintained Problem Behavior Without

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Arts in the Graduate School of The Ohio State University

Elle M. Smith, B.A.

Graduate Program in Educational Studies

The Ohio State University

2017

Master's Examination Committee:

Nancy Neef, Advisor

Sheila Alber-Morgan

Copyrighted by

Elle M. Smith

2017

Abstract

Although extinction has a strong empirical documentation of success with decreasing problem behaviors, there are still several negative side effects associated with the treatment. To eliminate the negative side effects, researchers have successfully treated escape-maintained problem behaviors without the use of extinction using immediate primary reinforcement. The current study explored the use of delayed reinforcement using a token economy. The results of a multiple probe design indicated that the tokens eliminated problem behavior and increased compliance for 4 children diagnosed with

Autism Spectrum Disorder (ASD).

Dedication

This thesis is dedicated to my incredible parents who have always taught me that anything is possible with hard work. I would not be here without your amazing love and

support. Also to my incredible other half, Maxwell, thanks for standing by through the

madness over the years. I owe my sanity to you.

iii

Acknowledgments

I would first like to thank my advisor, Dr. Nancy Neef for her continual support and guidance through the countless edits and meetings regarding this project. I would also like to thank Dr. Shelia Alber-Morgan for her insightful revisions and feedback. Lastly, I would like to thank my dream team, Corinne Gist and Natalie Andzik for their countless hours of revision, guidance, recommendation, and data collection. I would not have been able to complete this project without you.

Vita

2011-2015 ...... B.A. Special Education, Aurora University

January 2017-present ...... Graduate Research Assistant, Department of

Education, Special Education – Applied

Behavior Analysis Program, The Ohio State

University

Fields of Study

Major Field: Educational Studies

Area of Emphasis: Special Education, Applied Behavior Analysis

Table of Contents

Abstract ...... ii

Acknowledgments...... iv

Vita ...... v

List of Tables ...... viii

List of Figures ...... ix

Chapter 1: Introduction ...... 1

Chapter 2: Method ...... 11

Chapter 3: Results ...... 20

Chapter 4: Discussion ...... 30

References ...... 38

Appendix A: Baseline Data Sheet...... 42

Appendix B: Treatment Data Sheet ...... 43

Appendix C: Baseline IOA Data Sheet ...... 44

Appendix D: Treatment IOA Data Sheet ...... 45

Appendix E: Baseline Treatment Fidelity Data Sheet ...... 46

Appendix F: Treatment Fidelity Data Sheet ...... 47

Appendix G: Social Validity Questionnaire 1 ...... 48

Appendix H: Social Validity Questionnaire 2 ...... 50

Appendix I: Social Validity Questionnaire 3 ...... 51

vii

List of Tables

Table 1. Social Validity Questionnaire 1 Results ...... 26

Table 2. Social Validity Questionnaire 2 Results ...... 26

Table 3. Social Validity Questionnaire 3 Results ...... 27

viii

List of Figures

Figure 1. Problem Behavior Treatment Data for all Participants ...... 24

Figure 2. Complinace Treatment Data for all Participants ...... 25

CHAPTER 1

INTRODUCTION

All behaviors are learned and maintained by the specific effects behavior has on the environment. Functional Analysis (FA) is used to determine why people engage in certain behaviors. By exposing a behavior to various conditions, a clinician can evaluate when the behavior is occurring most often and determine its function. Positive reinforcers

(i.e., social attention and tangible) are stimuli added to the environment and will increase the likelihood of the behavior occurring. On the other hand, negative reinforcers (i.e., escape) result in an aversive stimulus being removed from the environment that also results in increases the likelihood of the behavior occurring.

Five Options for Treating Escape-Maintained Behavior

Escape and social negative reinforcement are two of the most common functions of behavior for individuals with developmental disabilities (Geiger, Carr, LeBlanc, 2010).

In one large study, a functional analysis was conducted with 52 individuals with developmental disabilities who exhibited self-injurious behavior (Iwata, Pace, Dorsey et al., 1994). The results of the study indicated that the behavior of 35% of the individuals was maintained by escape (26% was maintained by automatic reinforcement and 23% was maintained by attention). In a similar study, researchers found that escape was the

1 primary function for 50% of the 32 participants diagnosed with ASD (Carr and LeBlanc,

2009).

There are 6 categories of evidence-based treatments that have been shown to treat escape-maintained problem behaviors. The treatments include (a) activity choice, (b) curricular and instructional revision, (c) non-contingent escape, (d) demand fading, (e) differential reinforcement, and (f) escape extinction (Carr and LeBlanc, 2009). Activity choice and curricular and instructional revisions are antecedent-based interventions that make changes to the environment before the stimuli are presented, thereby lowering the chance that the behavior will ever occur by reducing the aversiveness (Kern et al., 1998).

A limitation of activity choice is that the procedure does not include an explicit plan for responding to problem behavior, so a consequence-based intervention should be combined to further reduce problem behavior (Kern et al., 1998). Additionally, with curricular and instructional revisions, the procedure requires an expert to be able to assess and change the curriculum, which takes time and will not allow for immediate reductions in problem behavior (Dunlap & Kern, 1972).

Non-contingent escape (or reinforcement) (NCR) is delivered independent of the individual’s behavior. In lieu of teaching an alternative behavior, non-contingent breaks serve as an abolishing operation for the problem behavior by reducing the aversiveness of the present stimuli. This type of treatment has proven successful in reducing problem behavior, but has little impact on compliance (Kodak, Miltenberger & Romanuik, 2003;

Vollmer, Marcus, & Ringdahl, 1995).

Demand fading has decreased escape-maintained problem behavior by completely removing all aversive stimuli from instruction, and systematically reintroducing the stimuli over time (Iwata, Cowdery, Abdree & McIntyre 1993; Piazza, Moes, & Fisher,

1996). Demand fading was used by Pace et al. (1993) to decrease the rate of self- injurious behavior (SIB) in 3 individuals with developmental disabilities by fading the frequency of tasks. Even as the frequency of tasks was gradually increased, rates of SIB remained relatively low. A limitation to demand fading, is the loss of instructional time, which can cause disruption to classroom activities making it impractical to implement

(Zarcone et al., 1994).

Differential reinforcement is a more commonly implemented treatment (Vollmer

& Iwata, 1992). This can be implemented in two different forms including differential negative reinforcement of alternative behavior (DNRA) and differential negative reinforcement of other behaviors (DRNO). DNRA provides escape contingent on occurrences of specifically taught responses. Functional Communication Training (FCT) is a type of DNRA that has decreased escape-maintained problem behavior by providing escape contingent on the occurrences of a specific communicative event (Durand &

Merges, 2001; Hanley, Piazza, Fisher & Madlieri, 2005; Horner & Day 1991). An example of FCT, would include allowing escape from a non-preferred task contingent on the verbalization of “break please.” DNRO provides escape contingent on the presence of any behavior excluding the problem behavior (Vollmer & Iwata 1992; Vollmer,

Roane, Ringdahl, and Marcus, 1999). A limitation of differential reinforcement is that the

3 procedures require constant monitoring of behavior, which can be labor intensive

(Vollmer & Iwata 1992).

Finally, escape extinction prevents access to the reinforcer (i.e., escape or avoidance) contingent on problem behavior by continuing the presentation of the aversive stimulus. Escape extinction has proven to be effective when used in isolation and as part of another treatment program, but there are several negative side effects associated with this treatment (Iwata, Pace, Kalsher, Cowdery & Cataldo, 1990; Lerman & Iwata, 1996).

These include (a) extinction burst (i.e., sudden increase in the occurrences of the problem behavior) (Ducharme & Van Houten, 1994), (b) spontaneous recovery (i.e., the sudden reoccurrence of the behavior once it appears to be eliminated) (Ducharme & Van Houten,

1994; Kazdin, 1994; Malott, Whaley & Malott, 1991), (c) worsening topographies of behavior (Vanderplanck, 1995) (e.g., extinction induced aggression) (Todd, Morris &

Fenza, 1989), (d) behavioral contrast (i.e., the elimination of a behavior under one stimulus, increases in the presence of the behavior under other stimuli) (Catania 1969), and (e) often involve implementing physical containment (e.g., physical restraint)

(Slocum & Vollmer, 2015). These risks are problematic to the individual and the program implementers and could result in the termination of the treatment program. Furthermore, physical containment is often prohibited in natural settings (e.g., schools) or may be impossible if the individual is larger or stronger than the implementer (Piazza, Moes,

Fisher, 1996).

Treatment Without Extinction

Research has been conducted on treating escape-maintained problem behavior without the use of extinction (Lalli et al., 1997). To manipulate the reinforcing value of compliance, researchers combined non-functionally related (i.e., positive) with functionally related reinforcement (i.e., negative) to treat escape-maintained behavior.

Baron and Galizio (2005) argued that there are two reasons why adding a non- functionally related reinforcer may be effective in replacing the need for extinction. First, the distinction between positive and negative reinforcement may not be necessary. The reinforcing function of a stimulus is dependent on the context in which the presentation and/or removal take place. Therefore, the reinforcing value (i.e, positive or negative) can differ from stimulus to stimulus contingent on the temporal location of the event

(Catania, 1972; D’Amato, 1969; Michael 1975). Second, the characteristics of positive and negative reinforcement are more alike than different (Hineline, 1984). The parameters that are used to describe positive reinforcement (magnitude, delay, and schedule) have similar results on behavior maintained by negative reinforcement. For example, the schedule of breaks to work time can impact the amount of problem behavior exhibited by an individual.

Piazza et al. (1997) conducted one of the first studies comparing the effects of treatments with and without extinction. Three participants, ranging from 7 to 9-years old with multiple disabilities, were exposed to five different differential reinforcement conditions with and without extinction. For the conditions without extinction, the authors established a concurrent schedule of reinforcement by offering either verbal praise, break,

5 or enriched break (break with a tangible item) for compliance, while problem behavior resulted in a 30s break. For the conditions involving extinction, compliance still resulted in one of the reinforcement types listed above, however, problem behavior did not result in a break. The problem behavior for 2 of 3 participants was treated without the use of extinction. For the other participant, extinction was required to achieve behavioral change even when compliance resulted in an enriched break.

The effects of contingent and non-contingent reinforcement with and without extinction were compared and extended by Lalli et al. (1999). Five individuals with ASD or pervasive developmental disorder, and mild developmental delays were included in an experiment that compared the separate effects of positive reinforcement (immediate edible), negative reinforcement (30s break), and non-contingent reinforcement on compliance, with and without extinction. The rates of problem behavior were lower and compliance was higher for all participants during the contingent positive reinforcement without extinction condition when compared to the other conditions.

Researchers have continued to manipulate other variables of reinforcement in efforts to expand the understanding of how response allocation can be transferred from problem behavior to compliance without the use of extinction (Payne & Dozier, 2013).

An additional dimension of reinforcement that has been explored is the use of high versus low preference for positive reinforcers (Carter, 2010; Payne & Dozier, 2013; Slocum &

Vollmer, 2015). Carter (2010), compared the effect of high- and low-preference edibles, and leisure items (sticker or music) for compliance and a 30s break for problem behavior

6 without the use of extinction. The most effective treatment for a 19-year-old with an intellectual disability was high-preference edible for compliance without extinction.

Hoch, McComas, Thompson, and Paone (2002), extended the work of Piazza et al. (1997) by assessing the comparative effects of positive plus negative reinforcement

(i.e., break with preferred item) versus negative reinforcement (i.e., break) for increasing compliance and reducing problem behavior without the use of extinction. For 3 participants ranging in age from 9 to 11-years old with autism or other health impairments, immediate and sustained decreases in problem behavior and increases compliance occurred when compliance resulted in the combination of positive and negative reinforcement (enriched break). Comparatively, when compliance resulted in a break, the participants’ rates of problem behavior were higher and compliance was lower than in the combination (positive and negative) reinforcement phase.

Research has vastly expanded the treatment options for escape-maintained problem behavior, however there are still several limitations. First, the most commonly used form of positive reinforcement in research is food (Payne & Dozier 2013; Piazza et al., 1996; Slocum & Vollmer, 2015). Food may be impractical in natural settings (e.g., classrooms) and may have varying effectiveness depending on the time of day (e.g., after lunch or snack). Second, this line of research (i.e., treating escape-maintained behaviors without extinction) has been conducted only in contrived settings with no generalization data (Payne & Dozier, 2013). Finally, the reinforcement used in previous research has involved immediate access (Carter, 2010; Hoch et al., 2002; Payne & Dozier, 2013;

Slocum & Vollmer, 2015). This is problematic because if food is delivered as a reinforcer frequently, it may lead to satiation and rejection from program implementers.

Delayed Reinforcement Through a Token Economy

An alternative option to immediate reinforcement, is to delay reinforcement through token reinforcement, which has been used for behavioral management and as motivational aides in applied setting since the early 1800s (Kazdin, 1987). Token reinforcement is based on conditioning a relationship between an object that has no intrinsic value (i.e., a token) and a reinforcer. After a long history of basic (non-human) and applied application of token reinforcement, Kelleher advanced the concept by combining tokens with reinforcement schedules. He conceptualized token reinforcement as a three-series contingency involving (a) the schedule (i.e., ratio between responses and the production of a token), (b) the exchange schedule or the requirement of tokens or time to gain access to the reinforcer, and (c) the token-exchange schedule, which referred to the requirement of tokens to access specific reinforcer. This early conceptualization then gave way to a new term, token economy. However, systematic development and application of token economies in classrooms did not occur until late 1960’s (K.D.

O’Leary & Drabman, 1978).

The effectiveness of token economies has been empirically supported in controlling a variety of behaviors including decreasing inappropriate behaviors and increasing appropriate social and academic behaviors. Token economies are commonly used when trying to differentially reinforce appropriate behaviors (McLaughlin &

Williams, 1988). A possible explanation of the effectiveness of token economies is

8 related to framing effect, or the tendency for decisions to be influenced by the context of format which they are presented in (Kahneman & Tversky, 2000). In several papers,

Logue and colleagues systematically assessed framing effect by examining participants’ choice between smaller-sooner and later-larger reinforcers. The results indicated that under various conditions, the participants generally preferred the later-larger reinforcers.

Their decision was influenced by the greater net reinforcing value of the delayed reinforcement.

A second study by Athens and Vollmer (2010) also investigated framing effect by examining the effects of differential reinforcement of alternative behaviors without extinction. The participants included seven children with developmental disabilities who engaged in multiply maintained problem behaviors. The study assessed participants’ response allocation for appropriate responses by manipulating dimensions of reinforcement (i.e., duration, quality and delay) in isolation and combination. In the first condition (duration), appropriate behavior produced a 30 s break from instruction and problem behavior produced a 10 s break. The second condition assessed quality by provided 30 s break with a highly-preferred item and problem behavior produced a 10 s break with a low preferred item. Third, delay was assessed by providing an immediate 30 s break with a highly-preferred item for appropriate behavior and a delayed 10 sec break with a low preference item for problem behavior. In the final condition, appropriate behavior produced immediate access to a highly- preferred item and problem behavior resulted in 10 s delay before a 5 s break with a low preference item was given. The results indicated the participants engaged in largest amount of appropriate responses most

9 consistently when several dimensions of reinforcement were combined in favor of that type of behavior.

The purpose of the current study was to investigate the treatment of escape- maintained problem behavior without extinction. The research questions were, (a) what are the effects of delayed terminal reinforcement through a token economy on compliance and escape-maintained problem behaviors without extinction for individuals with mild to severe levels of autism? (b) What are the effects of delayed reinforcement through a token economy on generalization to the classroom and maintenance? and (c)

What are the teachers’ opinions of the goals, procedure and outcomes of the treatment?

CHAPTER 2

METHODS

Participants

Participants included three males and one female, who were 4 or 5-years old. All participants attended private special education schools for individuals with ASD in a

Midwestern suburb. To protect the confidentiality of the participants, each child was assigned a pseudonym. Danny, Eve, and Aaron were found eligible for special education services as students with autism by their home school districts according to the

Multidisciplinary Education Team (MET) Report and Lance was diagnosed with autism by a psychologist at a local hospital. Danny, was a 4-year old white male, who communicated using multiword sentences and could follow two-step directions. Eve, was a 5-year old white female, who communicated through single word sentences and could follow single step directions. Aaron, was a 5-year old black male, who communicated in complete, grammatically correct sentences and followed multistep directions. Lance was a 5-year old white male, who was also diagnosed with cystic fibrosis, spoke in complete multiword sentences, and followed three step directions.

Setting

Sessions with Danny, Eve, and Aaron were conducted 1-on-1 in a 15 X 10- foot therapy room at their school. Generalization probes were conducted during natural instruction or tasks in their classrooms. Sessions with Lance were conducted in a 10 X 10 11 bedroom in his home. Tasks for each student were selected based on Individual

Education Plan goals, teacher reports, and classroom observations. The selection criteria for the tasks required that the participants engaged in problem behavior during the task and that the participant had not yet mastered the task. Danny’s tasks included tracing the letters of the alphabet, numbers one through ten, and polygons, determining what is next in an AB pattern, and larger number identification. Eve’s tasks included identifying colors, numbers, and shapes, and single digit addition problems with manipulatives.

Aaron’s tasks included color by number worksheets, counting coins up to 80 cents, and alphabetizing a five-word sequence. Lance’s tasks included writing his first and last name, cutting out shapes (circle, triangle, square, and rectangle) and writing his phone number and address.

Dependent Variables Definitions & Measurement

Problem behavior and compliance were the dependent variables. Problem behavior was defined individually based on the topography exhibited by each participant

(see Table 1). The topographies included, blocking (using his hands or arms to cover the task to prevent further prompting), destruction (using his hands or arms to push away, knock over, or rip materials), aggression (using his hands or feet to strike and pull the experimenter’s hair or clothing) and elopement (moving more than 2-feet away from where the task was introduced). When a participant (Lance or Eve) engaged in aggression

(hitting or kicking), experimenters attempted to block contact by restricting the movement of the associated limb. Blocked behaviors were still recorded as an occurrence of problem behavior. Rate was used to measure problem behavior by dividing the

12 frequency of problem behavior by duration of active demands (time where demands were present) in each session.

Compliance was recorded when a task was completed without any occurrence of problem behavior. Occurrence of problem behavior resulted in re-presenting the demand until the participant exhibited compliance. Demands were defined as each task within an activity. For example, with Aaron’s coin counting worksheet, each of the 7 problems were individual demands. If a demand was placed and the participant did not engage in the task or made an error, the prompting hierarchy was used to guide the participant through the task. Even if the participant needed prompting to complete the task, the demand was still scored as compliance if no problem behavior occurred.

Each time a demand was given, it counted as an opportunity for compliance and was scored as compliance (plus) or non-compliance (minus). At the end of each session, the percentage of compliance was calculated by dividing the number of occurrences of compliance by the total number of opportunities. (see Appendix A)

Interobserver Agreement (IOA) and Researcher Procedural Fidelity

Prior to data collection, the primary data collector (the first author) used video recordings of each participant to train one secondary data collector (a board-certified behavior analyst). Training included scoring occurrences of problem behavior and compliance. The scores of the primary and secondary data collectors were compared, and disagreements were resolved by reviewing the video clip and the definition until an agreement was reached. Five training sessions were completed before the observer met the mastery criterion of 90% agreement or higher across three consecutive sessions.

The secondary data collector observed 36% of the baseline and 34% of treatment sessions and independently scored each session. IOA was calculated using a point-by- point comparison, by dividing the number of agreements by the total of agreements plus disagreements for both compliance and problem behavior. Agreements were scored when both observers recorded an occurrence or non-occurrence (see Appendix C). Baseline

IOA for problem behavior ranged from 88% to 100% (M= 98%) and IOA for compliance was scored with 100% accuracy. During Treatment, IOA for problem behavior ranged from 97% to 100% (M= 99.7%) and compliance IOA was 100%.

The secondary data collector used video recordings and an experimenter-created checklist to assess procedural fidelity for 36% of baseline and 34% of treatment sessions.

The observer recorded a check or minus for each step to indicate whether or not the experimenter followed the step. The percentage of procedural fidelity was calculated by calculating the total number of steps completed correctly and diving that by the total opportunities (the number of checks plus minuses). Procedural fidelity was calculated by dividing the number steps completed (plus) by the total number of opportunities (see

Appendix D). The baseline treatment integrity ranged from 97% to 100%, (M= 99.4%) steps completed correctly. During the treatment condition, the percentage of steps completed correctly ranged from 97% to 100% (M= 99.1%) of the steps completely correctly.

Social Validity

Social validity was assessed with two different groups of consumers. First, 3 classroom teachers were given questionnaires before, during, and after the intervention to

14 assess the acceptability of the goals, procedures and outcomes of the intervention (see

Appendix G-I). Each questionnaire included rating scales, multiple choice, and/or open- ended questions. Second, the participants’ satisfaction with the intervention was assessed as a behavior correlate by recording the percentage of time each one spent within the original workspace (i.e., 2-foot radius of where the task was delivered) during baseline compared to intervention.

Pre-Experimental Procedures

Preference Assessment. A Multiple Stimulus Without Replacement (MSWO) preference assessment was conducted with each student based on the procedures described by DeLeon and Iwata (1996). The MSWO directly assessed the participants’ preference for five preselected items based on observations and recommendations from parents, teachers, and/or therapists. The participants were initially presented with all five items and were prompted to “choose one.” After selecting an item, the participant was given 1 min to interact with it before returning it to the experimenter. Selected items were not re-presented in the array of choices and the process was repeated until all items were selected. Highly preferred items (selected first) were given at the end of each treatment session. Danny’s preferences included Curious George® and Daniel Tiger® videos from the PBS Kid’s app. Eve’s preferences included Mickey Mouse Clubhouse®, Kate and

Min-Min®, and Chocolate Town® videos on the Disney Junior app. Aaron’s preferences included, “TouchMath 1–9” YouTube video by Jackie Fraifield, and coloring with markers. Lance’s highly preferred items were, “The Toy Reviewer” videos on YouTube and the “Little Dentist” application.

Functional Analysis. A functional analysis based on the procedures described by

Iwata, Pace, Dorsey, Zarcone, and Vollmer (1994) was conducted with three participants.

Sessions were 10 min and included demand, tangible, and control conditions. The function was determined by the condition containing the highest levels of problem behavior. Control conditions consisted of access to three preferred items, no demands, and continual attention from the experimenter. Occurrences of problem behavior did not result in any programmed consequences. During the demand condition, the experimenter continually delivered instruction throughout the session using sequential verbal, gestural, and physical prompts. Each level of prompting was followed by a 10 s response interval.

If no response or an error occurred, then a more intrusive prompt was immediately delivered. Occurrences of problem behavior resulted in a 30 s break from the demand. If problem behavior occurred during the break, it did not produce any programmed consequences. Before the tangible condition, the participant was given a one min interaction period with a preferred item. The experimenter then removed the item from the participant to start each session. Occurrences of problem behavior resulted in the item being returned to the participant for 30 s. This process was repeated for the entirety of the session.

When a functional analysis was attempted with Lance, he verbalized the contingencies in each condition (e.g., “If I hit you, you will give me the toy back.”) He appeared to be manipulating the conditions, which produced inconsistent results. A descriptive analysis was used to generate a hypothesis regarding the function of his behavior.

Token Training. Token training was based on the procedures used by LeBlanc,

Hagopian, and Maglieri (2000). The 5 min sessions were conducted in the baseline and treatment sessions. Participants were prompted to comply with demands such as, “Touch your nose.” or “Clap twice.” Occurrences of compliance were immediately reinforced with a token paired with praise. Participants were given verbal reminders that the tokens would be exchanged for a break with a preferred item at the end of the session. Training continued until each participant completed three consecutive sessions without trying to access the reinforcer until the experimenter prompted, “It’s time to trade in your tokens.” at the end of the session.

Experimental Procedures

Baseline. Baseline followed the same procedure used during the demand condition of the functional analysis. Occurrences of problem behavior resulted in a 30 s break and compliance did not produce any consequences. During sessions, demands were presented for 10 min. The timer was paused during breaks for problem behavior. Sessions were terminated after 15 min, regardless of the number of breaks taken. A termination criterion was set to prevent sessions with high rates of problem behavior from reflecting unrealistic work periods in the classroom. Problem behavior that occurred during the 30 s break was not scored. (See Appendix A)

Token Economy. The intervention followed the same procedures as baseline, except for the delivery of a token for compliance. A token was used to control for confounds (i.e., immediacy/delay of reinforcement), by creating a bridge between the occurrence of compliance and gaining access to terminal reinforcer without allowing

17 access to the terminal reinforcer during the session. Once a token was awarded, another task was immediately introduced to prevent breaks from occurring for compliance. At the end of each session the accumulated tokens were traded in. The ratio of reinforcer access was determined based on the number of tokens collected (e.g., five tokens equated to one min with the reinforcer). The reinforcers were available only after the completion of the session and participants had no access to these items outside of the session (i.e., closed economy). (See Appendix B)

Generalization. Generalization was assessed with Danny, Aaron, and Eve in their classrooms during natural instruction. Generalization probes were administered once during baseline and once during intervention. During these probes, the classroom teacher delivered the instruction and the first author delivered the prompting hierarchy and breaks for problem behavior.

Maintenance. Maintenance probes were collected for all participants for sessions

23 through 25. These sessions began 2 weeks after the last participant (Lance) finished the token economy condition and were administered one week apart. Maintenance sessions were conducted using the same tasks, procedures and in the setting as treatment.

Experimental Design

A multiple-probe design across participants was used to examine the effects of delayed reinforcement on treating escape-maintained problem behaviors without the use of extinction. In accordance with Gast (2010), to demonstrate experimental control, all participants were exposed to the probe condition (baseline) at the same time. Intervention was introduced for one participant at a time once a stable baseline was achieved for the

18 previous participant. This process was repeated until all participants had been exposed to the intervention. Once participants completed five consecutive baseline points, and met mastery during treatment, probe sessions were conducted any time another participant entered treatment or hit mastery.

Table 1:

Participant Demographics, Problem Behaviors & Tasks

Participant Age Problem Behaviors Tasks Tracing letters, numbers and shapes, Danny 4 years Blocking & destruction and AB patterns Color by number, counting coins up Aaron 5 years Blocking & destruction to 80 cents, and alphabetizing Identifying colors, numbers and Aggression, destruction, & Eve 5 years shapes, and single digit addition elopement problems Destruction, aggression, Writing his full name, phone number Lance 5 years blocking, & elopement and address, and cutting out shapes

CHAPTER 3

RESULTS

Figure 1 displays the baseline and treatment data for each participant’s rate of problem behavior and Figure 2 displays the baseline and treatment data for percentage of compliance.

Problem Behavior

Danny’s baseline data for rate of problem behavior were variable, trending upward, and had a level of 1.1 occurrences per min. His problem behavior ranged from

.67 to 1.6 occurrences per min (M= 1.0). During the generalization probe, he exhibited a rate of 1.3 occurrences of problem behavior per min. In the treatment condition, the level dropped significantly to a rate of .1 occurrence per min, was stable, and had little variability. His rate of problem behavior ranged from 0 to .3 occurrence per min (M= .3).

In the treatment generalization probe, he exhibited zero rate of problem behavior.

Baseline data for Aaron’s rate of problem behavior was variable, trending downward, and had a level of .5 occurrence per min. His problem behavior ranged from

.5 to .7 occurrence per min (M= .56). During the generalization probe, Aaron exhibited a rate of .5 occurrence of problem behavior per min. In the treatment condition, his problem behavior level decrease to zero, was stable, and had no variability. All

sessions produced zero rate of problem behavior. During the generalization probe, he exhibited a rate of zero occurrences of problem behavior per min.

Eve’s baseline rate of problem behavior was highly variable, trending upward, and had a level of 3.25 occurrences per min. Her problem behavior ranged from 1.9 to 5 occurrences per min (M= 3.03). During the baseline generalization probe, she exhibited a rate of 3.5 occurrences of problem behavior per min. During treatment, Eve’s problem behavior had little to no variability, trended downward, and had a level of .2 occurrence per min. In the treatment condition, her problem behavior ranged from 0 to .5 occurrences per min (M= .26). During the generalization probe, she exhibited .1 occurrence of problem behavior per min.

Lance’s baseline problem behavior was highly variable, trending upward, and had a level of 1.8 occurrences per minute. His problem behavior ranged from .67 to 6 occurrences per minute (M= 2.48). During treatment, his rate of problem behavior was stable with little variability and a level of .05 occurrence per min. His problem behavior ranged from .1 to zero occurrence per min (M= .02).

Compliance

During baseline, Danny’s compliance was variable with a level of 50% and was trending downward. His compliance ranged from 33% to 71% of the total demands (M=

56.4%). During the generalization probe, he exhibited compliance during 50% of the demands. His level of compliance increased to 95% of the total demands, was stable, and had little variability. His percentage of compliance for demands ranged from 91% to

100% (M=99.1%). During the generalization probe, he exhibited 0 occurrences of problem behavior and was compliant with 100% of the demands.

Aarons compliance during baseline was stable and trending upward with a level of 75%. His compliance ranged from 63% to 79% of the total demands (M=74.2%).

During the generalization probe, Aaron was compliant with 83% of the demands. In the treatment condition, Aaron was compliant with 100% of the demands in all treatment and generalization probe sessions.

Eve’s percentage compliance during baseline was highly variable, trending downward, and had a level of 40%. Her compliance during the demands ranged from 0% to 83% of the total demands (M= 42%). During the baseline generalization probe, she was complaint with 28% of the tasks. In the treatment condition, her compliance was trending upward with little variability and had a level of 95%. Her compliance ranged from 85% to 100% of the total demands (M= 92%). During the generalization probe, she was compliant with 97% of the demands.

During baseline, Lance’s percentage of compliance was variable and trending downward with a level of 40%. His compliance ranged from 0% to 75% of the total demands (M= 35%). In the treatment condition, his compliance was stable with little variability and had levels of 98% of the total demands. Lance’s compliance ranged from

97% to 100% of the total demands (M= 99.4%).

Social Validity

Questionnaires. Three special education teachers from Eve, Danny and Aaron’s school completed questionnaires regarding the study. Each questionnaire contained six to

22 seven questions or statements and teachers were prompted to respond by selecting a rating of one (strongly disagree) to five (strongly agree), selecting an answer from a list, or writing in a response.

Table 1 displays the results from the questionnaire given before the start of baseline. The mean scores from the rating scales indicated that all three teachers strongly agreed (mean score 5) that a focus on reducing problem behavior and increasing compliance are important. The mean score of the teachers’ responses was 3.67 when asked if their students would be highly motivated to work for tokens that could be traded in for a break at the end of work session. Interestingly, when asked if escape-maintained problem behaviors could be treated without extinction the teachers’ responses had a mean score of 2, indicating they disagreed with this statement. The teachers were also asked to select or write in how they would respond to a student engaging in escape-maintained problem behaviors. Two out of three teachers selected that they would require the student to complete some or all of the work before receiving a break and the third teacher wrote in that she would wait out the student’s problem behaviors. All three teachers expressed that they have had experience using a token economy with students and two teachers stated that they have had positive experiences. One teacher said that she had run into problems with token economies not working with some students in the past. Lastly, the teachers were given a scenario of a student who engaged in escape-maintained behaviors.

The teachers were asked to determine what a student would engage in escape-maintained problem behaviors or work for a token. All three teachers responded that the student would choose the immediate break.

Table 2 displays the results from the questionnaire used to evaluate the procedures, which was completed before treatment started. The questionnaire included five rating scale questions and two extended response questions. The results of the rating scale indicated that the teachers felt very comfortable with implementing the procedures in their classroom. The teachers’ responses had a mean of 4.67 regarding their willingness to allow students to trade in tokens at the end of an activity for a break, and their belief that their students would be motivated by the intervention. When asked if the teachers could implement the token system from the intervention in their classrooms, the mean response was 4.33. The teachers scored a mean of 4, when asked to consider their ratio of student to teachers, and decide if they could implement the intervention during non-preferred tasks. The lowest mean score of 3, was in response to the teachers’ willingness to incorporate a break following an occurrence of problem behavior in their classroom. One question asked the teachers if any of the interventions procedures would not work in their classroom, and a teacher expressed concern over other students becoming jealous and engaging in problem behavior to be placed on a token economy.

The teachers were given the opportunity to change or remove any of the intervention procedures, but none offered any suggestions.

Table 3 displays the rating scale questions and results from the third questionnaire that was given to the teachers after the completion of the treatment condition to assess the results of the intervention. Additionally, the teachers were asked two open ended response questions. The teachers all scored a mean of 5 when asked to assess if the decreased problem behavior and increased compliance were a result of the intervention, if

24 the procedures would be used in their own classroom, and if escape-maintained problem behaviors can be treated without extinction. When asked if the teachers would recommend the procedure to their colleagues, the mean score was 4.7. The teachers were given the opportunity to express changes for the future, but no changes were suggested.

Figure 1. Treatment data for rate of problem behavior across participants. 26

Figure 2. Treatment data for percentage of compliance across participants.

Table 2:

Social Validity Questionnaire 1 and Mean Score of Teacher Responses

Question Range Mean 1. I believe that focusing on reducing problem behavior is important. 5 5 2. I believe that increasing compliance is important. 5 5 3. I think that my students would be highly motivated to work for tokens that 3-4 3.67 they trade in for a break. 4. Problem behaviors that are exhibited to escape or avoid a non-preferred task can be eliminated without requiring a student to complete the task before 2 2 earning a break.

Table 3:

Social Validity Questionnaire 2 and Mean Score of Teacher Responses

Question Range Mean 1. I believe that it would be easy to implement the token system from the 3-5 4.33 intervention in my classroom. 2. I believe it would be easy to give students a 30 second break from the 3 3 task following an occurrence of problem behavior. 3. After completing a task, it would be easy for my students to trade in 4-5 4.67 tokens for a break with a preferred item. 4. I think that my student(s) will be motivated by this intervention. 4-5 4.67 5. Given my current teacher to student ratio, I would be able to implement 4 4 this intervention with my student(s) during non-preferred activities.

Table 4:

Social Validity Questionnaire 3 and Mean Score of Teacher Responses

Question Range Mean 1. My student(s) problem behaviors were decreased or eliminated 5 5 because of this intervention. 2. My student(s) compliance increased when he/she was rewarded with 5 5 a token. 3. I would recommend this intervention to colleagues. 4-5 4.7 4. This intervention is something that I would use in my classroom to 5 5 help my student(s) complete non-preferred tasks. 5. Awarding tokens for compliance and a 30 s break for problem 5 5 behavior can treat escape/avoidance behaviors.

CHAPTER 4

DISCUSSION

All 4 participants exhibited decreases in problem behavior and increases in compliance when tokens were delivered contingent on compliance. The participant’s data suggests that extinction is not necessary to eliminate escape-maintained problem behavior in children with ASD. This study extends the literature by examining the effects of delaying access to the terminal reinforcer through the use of tokens. By awarding tokens contingent on compliance this study demonstrated that delayed reinforcement can also reduce/eliminate escape-maintained problem behaviors without extinction. This study addressed limitations from previous studies by eliminating the need edible reinforcement and by using a classroom reinforcement program (token economy).

Research Question 1: Can escape-maintained problem behavior be treated without extinction?

The problem behavior was reduced to zero rates for all four participants without the use of extinction, replicating the original results of Piazza et al. (1997). The rate of problem behavior immediately decreased to zero for Danny and Aaron. It may have taken

Lance and Eve longer to reach zero levels of problem behaviors because their baseline rates were much higher than the other two participants. By the end of the treatment condition all participants reached zero levels of problem behavior and maintained this level through 3 maintenance sessions. 30

Research Question 2: What are the effects of delayed reinforcement through a token economy on escape-maintained problem behavior and compliance?

Immediate access to edibles and other preferred items, have been empirically proven to treat escape-maintained problem behavior without extinction (Payne & Dolizer,

2013). It is important to note that this study is the first to examine the impact of delayed terminal reinforcement (e.g., break with preferred item) by using tokens without extinction. All 4 participants exhibited decreases in problem behavior and increases in compliance from baseline to intervention. The importance of these results is that, under these circumstances, the conditioned reinforcer (token) for compliance directly competed with problem behavior that resulted in an immediate break. This demonstrated that immediate edible reinforcement may not be necessary to treat escape-maintained problem behaviors without extinction.

As explained in the introduction, it is likely that the participants’ response allocation changed from problem behavior to compliance during the token economy treatment because of the framing effect (Kahneman & Tversky, 2000). The participants were more likely to engage in compliance during the treatment condition because the context of the situation differentially reinforced compliance which resulted in a greater reinforcement value (i.e., break plus a highly-preferred item) than problem behavior (i.e., short immediate break).

Other studies have suggested that immediate positive reinforcement was more effective than negative reinforcement (i.e., break) because it acted as an abolishing operation by reducing the aversive nature of the sessions (Slocum & Vollmer, 2015).

This study found that positive reinforcement was still more effective, but the participants did not need to immediately access the terminal reinforcer for the problem behavior to decrease. These results may indicate that the immediate primary reinforcer may not have acted as an abolishing operation, as suspected by Slocum and Vollmer (2015).

Research Question 3: Can the effects of delayed reinforcement through a token economy be maintained overtime and generalized to the classroom?

Maintenance. The effects of the token economy were maintained for all 4 participants even without the participants being exposed to the procedure multiple times each week. This is important because it demonstrates that the treatment can be used for non-preferred tasks that do not occur frequently in the classroom.

Generalization. It is important for interventions to be successful in 1-on-1 research sessions and in natural settings. The literature has only examined the effects in

1-on-1 sessions. To explore this issue, generalization probes were conducted during natural instruction and activities that occurred in the participant’s classrooms. All 3 participants exhibited lower rates of problem behavior and higher rates of compliance in the treatment probes, than in their baseline probe. Danny and Aaron both had zero rates of problem behavior in the treatment probes. Eve did not exhibit a rate of zero problem behavior during her generalization probe, but her rate during the treatment probe was significantly lower than her baseline probe. This may have been caused by her higher rate of problem behavior during the baseline probe. Given additional generalization probes, she may have been able to reach zero levels of problem behavior.

Research Question 3: What are the teachers’ opinions of the goals, procedure and outcomes of the treatment.

Goals. The teachers’ responses on the first questionnaire indicated a strong agreement with the importance of the goals of reducing problem behavior and increasing compliance. Additionally, the teachers reported having experience implementing a token exchange. One area of the treatment that could potentially lead to pushback or rejection was the teacher belief that escape-maintained problem behavior could not be treated without extinction. All the teachers reported that they currently required students engaging in escape-maintained problem behavior to complete some or all the work before getting a break.

Procedures. When reviewing the procedures, the teachers strongly agreed that a token exchange for a break at the end of the task could be incorporated into their classrooms, and that their students would be motivated by the intervention. The procedure with the lowest score was the 30 s break following problem behavior. It is likely that this procedure scored the lowest because it was the opposite of the teachers’ current behavior management plans. Although this question scored the lowest mean, when given the change to take out or modify the procedures of the treatment, none of the teachers offered any suggestions.

Outcomes. The results of the teacher’s responses indicated that the teachers believed there was a strong connection between the treatment and the students’ decreased problem behavior and increased compliance. Additionally, all the teachers strongly agreed that they would use the intervention in their classrooms. Possibly the most

33 interesting result from the final questionnaire was the change in the teachers’ beliefs that the problem behavior could be treated without using extinction. This statement scored the lowest on the first two questionnaires, but by the end it received the highest ranking by all the teachers. The lowest scoring statement related to teachers recommending the treatment to their colleagues. All but one teacher strongly agreed, and the other agreed with the statement. The lack of a strong agreement may be due to the teacher not feeling confident in her ability to explain the procedure to others.

Limitations and Future Research

The limitations of this study were related to the descriptive nature of the study, generalization, maintenance, and social validity.

Descriptive Study. Given the limited research on treating escape-maintained problem behavior with a token economy without extinction, the current study was descriptive rather than comparative. This allowed the study to examine the effectiveness of a relatively novel procedure. However, future research should use a comparative model to analyze the effects of the treatment. Comparisons should include variables of reinforcement (e.g., immediate versus delayed, high versus low preference, etc.) and treatments with versus without extinction.

Generalization. This study was the first to probe the effectiveness of the intervention in a classroom setting. However, during the probes, the experimenter was unable to control for the type of tasks administered and the rate at which the demands were given. This lack of control could have impacted the rate of problem behavior and

34 percentage of compliance for the participants if the tasks were vastly different than the ones used during the sessions. Additionally, to get a more realistic picture of the generalizability, future research should evaluate the effectiveness of the procedure more frequently, in other settings (e.g., art, music, gym, field trips, etc.), and with other types of tasks (e.g., daily living skills, food acceptance, etc.).

Maintenance. Maintenance was assessed with all 4 participants and demonstrated that the results could be maintained over a 5-week period. However, a limitation was that after the initial 2-week break, maintenance was assessed in 2 consecutive weeks. Future research should explore the maintenance of the treatment over longer and more variable periods of time.

Additional Suggestions for Future Research

The procedures in this study used a fixed rate (FR) of one reinforcement schedule for compliance. This may be cumbersome in other settings or with multiple individuals working at the same time. Future research should explore the possibility of fading the rate of reinforcement from an FR1 to lower fixed rates or even to a variable reinforcement schedule. By using a faded reinforcement schedule, the procedure may be more practical for implementers. Additionally, future research should explore the effects of the treatment through a wider scope with different disabilities, ages, settings, and functions of behavior.

Implications for Practitioners

Extinction has a strong empirical backing to demonstrate its success in treating problem behaviors (Iwata, 1994). However, extinction is also associated with several

35 negative side-effects including extinction bursts, spontaneous recovery, worsening topographies, and extinction induced aggression. Additionally, in some settings, it is challenging or impossible to prevent individuals from escaping the demand for several reasons. First, it may be impossible to catch every occurrence of the behavior and ensure that the student does not escape if there are other individuals requiring the attention of the practitioner. Second, preventing an individual from escaping a task often requires physically restraining the individual in the space, which may be prohibited or unethical.

Third, sometimes it is impossible to prevent escape due to safety concerns because the individual is stronger or larger than the practitioner. It is important for practitioners to be aware of alternative treatments that do not require extinction to establish appropriate replacement behaviors.

Additionally, the procedure used a relatively easily implemented evidence-based practice to replace the need for extinction and immediate access to the terminal reinforcer. The use of tokens created a more preferred learning environment, as demonstrated by the decrease in problem behavior. The participants’ social validity assessment of looking at the amount of time spend in the work environment as a behavior correlate also indicated their opinion of the treatment. This was determined by comparing the amount of time spent in the learning environment (2-foot radius from where the task was introduced) during baseline and intervention. During treatment, participants spent significantly more time in the learning environment and demonstrated less problem behavior (resulting in fewer breaks), which increased the total number of learning opportunities and tasks completed. For example, during baseline Lance was exposed to a

36 mean of 21.6 task demands and completed a mean 10 task demands. During treatment, he was exposed to a mean 29 task demands and completed a mean of 28.8 task demands.

Lastly, the generalization probes highlighted the ability of this intervention to be implemented successfully in 1-on-1 and applied settings. Success in 1-1 and applied settings helps increase the overall impact of the intervention, and presents the treatment as a possible option for practitioners in a wider range of settings.

Conclusion

The purpose of this study was to expand the research on treating escape- maintained problem behavior without extinction by assessing the effects of delayed reinforcement using a token economy. Once a reliable treatment for escape-maintained problem behavior without the use of extinction has been identified, the treatment of other functions of behaviors can be explored using this same treatment model.

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Appendix A: Baseline Data Sheet

Baseline Datasheet Session _____

Participant: ______Observer: ______Date: ______Duration: ______Demand Task Problem Behavior C 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Total

Appendix B: Treatment Data Sheet

Treatment Datasheet Session _____

Participant: ______Observer: ______Date: ______Demand Task Compliance Problem Behavior 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Total Duration: ______

Appendix C: Baseline IOA Data Sheet

IOA Datasheet: Treatment Session _____

Participant: ____ Observer A: _____ Observer B: ______Date: ______

Problem Behavior Demand Task Obs. A Obs. B IOA 1 A D 2 A D

3 A D 4 A D 5 A D

6 A D 7 A D 8 A D

9 A D 10 A D 11 A D

12 A D 13 A D 14 A D

15 A D 16 A D 17 A D

18 A D 19 A D 20 A D Totals

Appendix D: Treatment IOA Data Sheet

IOA Datasheet: Treatment Session _____

Participant: ____ Observer A: _____ Observer B: ______Date: ______

Problem Behavior Compliance Demand Task Obs. A Obs. B IOA Obs. A Obs. B IOA 1 A D A D 2 A D A D 3 A D A D 4 A D A D 5 A D A D 6 A D A D 7 A D A D 8 A D A D 9 A D A D 10 A D A D 11 A D A D 12 A D A D 13 A D A D 14 A D A D 15 A D A D 16 A D A D 17 A D A D 18 A D A D 19 A D A D 20 A D A D Totals

Appendix E: Baseline Procedural Fidelity Data Sheet

Baseline Procedural Fidelity Datasheet

Participant: _____ Observer: ____ Session # ______Date: ______

Key: +: occurrence -: nonoccurrence N/a: Not applicable

Prompting Hierarchy Problem Behavior Demand Task Demand 30 s Break- No Placed Verbal Model Physical removed access to items 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Totals

Appendix F: Treatment Procedural Fidelity Data Sheet

Treatment Procedural Fidelity Datasheet

Participant: _____ Observer: _____ Session # ______Date: ______

Post During Session session Prompting Hierarchy Problem Behavior Compliance 30 s Demand Tokens Task Demand Break- No Placed Verbal Model Physical Token exchanged removed access to items 1 2 3 4 5 6 7 8 9 10 N/A 11 12 13 14 15 16 17 18 19 20 N/A Totals Key: +: occurrence -: nonoccurrence N/a: Not applicable

Appendix G: Social Validity Questionnaire 1

Social Validity Questionnaire 1 (Before baseline) Teacher Name: ______Date: ______

1. I believe that focusing on reducing problem behavior is important.

1 2 3 4 5 Strongly Strongly agree disagree

2. I believe that increasing compliance is important.

1 2 3 4 5 Strongly Strongly agree disagree

3. I think that my student would be highly motivated to work for token that they trade in for breaks.

1 2 3 4 5 Strongly Strongly agree disagree

4. Problem behaviors that are exhibited to escape or avoid a non-preferred task can be eliminated without requiring a student to complete the task before earning a break.

1 2 3 4 5 Strongly disagree Strongly agree

5. When my students are trying to escape, or avoid a non-preferred task by engaging in problem behaviors, I normally ______.  Require the student complete some/ all of the work before escaping the task  Give the student a break  Remove the student from the work area  Give up on the task and move on  Other Explain: ______

Appendix G continued

6. Have you implemented a token economy in your classroom? Was it successful or unsuccessful and why?

7. If a student is engaging in escape-maintained problem behavior, is offered a token for completing work (that can be traded in for a break at the end), or an immediate 30 second break from a non-preferred task, which do you think the student will choose?

Appendix H: Social Validity Questionnaire 2

Social Validity Questionnaire 2 (Before Treatment) Teacher Name: ______Date: ______

1. I believe that it is/would be easy to implement a token system with my students in my classroom.

1 2 3 4 5 Strongly disagree Strongly agree

2. I believe that it would be easy to give students a 30 s break from the task following an occurrence of problem behavior.

1 2 3 4 5 Strongly disagree Strongly agree

3. After completing a task, it would be easy for my students to trade in tokens for a break with a preferred item.

1 2 3 4 5 Strongly disagree Strongly agree

4. I think that my student(s) will be motivated by this intervention.

1 2 3 4 5 Strongly disagree Strongly agree

5. Given my current teacher to student ratio, I would be able to implement this intervention with my student(s) during non-preferred activities.

1 2 3 4 5 Strongly disagree Strongly agree

6. Given the procedures of the intervention, are there any that you would add, remove, or change and why?

Appendix I: Social Validity Questionnaire 3

Social Validity Questionnaire 3 (After Treatment) Teacher Name: ______Date: ______

1. My student’s problem behaviors were decreased or eliminated because of this intervention.

1 2 3 4 5 Strongly disagree Strongly agree

2. My student’s compliance increased because of the token that was traded in at the end for a break.

1 2 3 4 5 Strongly disagree Strongly agree

3. I would recommend this intervention to colleagues.

1 2 3 4 5 Strongly disagree Strongly agree

4. This intervention is something that I would use in my classroom with my students during non- preferred tasks.

1 2 3 4 5 Strongly disagree Strongly agree

5. Awarding tokens for compliance and a 30 s break for problem behavior can treat escape/avoidance behaviors.

1 2 3 4 5 Strongly disagree Strongly agree

6. Is there anything you would change about the intervention for the future?