Clinical and Organizational Applications of Applied Behavior Analysis

By Academic Press

Applied behavior analysts use applied research to create and implement effective evidence-based procedures in schools, homes, and the community, which have proved effective in addressing behaviors associated with autism and other developmental disorders.  The principles underlying this therapeutic approach have been increasingly effective when applied to other populations, settings, and behaviors.  Clinical and Organizational Applications of Applied Behavior Analysis explores data-based decision-making in depth to inform treatment selection for behavior change across various populations and contexts.  Each chapter addresses considerations related to data collection, single-case research design methodology, objective decision-making, and visual inspection of data.  The authors reference a range of published research methods in the area of applied behavior analysis (ABA) as it has been applied to specific topics, as well as utilizing their own clinical work by providing numerous case examples.

• Reviews current evidence-based practices to provide a comprehensive guide to the application of ABA principles across a range of clinical contexts and applications
• Divides clinical applications into three sections for ease-of-use: child, adult, and broad-based health
• Explores the breadth of ABA-based treatment beyond autism and developmental disorders
• Draws upon a range of subject-matter experts who have clinical and research experience across multiple uses of ABA

• Language: English
• Publisher: Academic Press
• Release date: Jun 20, 2015
• ISBN: 9780128007938

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Chapter 1

Defining Features of Applied Behavior Analysis

Terry S. Falcomata [e-mail]    Department of Special Education, The University of Texas at Austin, Austin, Texas, USA

Abstract

This chapter provides a summary and description of the defining features of behavior analysis within the framework provided by Baer, Wolf, and Risley (1968). Those dimensions include: (a) applied, (b) behavioral, (c) analytic, (d) technological, (e) conceptually systematic, (f) effective, and (g) generalizable. In this chapter, I briefly review and describe how these dimensions characterize work conducted in various areas of focus, settings, and populations. Each of the dimensions is described and demonstrated using examples from various child, adult, and organizational ABA-based research.

Keywords

Applied behavior analysis

Dimensions of applied behavior analysis

Children

Adults

Organizational behavior management

Introduction

Individuals who work in applied behavior analysis (ABA) implement clinical interventions as well as conduct research to assist in the development of practices for addressing problems that occur with socially significant behavior. Applied behavior analysts often conduct applied research and use the results to create and implement effective, evidence-based procedures in more natural settings such as the home, schools, and the community. ABA-based research often focuses on behavioral issues that occur in specific settings, are associated with particular populations including children (e.g., obesity, autism or other developmental disabilities, traumatic brain injury, feeding disorders) and adults (e.g., caregiver training, sports performance, gambling), as well as those within other social contexts such as various workplace environments (e.g., performance management, workplace safety, systems analysis).

Although ABA has an extensive history of effectiveness in application and research across a diverse number of areas of focus, settings, and populations, perceptions exist in the media, various disciplines, and the public in general that ABA is synonymous with procedures for addressing issues related to autism spectrum disorder and other developmental disabilities (e.g., discrete-trial training and other procedures to promote skill acquisition; functional behavioral assessment and treatment of challenging behavior). In fact, the use of ABA-based methods and procedures to address issues relating to autism is just one of the many examples of the effective application of the ABA approach to addressing socially significant behavior. Said another way, although ABA has been demonstrated to be an effective approach to addressing issues with autism (e.g., Howard, Stanislaw, Green, Sparkman, & Cohen, 2014; MacDonald, Parry-Cruwys, Dupere, & Ahearn, 2014; Matson, Tureck, Turygin, Beighley, & Rieske, 2012), this aspect of ABA represents only one, relatively narrow application.

This chapter provides an overview of the features of ABA within the framework provided by Baer, Wolf, and Risley (1968) and how those features characterize work conducted in various areas of focus, settings, and populations. Each of the dimensions is described and demonstrated using examples from various child, adult, and organizational ABA-based research.

Dimensions of ABA

Baer et al. (1968) provided what they contended were defining dimensions of ABA. As described by Baer et al., there are seven dimensions of ABA that must be present to ensure that effective practices are developed and implemented. According to Baer et al., ABA is (a) applied, (b) behavioral, (c) analytic, (d) technological, (e) conceptually systematic, (f) effective, and (g) generalizable. The remainder of this chapter will review the dimensions described by Baer et al. using applied studies across various populations and areas of focus as outlined in this text to illustrate how they characterize ABA.

Applied

The term applied indicates that a particular target behavior of interest is of social significance. Further, it is the emphasis on social significance that distinguishes ABA from laboratory analysis. Specifically, applied behavior analysts select behaviors that are socially meaningful and are currently of importance to the individual(s) whose behavior is being addressed. At various times, applied behavior analysts have opportunities to address numerous behaviors demonstrated by individuals, and it is considered vital that they prioritize those behaviors in terms of importance. Illustrations of the applied dimension of ABA are wide-ranging and can be observed in studies across numerous populations, settings, and areas.

Myriad child-focused studies have been conducted within ABA that exemplify the focus on social significance. These include (but are not limited to) studies evaluating treatments for feeding disorders (e.g., Kadey, Piazza, Rivas, & Zeleny, 2013; Kadey, Roane, Diaz, & Merrow, 2013; LaRue et al., 2011; Volkert, Vaz, Piazza, Frese, & Barnett, 2011), interventions for childhood obesity (e.g., Fogel, Miltenberger, Graves, & Koehler, 2010; Van Camp & Hayes, 2012), and issues relating to attention deficit hyperactivity disorder (ADHD; e.g., Northup, Fusilier, Swanson, Roane, & Borrero, 1997; Ridgway, Northup, Pellegrin, LaRue, & Hightsoe, 2003).

The ABA-based approach to the assessment and treatment of pediatric feeding disorders has included a wide variety of behaviors of significant social importance including food refusal (Borrero, Woods, Borrero, Masler, & Lesser, 2010), self-feeding (Vaz, Volkert, & Piazza, 2011), and swallowing (e.g., Kadey, Piazza, et al., 2013). For example, Kadey, Piazza, et al. (2013) addressed the food consumption of a 5-year-old girl who relied on a gastrostomy tube for her caloric needs. The authors conducted a texture assessment in which they evaluated various textures, across foods, to determine the one which the girl could successfully swallow. Through their systematic process of identifying a texture with which she could be successful with individual foods, the authors were able to increase the girl's consumption of those foods.

Child obesity is another socially significant area in which several ABA-based studies have been conducted. Fogel et al. (2010) evaluated the effects of video game-based exercise (i.e., exergaming) relative to traditional physical education (PE) with four physically inactive and overweight fifth grade students. The authors' purpose was to evaluate whether the physical activity of the children would increase through exposure to 10 exergames (e.g., Play Station; Nintendo Wii Boxing, Sports Baseball, Sports Tennis; iTech Fitness XrBoard). Through the use of the exergaming approach, the authors were able to substantially increase the physical activity of all four children above the levels observed during traditional PE.

A third socially significant, child-focused area of study deals with variables relating to ADHD. Northup et al. (1997) evaluated the effects of stimulant medication on five children with ADHD diagnoses. Specifically, the authors evaluated the children's preference for different reinforcers (quiet time, alone play, and social play) across the presence and absence of stimulant medications. Although the results of Northup et al. were idiosyncratic across children, the authors showed that stimulant medication can alter children's motivation for types of reinforcement.

Studies conducted in the areas of pediatric feeding disorders such as Kadey, Piazza, et al. (2013), childhood obesity such as Fogel et al. (2010), and ADHD such as LaRue et al. (2011) illustrate the emphasis of child-focused ABA on social significance. Each of the dependent variables, or target behaviors, in the above studies was meaningful and of practical importance to the children in the studies and to potential future consumers of the studies.

Similarly, a large number of adult-focused studies with high social significance have been conducted within ABA. These include (but are not limited to) studies evaluating assessment, treatment, and training practices in pathological gambling (e.g., Guercio, Johnson, & Dixon, 2012; Nastally, Dixon, & Jackson, 2010) as well as teacher and caregiver training (e.g., Lerman, Tetreault, Hovanetz, Strobel, & Garro, 2008; Lerman, Vorndran, Addison, & Kuhn, 2004).

For example, the dimension of social significance is demonstrated in adult-focused, ABA-based studies pertaining to the assessment, treatment, and determination of the variables that contribute to pathological gambling. Guercio et al. (2012) studied a treatment intended to decrease urges to gamble and actual gambling behavior of three adults with acquired brain injury who were also indicated as pathological gamblers. The authors implemented a treatment program that consisted of one-on-one therapy that entailed providing instruction to the adults about motivating operations (MOs), antecedents, and consequences relating to gambling. Through the application of the treatment program, the authors demonstrated a reduction in urges to gamble (based on data collected via self-reports) and gambling behavior in each of the adults.

Another adult-focused area of study that illustrates the dimension of social significance in ABA is care provider training. Lerman et al. (2008) evaluated a training program intended to teach skills to teachers of children with autism relating to the implementation of preference assessment and teaching procedures. The training program consisted of a variety of teaching methods including lectures, discussion, and role-play procedures. The results showed that the training program resulted in the acquisition of the target skills by each of the teachers, and follow-up assessment suggested that those skills maintained over time following training. Similar to the child-based studies described above, each of the dependent variables evaluated in adult-based studies was meaningful and of obvious practical importance.

Many studies have also been conducted in the area of organizational behavior management (OBM) pertaining to safety (e.g., Ludwig & Geller, 1997) illustrating the applied nature of ABA. For example, Ludwig and Geller (1997) conducted a study in which they evaluated an intervention aimed at increasing safe driving behavior of pizza delivery drivers. Specifically, the authors implemented two interventions with two groups of drivers, respectively. One intervention consisted of goal setting in which the drivers participated in the setting of the goals. The second intervention consisted of goal setting but the drivers did not participate in the setting of goals. The results showed that both interventions were effective at increasing complete stops at intersections. Further, the results also showed that nontargeted safe driving behaviors (i.e., turn signal use, safety belt use) also increased during one of the interventions. The interventions, which were antecedent-based in nature, utilized by Ludwig and Geller (1997) demonstrated the effective use of an ABA-based approach to produce positive, socially significant changes with meaningful and practical target behaviors.

Behavioral

The term behavioral indicates that ABA concerns itself with the study of directly observable behavior. Specifically, applied behavior analysts emphasize the direct observation and manipulation of overt behavior. Indirect measures of behavior such as self-report, interviews, or checklists, although often used, are de-emphasized in ABA research in favor of direct methods of measurement and manipulation. In addition, applied behavior analysts do not attribute behavior as characteristics of, or based upon, nonbehavioral constructs or inner qualities (e.g., personality traits). Rather, ABA emphasizes the manipulation of environmental variables and the observation of relations between behaviors of interest and those variables for the purpose of demonstrating functional relations (i.e., functions of behavior). The behavioral dimension of ABA is vital because of the importance of precise measurements of behaviors of interest that, in turn, allow for valid evaluations and demonstrations of functional relations between interventions of interest and target behaviors of importance (see Section Analytic). Further, it allows for a systematic analysis of the extent to which applied behavior analysts are addressing the intended target behaviors and not approximations or nontarget behaviors (i.e., reliability of measurement).

The behavioral dimension of ABA can be illustrated in numerous child-based studies including those focusing on challenging behavior (e.g., Athens & Vollmer, 2010; Lustig et al., 2014) and academic skills (e.g., Martens, Werder, Hier, & Koenig, 2013). For example, Athens and Vollmer (2010) conducted a study in which they evaluated a treatment of challenging behavior exhibited by children with autism and ADHD. The authors focused exclusively on the direct observation of the target behaviors (i.e., aggression, disruption, compliance, communicative behaviors). To do so, the authors established a specific, operational definition of aggression for the participant (Henry) that consisted of forcefully hitting and kicking others resulting in bruising his victims (p. 573). This definition allowed for the direct observation and measurement of the presence and absence of the behavior. This approach can be contrasted with a nonbehavioral approach that might consist of anecdotal reports, or impressions provided by care providers regarding the behavior of the child.

Martens et al. (2013) focused on accuracy and fluency exhibited by children during oral reading. The authors specifically defined each of these target behaviors to allow for direct observation and measurement. Specifically, they established an operational definition of accuracy that consisted of the correct reading of a particular word, and they established an operational definition of fluency that consisted of the number of words correctly read per minute. Establishing these specific, observable operational definitions allowed the authors to evaluate variables (i.e., an intervention consisting of word training) impacting their occurrence, or lack thereof, in a systematic way. Without an emphasis on a behavioral approach, establishment of reliability of measurement would not be possible which would have precluded the authors from drawing conclusions about relations between their independent and dependent variables (i.e., conclusions about the effectiveness of their interventions would not be appropriate in the absence of demonstration of reliability of measurement made possible by the behavioral approach).

The behavioral dimension of ABA is also illustrated in numerous adult-based studies including those focusing on problem behaviors in gerontological populations (e.g., Baker, LeBlanc, Raetz, & Hilton, 2011) and acquired brain injury (e.g., Lancioni et al., 2012). For example, Baker et al. (2011) intervened with an individual with Alzheimer's-type severe dementia who was engaging in hoarding behaviors. The authors established a definition of hoarding that allowed for the direct observation and measurement of the behavior (i.e., putting items in her shirt or pants). This was opposed to a nonbehavioral approach that might have relied on the feelings of the staff that worked with her. Thus, by relying on directly observable behaviors, the authors minimized potential bias and accuracy issues that would likely impact nonbehavioral approaches (e.g., staff impressions). Subsequently, the authors were able to systematically evaluate the effectiveness of two interventions and demonstrate their effectiveness. In another adult-focused study, Lancioni et al. focused on text messaging skills with individuals with acquired brain injuries. To systematically evaluate the effectiveness of their intervention, the authors established operational definitions that allowed for the direct observation and measurement of target skills related to text messaging including number of messages sent, length of messages, the time needed to send and receive messages, and number of messages received and whether the individual read/listened to the message. Whereas this approach allowed for a systematic, empirical evaluation of the effects of the intervention, a nonbehavioral approach would not have allowed for a precise and accurate reflection of positive (or lack thereof) effects.

Many studies that illustrate the behavioral approach of ABA have also been conducted in the area of OBM pertaining to performance management (e.g., Fienup, Luiselli, Joy, Smyth, & Stein, 2013; Goomas, Smith, & Ludwig, 2011). For example, Fienup et al. (2013) evaluated an intervention intended to improve the performance of staff at a human services organization. Specifically, the authors intervened with the purpose of decreasing staff tardiness for supervision meetings. The authors measured latency from the scheduled beginning time for meetings until the actual time in which meetings began. This behavioral and observable measurement system minimized potential inaccurate inferences about the positive effects of the intervention they employed. Goomas et al. (2011) focused on the performance of employees at a retail distribution center. The authors directly measured the amount of time it took employees to complete specific tasks. By establishing direct measures of behavior, these authors were able to directly evaluate potential relations between their intervention and its effects on those targeted behaviors.

Analytic

The term analytic indicates that ABA emphasizes believable demonstrations of relations between behaviors of interest and environmental variables, interventions, and treatments under study. Systematic analyses of behavior are vital for the demonstration of experimental control with regard to the effects of independent variables (e.g., interventions and treatments) on dependent variables (e.g., socially relevant behaviors of interest). An emphasis is placed on the analytic nature of ABA because it is vital that applied behavior analysts base their practical recommendations on believable demonstrations (Baer et al., 1968, p. 93) that their interventions were responsible for positive changes in behaviors of interest. Thus, it is important that the inferences about causal relations between recommended interventions and positive outcomes should be based on systematic, empirical methods and demonstrations of experimental control.

Experimental control is achieved when an applied behavior analyst demonstrates a functional, or causal, relation between environmental variables of interest and behaviors of interest. In ABA, various single-subject experimental designs are utilized to demonstrate functional relations including (but not limited to) the reversal, multielement (and alternating treatments design), changing criterion, and multiple-baseline experimental designs. These basic designs share three common elements: (a) prediction—anticipated future levels of behavior, (b) verification—demonstration that the previously predicted levels of behavior would continue in the absence of a treatment, and (c) replication—repeating previous changes in behavior via the reintroduction and subsequent removal of the treatment across time, settings, and/or individuals.

The analysis dimension of ABA is illustrated in the child-based literature as reflected by emphasis on, and use of, various single-subject experimental designs to demonstrate functional relations between the independent variables (e.g., environmental variables, interventions, treatments) and socially relevant behaviors of interest. For example, in the study described above, Kadey, Piazza, et al. (2013) employed a reversal design to systematically demonstrate the relation between swallowing behavior (i.e., mouth cleans) demonstrated by a 5-year-old girl with feeding problems and specific texture levels. Using the reversal design, the authors first implemented a smooth texture level produced by a specific type of food processer (i.e., a Magic Bullet®) and documented the percentage of bite trials in which the child swallowed as reflected by mouth cleans. The authors conducted repeated sessions in this initial condition, and the child demonstrated high and relatively stable levels of swallowing behavior. The results of the first condition provided preliminary evidence of a relation between the child's swallowing behavior and the texture level of the food. However, without additional experimental manipulations, it would have been inappropriate to infer causality between food texture and swallowing. Therefore, the authors ended the condition and implemented a second condition in which pureed food was presented that was of a different texture than the food presented in the previous condition. The authors implemented repeated sessions in the second condition until they observed low and stable levels of swallowing. The results of the second condition provided additional evidence that the level of texture used in the first condition was responsible for the high levels of swallowing observed. However, the potential effects of extraneous variables on swallowing could not be ruled out (e.g., a variable outside of the evaluation may have coincided with the onset of the second condition and could have influenced the results). The authors reimplemented the initial condition and swallowing behavior increased back to levels observed during the initial condition. These results provided additional evidence that the high level swallowing resulted from the texture level rather than extraneous variables. The authors subsequently conducted an additional reversal (i.e., an additional puree condition and additional Magic Bullet® condition) and produced similar results. Thus, the co-occurrence of positive changes in the target behavior (i.e., swallowing) was demonstrated to occur only in the presence of the food texture produced by the Magic Bullet blender. Therefore, causality between positive effects observed with the swallowing behavior and the treatment could be reasonably inferred.

Normand (2008) provided an example of the use of a multiple-baseline (combined with an ABAB design), single-subject experimental design to demonstrate the functional relation between an intervention package and physical activity demonstrated by adults. Normand first introduced baseline conditions to each of four adult participants and measured the total number of steps taken by each participant. The treatment package (consisting of goal setting, self-monitoring, and feedback) was introduced with one of the participants after stable levels of steps taken were observed; while baseline continued to be implemented with the other three participants. Positive effects (i.e., increased levels of steps taken) were observed with the first participant while concurrently, levels of steps taken continued at consistent levels with the additional four participants. This result provided preliminary evidence that the treatment package was effective at increasing steps taken; however, extraneous variables could not be ruled out without replication of those effects across participants. Therefore, Normand introduced the intervention with the second participant while baseline conditions continued with the other three participants. Similar patterns of behavior were observed with the second participant as those observed with the first participant with an increase in steps taken. These results represented a replication of the positive effects observed with the first participant. Coupled with the continued consistent levels of steps taken with the other two participants during baseline conditions, evidence accrued suggesting a functional relation between the treatment package and an increase in steps taken. Normand went on to replicate the positive effects with the additional two participants, demonstrating three replications of the initial positive effects. Through this process, the author was able to rule out, to a reasonable degree, the possible effects of extraneous variables on the observed positive effects. Said another way, through the demonstration of functional relations, Normand could be confident that it was the treatment package that produced the positive results and not some other extra experimental variable(s).

Empirical methods that emphasize the demonstration of functional relations are also emphasized in the area of OBM. For example, Pampino, MacDonald, Mullin, and Wilder (2004) used a multiple-baseline, single-subject design to evaluate the effects of an intervention package consisting of task clarification, goal setting, positive reinforcement, and feedback on completion of maintenance tasks by workers in a framing and art store. The authors first collected baseline data prior to the implementation of the intervention package across two sets of duties. After stable levels of completion of duties were observed across both sets of duties, the authors implemented the intervention with one set of duties while continuing to collect baseline data with the second set of duties. Percentages of completion of the duties in the intervention condition immediately increased when the intervention was implemented, while levels of completion of the second set of duties (i.e., in baseline conditions) remained low. Next, the authors implemented the intervention with the second set of duties and an immediate increase in completion of those duties was observed; thus, the positive effects observed with the first set of duties were replicated with the second set of duties. The systematic methods used by the authors allowed them to infer causality between their intervention and the observed positive effects.

Technological

In addition to focusing on analysis and emphasizing functional relations through the use of appropriate experimental designs and the use of behavioral methods (e.g., precise measurements of target behaviors), ABA emphasizes thorough and accurate descriptions of procedures within the context of research and the application of behavioral interventions. Descriptions of procedures, operational definitions, and procedural integrity data are documented to allow other applied behavior analysts to replicate studies and evaluations in applied settings and research. A review of practically any study published in a peer-reviewed ABA journal (such as the Journal of Applied Behavior Analysis) will provide a demonstration of the technological aspect of ABA.

Conceptually Systematic

The practices utilized in ABA are applied in nature. However, there is a clear emphasis in ABA that these practices be conceptually systematic. Thus, basic behavioral principles empirically validated over many years by scientists and applied behavior analysts who conduct basic and applied research on the behavioral theories of experimental analysis of behavior underlie the practices of ABA. For example, intervention components that are based on conceptually systematic behavioral principles include (but are not limited to) reinforcement, extinction, punishment, stimulus control, discrimination, MOs, and schedules of reinforcement. Baer et al. (1968) asserted that by emphasizing behavioral principles along with precise descriptions of procedures, ABA would advance at a rate superior to an alternative approach that could be described as a collection of tricks (p. 96).

The emphasis on conceptual systems can be illustrated in the child-based behavioral literature pertaining to functional communication training (FCT; Carr & Durand, 1985). FCT involves (a) evaluating and identifying the reinforcer maintaining challenging behavior via a functional assessment (e.g., functional analysis; Carr & Durand, 1985; Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994); (b) training a new appropriate communicative behavior (e.g., card exchange, microswitch, sign language) and delivering the same reinforcer contingent on the response; (c) placing challenging behavior on extinction (i.e., reinforcement is withheld following occurrences of challenging behavior; Fisher et al., 1993; Hagopian, Fisher, Sullivan, Acquisto, & LeBlanc, 1998); and (d) in some cases, applying punishment contingent on challenging behavior (Hagopian et al., 1998; Wacker et al., 1990). Thus, the effectiveness of FCT is based on the behavioral mechanisms including reinforcement (positive and/or negative) and, in many cases, extinction and punishment, as well as training procedures such as the use of a time-delay prompt.

The approach of conceptualizing FCT using behavioral mechanisms and a conceptual system is distinct from a potential approach to the treatment that might focus on other aspects of the treatment. For example, a clinician focusing on FCT without considering the underlying conceptual system may favor conceptualizing the treatment as one that focuses on the utilization of technology (e.g., iPad technology, voice-output device) for communication and mistakenly assume that the effectiveness of the treatment is based on the provision of technology-based communicative techniques. Such an approach would be problematic for several reasons. First, without considering the antecedents and reinforcement contingencies associated with challenging behavior, while focusing solely on training communication using technology-based modalities, it is likely the treatment will fail to effectively treat the challenging behavior because the contingencies controlling the behavior will not have been addressed. Thus, to address the contingencies controlling the behavior, the effective applied behavior analyst considers the behavioral mechanisms responsible for the challenging behavior as well as the target-appropriate communicative behaviors (technology-based or otherwise). In addition, as Baer et al. (1968) asserted, without using a conceptual system when implementing the treatment, it is unlikely the clinician will generalize and apply the treatment effectively in other situations.

Guercio et al. (2012) provided an example of the application of a treatment based on a behavioral conceptual system for adult pathological gamblers in individuals with acquired brain injury. As described previously, the authors implemented a program that consisted of one-on-one treatment therapy sessions in which they focused on teaching the participants about the MOs, antecedents, and reinforcers associated with gambling behaviors. Thus, the treatment was explicitly based on behavioral mechanisms conceptualized as controlling gambling behavior. An alternative conceptualization of the treatment might minimize or omit the behavioral components of the approach and instead focus on the format for therapy (e.g., one-on-one sessions, client-centered discussions). Similar to FCT, however, the focus and reliance on behavioral mechanisms is vital to the effectiveness of the treatment as well as the effective generalization and application of the procedures by future clinicians.

The use of a behavioral conceptual system is also emphasized in the area of OBM. For example, Cunningham and Austin (2007) utilized an intervention package consisting of goal setting, task clarification (via modeling), and feedback (description of performance, praise) via weekly meetings to improve the performance of hospital operating room employees pertaining to hands-free operating techniques. The authors conceptualized the behavioral mechanism of the feedback component of the intervention package as positive reinforcement of the target behavior. An alternative conceptualization that would not incorporate an underlying behavioral mechanism might focus not on the mechanism of reinforcement, but rather the implementation of weekly meetings to discuss the performance of staff. However, future attempted applications of the intervention that emphasize elements of the intervention that were not responsible for the observed positive behavior (rather than the behavioral mechanism responsible; i.e., positive reinforcement) would be much less likely to be effective. It should also be noted that although not explicitly stated in the study, the goal setting and modeling components could be conceptualized as antecedent-based and intended to increase discrimination and occasion the desired behaviors.

Effective

Effectiveness is a dimension that emphasizes the practical quality of ABA practices. That is, the effectiveness dimension of ABA focuses on whether the individual whose behavior was changed and the family and care providers of the individual view the behavior change to be practical and significant. Applied behavior analysts determine the effectiveness of their procedures by evaluating their data, often through visual inspection using valid single-subject experimental designs (as opposed to the use of statistical procedures to determine if behavior change is significant). Additionally, ABA emphasizes judgments of socially acceptable levels of improvement of target behaviors.

An example from the child-based ABA literature pertains to the assessment and treatment of pica. Pica (i.e., the insertion of inedible objects into the oral cavity or the ingestion of inedible objects; Piazza et al., 1998; Roane, Kelly, & Fisher, 2003) can be a life-threatening behavior displayed by children with autism and other developmental disabilities. Falcomata, Roane, and Pabico (2007) conducted a study that involved the assessment and treatment of pica in a 12-year-old boy with autism. During the study, the authors evaluated several treatment approaches by comparing their effects to each other as well as baseline conditions. The treatments included enriched environment (i.e., continuous access to highly preferred stimuli) and enriched environment plus a timeout procedure (i.e., visual screen timeout). The results showed that both treatments were effective at decreasing pica in comparison to baseline conditions. However, although the enriched environment treatment decreased pica relative to baseline (in which a mean rate of 6.7 occurrences per minute were observed), pica still occurred at a mean of 1.8 occurrences per minute. Thus, although it could be argued that the treatment produced an improvement, the dangerous nature of the behavior dictated that this was not a practical, or effective, level of improvement. An acceptable level of practical improvement (i.e., a demonstration of effectiveness) with a dangerous behavior such as pica is zero or near zero occurrences. The results of the study also showed, however, that the second treatment consisting of enriched environment plus timeout produced near zero levels of pica. Thus, this was considered a practical outcome, and the treatment could be deemed effective.

A study conducted by Normand and Osborne (2010) provides an example of the demonstration of effectiveness within an adult-focused application of ABA to healthier food choices demonstrated by college students. The authors first implemented a baseline condition in which they assessed college students' food choices via receipts and food checklists and tracked their daily calorie intake. Next, the authors implemented an intervention that involved providing feedback to the students by showing them graphs depicting daily calorie and fat intake. Additionally, the authors provided information to the students on recommended daily consumption for food groups as well as recommended levels of sugar and fat intake. Decreases in calorie and fat intake were demonstrated with three of the four participants. With each of the participants for whom clear effects of the intervention were demonstrated, their intake levels during the intervention condition occurred at or below United States Dairy Association (USDA) recommended daily guidelines. The clear demonstration of an experimental effect within the multiple-baseline, single-subject experimental design in Normand and Osborne did not, in and of itself, confirm the effectiveness of the intervention. However, the USDA recommended daily guidelines provided a benchmark with which to evaluate effectiveness; the favorable comparison to that benchmark provided clear evidence of the effectiveness of the intervention.

Lebbon, Sigurdsson, and Austin (2012) provided an example of the demonstration of effectiveness in OBM-based ABA research. The authors evaluated an intervention package consisting of training, peer observations, peer-directed feedback, and graphic feedback. To evaluate the intervention package, the authors collected data on several dependent variables including Occupational Safety Health Administration recordable incidents, lost workdays, and peer observations. The results suggested that the intervention package decreased the total number of incidents and lost days when compared to preintervention conditions. The authors provided a cost-effectiveness analysis by comparing the average direct cost of individual work-related disabling injuries and other injuries to the total cost of the intervention given the reduction in injuries during the course of the study. The results suggested that the intervention was clearly cost-effective, providing evidence of the effectiveness of the intervention.

Generality

The last dimension of ABA places an emphasis on the extent to which gains are generalizable to other settings, caregivers, or behaviors. Generalization is important because it is not beneficial to improve a client's behavior only in settings (e.g., clinics) outside of the natural environment, particularly if the client only spends a few hours of his/her week outside the natural environment. The behavioral intervention is only beneficial if it improves behavior across different settings and when it is implemented by different individuals (e.g., multiple caregivers).

Silber and Martens (2010) provided an example of the application of child-focused ABA in which the dimension of generality was evident. The authors evaluated a multiple exemplar approach to a program for generalized oral reading fluency demonstrated by children in the first and second grades. Specifically, the authors compared three conditions including a control, a reading intervention that consisted of teaching key words and sentence structures, and a typical reading intervention consisting of preview and repeated readings. Following the implementation of each condition, the authors conducted probes with nontrained reading passages to evaluate the extent to which the children's learned skills generalized. The results showed that both reading interventions were more effective at promoting generalization of reading skills as evidenced by significantly higher scores during the generalization probes with untrained readings. By showing the spread of the positive effects of the interventions to untrained reading passages, the authors demonstrated the generality of the interventions.

Stokes, Luiselli, Reed, and Fleming (2010) provided an example of the emphasis on generalization in the ABA-based sports management literature. During the study, the authors evaluated the utility of descriptive feedback alone; descriptive feedback in combination with video-based feedback; and a combination of descriptive feedback, video-based feedback, and an audio-based feedback procedure (i.e., teaching with acoustical guidance, TAG) to improve line pass-blocking skills in high school football players. After demonstrating the effectiveness of the intervention package consisting of descriptive feedback, video-based feedback, and TAG with improvements in blocking, the authors assessed improvements during game situations (with four of the five participants) in the absence of the intervention. The results showed that all four players demonstrated high levels of correct blocking techniques during game situations suggesting that generalization had occurred with the intervention.

The generality dimension of ABA is also illustrated in numerous OBM-based ABA studies. For example, as described earlier, Ludwig and Geller (1997) evaluated two approaches to improving intersection stopping by pizza delivery drivers as well as generalization to nontargeted safe driving behaviors (i.e., turn signal usage, safety belt usage). Both interventions were shown to improve intersection stopping. However, significant increases in nontargeted turn signal and safety belt usage were demonstrated with the drivers who participated in the goal-setting process. Thus, the results suggested a high level of generality of the intervention.

Summary

Features of ABA include seven dimensions described by Baer et al. (1968) including applied, behavioral, analytic, technological, conceptually systematic, effective, and generalizable. Applied behavior analysts, through both applied work and research, have conducted practice characterized by these dimensions and features across populations and specific areas of focus for more than a half-century. In addition, assessment and intervention practices based on the principles of ABA have been implemented successfully in educational, clinical, sports, and business settings to address a wide range of behavioral issues.

This chapter highlighted the wide breadth and diversity of application of procedures and methodologies based on the discipline of ABA. Despite the impression that ABA is synonymous with specific assessment and treatment approaches to autism and developmental disabilities (e.g., Bowman & Baker, 2014), the wide range of studies described in this chapter in terms of populations, areas of focus, and settings illustrates the actual nature of the impact and discipline of ABA.

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Chapter 2

Applied Behavior Analytic Assessment and Treatment of Autism Spectrum Disorder

Wayne W. Fisher; Amanda N. Zangrillo    Center for Autism Spectrum Disorders, Munroe-Meyer Institute, The University of Nebraska Medical Center, Omaha, Nebraska, USA

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is typically identified in early childhood, with symptoms often presenting at or before 18 months (Blumberg et al., 2013). The hallmarks of ASD include marked impairments in social interaction, verbal and nonverbal communication, and restricted, repetitive interests and behaviors displayed in a variety of contexts. The prevalence of ASD has steadily increased, nearly tripling over the last decade (i.e., increasing from 1 in 150 children to approximately 1 in 50 children; Blumberg et al., 2013; Centers for Disease Control and Prevention, 2014). In this chapter, we provide (a) a review of diagnostic criteria and hallmarks of ASD and recent changes to the diagnostic criteria; (b) a discussion of the impact of the disorder in terms of prevalence rates, etiology, and prognosis; (c) an overview of evidence-based approaches to assessment and treatment; and (d) future directions and considerations for practitioners.

Keywords

Autism spectrum disorder

Early intensive behavioral intervention

Restricted and repetitive behaviors

Behavioral intervention

Type the word autism into any Internet search engine and the abundance of returned results is overwhelming. The prevalence of autism spectrum disorder (ASD) has steadily increased, nearly tripling over the last decade (i.e., increasing from 1 in 150 children to approximately 1 in 50 children; Blumberg et al., 2013; Centers for Disease Control and Prevention [CDC], 2014). Given this increase, it is not surprising that caregivers, clinicians, and the general public are generating considerable discussion about ASD. Eugen Bleuler provided an initial description of the symptoms of ASD in the early 1900s (Klinger, Dawson, & Renner, 2003). Over the past century, research has contributed significantly to the availability of information regarding diagnosis, assessment, and treatment of ASD. Unfortunately, not all research is created equal, and consumers are faced with the daunting task of differentiating empirical research and evidence-based practice from that which is invalid or pseudoscientific (National Autism Center, 2009). In this chapter, we provide (a) a review of the diagnostic criteria and hallmarks of ASD and recent changes to the diagnostic criteria; (b) a discussion of the impact of the disorder in terms of prevalence rates, etiology, and prognosis; (c) an overview of behavior analytic, evidence-based approaches to assessment and treatment; and (d) future directions and considerations for practitioners.

A little learning is a dang’rous thing; Drink deep or taste not…

Alexander Pope

The Impact of ASD on Affected Children and Their Families

The impact of autism on affected children and their families is difficult to overstate. In the absence of effective intervention, long-term outcomes for children diagnosed with ASD have generally been poor. For example, in one long-term follow-up study of adults affected by autism, only 4% lived independently, only 13% worked independently (primarily in low paying occupations), and only 26% had one or more friends (Howlin, 2005; Howlin, Goode, Hutton, & Rutter, 2004). More recent studies on adolescent and adult outcomes for persons with ASD have produced somewhat more optimistic results; however, many of these studies have focused on outcomes for a small sample of relatively high-functioning individuals (see Levy & Perry, 2011 for a review). Finally, parents and siblings of individuals affected by ASD are at increased risk for developing stress-related mental disorders (Dumas, Wolf, Fisman, & Culligan, 1991; Feldman et al., 2007; Lofholm, 2008).

Defining Features and Diagnosis

ASD is a neurodevelopmental disorder that is typically identified in early childhood, with symptoms often presenting at or before 18 months (Blumberg et al., 2013). Eugen Bleuler initially conceptualized autism as a form of childhood schizophrenia; however, ASD differs from schizophrenia on all of the factors that define a syndrome, including symptoms, age of onset, etiology, family history, and response to treatment. Based on the presentation of the unique symptoms associated with ASD, Leo Kanner and Hans Asperger later conceptualized autism and Asperger’s syndrome, respectively, as separate disorders in the early 1940s (Klinger et al., 2003), and in 2013 the diagnostic label was changed to ASD. Although the specific naming conventions have changed over the years, the hallmarks of ASD established in the Diagnostic and Statistical Manual of Mental Disorders 5th ed. (DSM-5; American Psychiatric Association [APA], 2013a) have generally remained consistent and are deeply rooted in impairments in social-communication behaviors (e.g., social interaction, verbal and nonverbal communication) and restricted and repetitive interests and behaviors in a variety of contexts, and across many domains (APA, 2013a).

Clinicians use the DSM-5 as a guide to determine if the symptoms displayed by an individual meet the diagnostic criteria for ASD diagnosis. The DSM-5 outlines five key diagnostic criteria that are required for diagnosing ASD: (a) an individual must display persistent impairments or deficits in social communication and social interaction; (b) an individual must display restricted, repetitive patterns of behavior, interests, or activities; (c) the symptoms must be present in early childhood; (d) symptoms produce clinically significant impairments in current functioning in a variety of contexts (e.g., home, work, and school); and (e) the symptoms cannot be better explained by intellectual disability or global developmental delay. Each category is evaluated separately, and each criterion specified in the five areas listed above must be met to provide an individual with a diagnosis of ASD (APA, 2013a). What follows is a discussion of the observable and measureable symptoms that are described in the first two areas of the diagnostic criteria.

Social Communication and Social Interaction

The category of social communication and social interaction is divided into three distinct subdivisions. The first subcategory includes skills related to social-emotional reciprocity. An individual experiencing marked delays or deficits in this subcategory may (a) rarely initiate conversation with others, (b) fail to look at or acknowledge others when his or her name is called or when others enter the room, and (c) intrude on what is typically called another individual’s personal space.

The second subcategory describes deficits or impairments in social interactions involving nonverbal communicative behaviors (e.g., deficits in coordinated use of verbal and nonverbal communication, eye contact). The third subcategory includes deficits or impairments in developing, maintaining, and understanding relationships (e.g., adjusting behavior to fit social contexts, absence of interest in peers). An individual must present with impairments or deficits in all three subcategories in order to meet the criteria for a diagnosis of ASD.

Restricted, Repetitive Patterns of Behavior, Interests, or Activities

The category of restricted, repetitive patterns of behavior, interests, or activities is also divided into four distinct subdivisions. The first subcategory includes stereotyped or repetitive (a) motor movements (e.g., hand flapping, toe walking, spinning in circles), (b) use of objects (e.g., repeatedly dropping objects and watching them fall, lining up objects), and/or (c) speech (e.g., pedantic or overly formal speech, idiosyncratic words or phrases, echolalia). Behaviors that are included in this subcategory may vary depending on the cognitive level and vocal abilities of the individual. The second area includes insistence on sameness, inflexible adherence to routines, and/or ritualized patterns of verbal or nonverbal behavior (e.g., rigidly following rules, insisting on wearing the same shirt each day). The third area includes highly restricted, fixated interests that are abnormal in intensity or focus (e.g., only talking about one topic, significantly restricted food preferences, preoccupation with a limited range of toys or activities). The last area includes hyper- or hyporeactivity to sensory input or unusual interest in sensory aspects of the environment (e.g., extreme responses to specific sounds, textures, changes in the environment, indifference to exposure to pain or temperatures). An individual must display marked impairment in at least two of the four subcategories noted above to meet the diagnostic criteria for restricted, repetitive patterns of behavior, interests, or activities.

The defining features of ASD (previously discussed) exist along a continuum and may manifest differently in each individual. Specific characteristics may develop over time (i.e., as the child matures and social interactions become more complex), change form or topography, and/or increase or decrease in intensity or level of impairment of daily functioning (i.e., following exposure to environmental consequences or early intervention services; APA, 2013a). Individuals diagnosed with ASD may also present with a variety of features that are not included as hallmarks of the disorder, but are associated features. These associated features include disturbances in feeding and sleeping (see Kodak & Piazza, 2008), delayed toilet training (Kodak & Grow, 2011), genetic and medical conditions (e.g., intellectual disability, seizure disorders, fragile-X syndrome; Klinger et al., 2003; Kodak & Grow, 2011), severe self-injury, and/or other related behavior problems (e.g., aggression, pica, elopement, tantrums, etc.; Jones, Lerman, & Laechago, 2014).

Modifications to the DSM

In 2013, the APA published the DSM-5, which included a number of revisions to the diagnostic criteria in the DSM-IV-Text Revision (TR; 2000) that have been somewhat controversial. The DSM-5 collapsed several of the DSM-IV-TR diagnoses (e.g., autistic disorder, Asperger syndrome) into a single disorder (i.e., ASD). In addition, Rett syndrome was considered a pervasive developmental disorder in DSM-IV-TR, but with DSM-5, a child with Rett syndrome would receive a diagnosis of ASD only if the new diagnostic criteria are met, in which case the diagnosis of Rett syndrome would be considered a specifier (e.g., ASD associated with the genetic condition called Rett syndrome; APA, 2013b). These changes have been controversial due to concerns that the new diagnostic criteria may be less sensitive than the prior version, which would result in fewer children being diagnosed with an ASD and receiving associated treatments (APA, 2013b). For example, a recent meta-analysis of studies comparing the DSM-5 and DSM-IV-TR criteria found that the former reduced the number of diagnosed cases of ASD by an average of 31% (Kulage, Smaldone, & Cohn, 2014). However, other studies have applied diagnostic criteria specifically developed for the DSM-5 and found high levels of selectivity (percentage of true or actual cases of ASD identified) and specificity (percentage of noncases of ASD correctly identified as such; Carrington et al., 2014; Kent et al., 2013). Additional research will be needed before this controversy is satisfactorily resolved.

Diagnostic Assessment

A variety of etiological factors have been associated with increased risk of ASD (e.g., high paternal age: Kolevzon, Gross, & Reichenberg, 2007; fragile-X syndrome: Kaufmann et al., 2004), but none have shown a one-to-one correspondence with the behavioral syndrome; thus, clinicians must rely on indirect and direct observations of the measurable dimensions of an individual’s behavior (as opposed to biological or genetic determinants) to render a diagnosis. Routine medical evaluations, such as well-child doctor visits, play a key role in early detection and access to treatment for many children and families. Examples of screening tools aimed specifically at identifying the hallmarks of ASD include the Checklist for Autism in Toddlers (CHAT; Baron-Cohen, Allen, & Gillberg, 1992), Modified Checklist for Autism in Toddlers (M-CHAT; Robins, Fein, Barton, & Green, 2001), and Screening Tool for Autism in Toddlers (Stone, Coonrod, & Ousley, 2000; see Taubman, Leaf, & McEachin, 2011 for a review). Pediatricians or caregivers may request additional referrals for assessment from clinicians with specialized training in diagnostic assessment with young children to determine if the current presentation meets the diagnostic criterion for ASD.

With regard to diagnostic assessment, the specific indirect and direct assessment methods used vary from clinic to clinic. It is important to note that no one assessment tool or method should be used alone to assess an individual. Many diagnostic evaluations use multimethod (e.g., indirect and direct methods) and multidisciplinary approaches during the diagnostic assessment process. For example, a clinician may use caregiver interviews and rating scales (such as the tools listed above), in combination with neuropsychological assessments, speech and language evaluations, assessments of adaptive functioning (e.g., Vineland Adaptive Behavior Scale-Second Edition; Sparrow, Cicchetti, & Balla, 2005), direct observation, and standardized assessments aimed at assessing the defining features of ASD. Tools that have been empirically validated for the diagnosis of ASD include Autism Diagnostic Interview—Revised (e.g., ADI-R; Rutter, Le Couteur, & Lord, 2003), Childhood Autism Rating Scale-Second Edition (CARS2; Schopler, Van Bourgondien, Wellman, & Love, 2010), Gilliam Autism Rating Scale (GARS; Gilliam, 2006), and Autism Diagnostic Observation Schedule, Second Edition (ADOS-2; Lord, Rutter, DiLavore, & Risi, 2001).

Estimates of the Prevalence of ASD

Estimates of the prevalence of ASD have varied widely over time and across studies. The latest reports from the CDC estimate the prevalence of ASD at 1 in 68 children (CDC, 2014), whereas the median estimate for prevalence studies worldwide since the 1960s is about 1 in 162 (Elsabbagh et al., 2012). In addition, Elsabbagh et al. found that the worldwide prevalence estimates have shown a statistically significant increase over time (r = 0.4; p < 0.01). Moreover, a small number of recent, well-designed studies (Baird et al., 2006; Kawamura, Takahashi, & Ishii, 2008; Kim et al., 2011) that have employed more vigorous case-ascertainment methods (i.e., using systematic, population-wide screening and diagnostic procedures rather than simply counting cases that have been identified and diagnosed clinically) reported prevalence estimates as high as 1 in 38 children (or 2.6% of the childhood population). Although some authors have argued that the increase in the reported prevalence rates of ASD over time represents a true increase in the number of affected children, the observed increase is probably due to (a) more inclusive diagnostic criteria, (b) increased recognition and diagnosis of the disorder, and (c) diagnostic substitution (i.e., children who may have received other diagnoses in the past are more likely to be diagnosed with ASD today; Elsabbagh et al., 2012). Finally, the results of the recent, well-designed studies that have used more aggressive case-ascertainment methods suggest that the observed prevalence of autism may continue to rise for some time going forward.

Etiological Factors in ASD

Early accounts of the etiology of ASD varied between those that attributed the disorder to emotionally cold and distant parenting practices (the so-called refrigerator-mother hypothesis; Bettelheim, 1967; Kanner, 1943) to those that described it as primarily a biological condition (Rimland, 1964). Leo Kanner, who first applied the label of autism to this group of children, reportedly oscillated multiple times between the two views, calling it an inborn condition in his original paper (Kanner, 1943), attributing the disorder to parental inadequacies in a later publication (Kanner, 1954), and then vacillating between these two positions later on (see Rapin, 2011 and Sanua, 1990 for more detailed discussions). Today, ASD is viewed as having primarily a neurobiological basis due to (a) higher than expected concordance rates among monozygotic twins and among close family relatives (Folstein & Rutter, 1977); (b) frequent co-occurring clinical features associated with neurobiological conditions, such as seizures (Deykin & MacMahom, 1979) and genetic conditions (e.g., fragile-X syndrome: Harris et al., 2008); and (c) a wide variety of brain-imaging studies showing anomalies of brain structure (Stanfield et al., 2008), function (Pelphrey & Carter, 2008), and connectivity (Wass, 2011).

History of Behavioral Treatment of ASD

Jean-Marc-Gaspard Itard (1801), a French physician, treated a feral boy named Victor who lived on his own in the wild for 5 years or more until he was approximately 12 years old. Victor was described as having a number of symptoms of ASD, including a lack of communication and interest in social interaction and stereotypic motor responses. However, there has been considerable debate as to whether the symptoms resulted from his social isolation in the wild or whether his caretakers may have abandoned him due to a congenital behavior disorder, such as ASD (Frith, 1989; Lane, 1976). Itard’s approach to treatment included (a) individualized instruction, (b) beginning with the child’s current level of performance and then introducing increasingly more difficult material, (c) imitation training, and (d) delivering immediate rewards for correct and appropriate responses, procedures that remain highly relevant to the treatment of ASD today. After about 5 years of intervention, Victor could read and follow simple spoken or written sentences, request preferred items or activities using gestures or simple written phrases, and discriminate basic emotions expressed by others, but he never learned to emit spoken language. If Victor was on the autism spectrum, then Itard’s description of his work with this boy represents the first detailed account of a child with ASD as well as the treatment of the symptoms of this disorder (Thompson, 2013). Little, if any progress was made in the treatment of ASD between Itard’s time and the early