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Applied Behavior Analysis and Early Intensive Behavioral Intervention 

Applied Behavior Analysis and Early Intensive Behavioral Intervention
Chapter:
Applied Behavior Analysis and Early Intensive Behavioral Intervention
Author(s):

Tristram Smith

DOI:
10.1093/med/9780195371826.003.0066
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Points of Interest

  • Applied behavior analysis (ABA) is a discipline of research and practice within the helping professions. ABA interventions are implemented in many settings, with many different clinical and nonclinical populations.

  • ABA interventions for individuals with autism spectrum disorders (ASD) primarily involve strategies based on operant conditioning, such as systematically reinforcing target behaviors and teaching individuals to distinguish between different cues in their environments.

  • In both research and practice settings, ABA interventions are routinely evaluated with single-case experimental designs in which each individual serves as his or her own control.

  • One ABA intervention format, discrete trial training (DTT), is designed to help individuals with ASD master new skills rapidly by breaking down instruction into a series of short, simple learning units, each of which lasts only a few seconds and has a clear beginning and end. Other ABA intervention formats are more loosely structured and are used to promote generalization from the teaching situation to everyday settings.

  • Research suggests that when implemented intensively (20–40 hours per week) and early (beginning prior to age 4 years), ABA may enable some children to make significant gains in IQ and other standardized test scores.

  • Many studies indicate that ABA interventions can help individuals with ASD learn new skills, but these studies have involved small numbers of subjects, most of whom are young, developmentally delayed, or both. Thus, larger studies that include a broader range of individuals with ASD are needed.

ABA draws on principles of learning theory to help people learn new skills and overcome behavior problems (Cooper, Heron, & Heward, 2007). ABA has become an important intervention strategy for persons with ASD, but, more generally, it is an applied science and profession that is practiced in diverse contexts. Examples include general and special education at all grade levels (Heward et al., 2005), psychotherapy for a variety of behavioral disorders (Woods & Kanter, 2007), safety programs at job sites and other locations (Geller, 2001), management of business organizations (MacWhinney, Redmon, & Johnson, 2001), and interventions to promote health and well-being (Cummings, O’Donahue, & Ferguson, 2003).

In ABA, the term applied refers to a focus on socially relevant outcomes (Baer, Wolf, & Risley, 1968). For individuals with autism, ABA practitioners and researchers (referred to as behavior analysts) have emphasized outcomes such as moving out of institutions into the community (Lovaas et al., 1973), entering general education classes (Lovaas, 1987), strengthening relationships with typically developing peers (Strain & Schwartz, 2001), and enabling caregivers to become effective teachers for their children (Johnson et al., 2007).

The term behavioral in ABA reflects an emphasis on measurable outcomes. Behavior analysts consider any action that can be measured to be a behavior (Baer et al., 1968). Thus, the defining features of ASD (problems with reciprocal social interaction, limited social communication, and intense repetitive behaviors or narrow interests) are all considered behaviors. Associated features of ASD, such as delays in cognitive and self-help skills, are also viewed as behaviors. Because internal states such as thoughts and feelings are associated with observable actions such as verbalizations, facial expressions, and body language, they too are deemed to be behaviors.

Analysis indicates that decisions about interventions derive from a systematic data-based evaluation. Data collection usually involves direct observations that are repeated on multiple occasions with the same individual over time. These observations are often supplemented by assessments of the acceptability of interventions and outcomes to consumers and caregivers (Wolf, 1978), as gauged from ratings or interviews.

Key Concepts

Behavior analysts recognize that ASD are biological syndromes and that research on genetic and neurological etiologies is necessary to advance understanding of the disorder (Smith, McAdam, & Napolitano, 2007). However, they also believe that it is possible to develop effective interventions without knowing the precise etiologies of ASD (Lovaas & Smith, 2003). They posit that whatever the etiologies turn out to be, the biological functioning in individuals with ASD leads them to be “ill-fitted” to typical environments (Bijou & Ghezzi, 1999; Lovaas & Smith, 1989) and that environmental modifications can promote behavior changes that improve their functioning and quality of life.

ABA emphasizes careful assessment of how environmental events influence the behavior of an individual. ABA studies show that many significant events involve operant learning, which occurs in all humans and many other organisms. This kind of learning takes place when an antecedent event sets the occasion for a behavior and a consequent event either increases or decreases the likelihood that the behavior will occur again. An antecedent event is a change within the individual or in the external environment that occurs just prior to the behavior and acts as a trigger. A consequent event is a change that immediately follows the behavior. Consequent events that increase behavior are called reinforcers; consequent events that decrease behavior are said to result in extinction. For example, when an individual with ASD sees a peer (antecedent event), she may make eye contact and say “Hi.” If the consequence is a smile and praise from the peer (a reinforcer), the student is likely to greet the peer in the future. However, if the peer walks by without acknowledging the greeting, the student may not greet the peer on subsequent occasions because the behavior was not reinforced. Behavior analysts use the term three-term contingency to describe this relationship among the antecedent, behavior, and consequence.

Behavior analysts note that humans can acquire a three-term contingency without experiencing it directly. Through modeling, an individual learns a contingency by observing others. Thus, an individual with ASD might be taught how to make greetings by watching two people greet each other. In rule-governed behavior, the individual is merely told about the antecedent–behavior–consequence relationship. For example, a person with ASD might learn greetings by hearing an instructor explain, “When you greet others, it’s important to make eye contact and say ‘Hi’ or ‘Hello’ to show you’re interested.” In equivalence class formation, an individual may learn that stimuli are associated with one another even if they have never been presented together. If an individual finds out that the spoken word “ball” corresponds to a picture of a ball, and that this spoken word also corresponds to the written word “ball,” he is likely to associate the picture with written word, despite never being taught this association (Sidman, 1994).

As individuals learn new three-term contingencies, it becomes important for them to discriminate among antecedents. Discrimination learning involves giving different responses to different antecedents. For example, if a teacher holds up a ball and asks “What is it?,” the correct response is to say “ball.” However, if the teacher holds up a cup and asks “What is it?,” the correct response is to say “cup” (and not “ball”). To help individuals make discriminations, behavior analysts systematically use prompting procedures such as providing physical, gestural, or verbal guidance to perform a behavior in response to an antecedent. Prompts are gradually reduced and eventually eliminated as the individual masters the discrimination. Throughout this instruction, correct responses may be reinforced immediately.

In ABA, an establishing operation (EO) is an event that alters the reinforcement value of a consequence. An EO also may alter the frequency of behaviors that the individual uses to obtain the consequence. For example, placing a favorite toy in sight but out of reach may increase both the reinforcement value of the toy and the rate at which an individual requests the toy. This situation creates opportunities to expand the individual’s communication skills in ways such as requiring the individual to add more words to the request or to coordinate the request with eye contact. Systematic use of EOs is a central component of the incidental or “naturalistic” teaching approaches described in the next chapter.

Another common ABA procedure is task analysis, which consists of breaking down a complex skill into its component steps. For example, most self-help skills require completion of a series of steps. To wash hands, an individual must turn on the water, place her hands under the tap, apply soap, rub her hands together, and so on. Once behavior analysts have identified the steps, they can teach the skill with chaining procedures, in which steps are taught separately and subsequently linked together; and shaping, in which successive approximations of a behavior are taught (e.g., drying hands more and more completely).

Application of Applied Behavior Analysis Concepts to Autism Spectrum Disorders

In all, behavior analysts emphasize a rather small number of key concepts—mainly, the three-term contingency (antecedent–behavior–consequence), reinforcement, discrimination learning, and a handful of others. To behavior analysts, this short list has the virtue of parsimony (Lovaas & Smith, 1989). To many others, however, it seems too reductionistic to give an adequate account of ASD and support appropriate interventions (Greenspan, 2000). One reason for skepticism is that although most ABA concepts apply to humans and nonhumans alike, the defining features of ASD involve difficulties with skills that are unique to humans, such as reciprocal communication, creativity, and social interaction.

Behavior analysts have attempted to describe these difficulties in ABA terms. In ABA, communication is a particular kind of operant learning referred to as verbal behavior (Skinner, 1957). From this perspective, communication can be classified into different categories based on its function. In ABA terminology, mands include requests, questions, commands, and advice whose primary controlling variable is an EO, such as deprivation. For example, either stating a request or having a tantrum to obtain a favorite object could be a mand in which the reinforcer is receiving the object from another person and the establishing operation is lack of access to the object. Communication that occurs in the presence of a nonverbal discriminative stimulus is called a tact. Opinions, observations, replies to many questions, and verbal reports are all examples of tacts. Intraverbals are another class of communication that consist of verbal responses to a verbal discriminative stimulus, as occur in conversations between two people. An autoclitic is a unit of verbal behavior that clarifies or alters the meaning of other verbal behavior. Examples include plurals and verb tenses, which specify the number and timing, respectively, of other sentence structures and words such as not, which reverse the meaning of phrases.

From this perspective, many individuals with ASD make frequent mands, but the mands tend to be limited in variety or complexity (or both). Other classes of communication (tacts, intraverbals, etc.) may occur less often or may be inappropriate to the situation. (In ABA terms, the antecedents may differ from the antecedents for communication by typically developing individuals). The analysis of verbal behavior has had a strong influence on ABA interventions for enhancing communication skills (e.g., Bondy, Tincani, & Frost, 2004; Sundberg & Michael, 2001).

Creativity is defined in ABA in terms of fluency (number of responses), originality (novelty of responses), variability (differences between responses), flexibility (use of a stimulus for multiple purposes), and divergent thinking (problem solving) (Neuringer, 2004). By reinforcing responses with these characteristics, ABA practitioners seek to increase creativity (e.g., Lee, McComas, & Jawor, 2002).

Social interaction similarly can be characterized in terms of discriminative stimuli and reinforcers. For example, joint attention, which is an area of particular difficulty for young children with ASD, involves sharing an experience with another person (Mundy & Crawson, 1997). An example is looking at an adult, then looking at a toy, and then looking back at the adult. From an ABA standpoint, joint attention requires that the adult and toy each function both as discriminative stimuli and as reinforcers (Dube et al., 2004). ABA teaching methods for systematically establishing these functions may increase joint attention (Whalen & Schreibman, 2003). For older and more advanced individuals with ASD, problems with social interaction are often attributed to a lack of “theory of mind” (Baron-Cohen, 1995). That is, they struggle to explain, predict, and interpret the behavior of people in terms of mental states such as desires, beliefs, feelings, and thoughts. To behavior analysts, this problem may reflect an inability to detect social cues or a limited repertoire of responses to those cues.

Behavior analysts suggest that individuals with ASD tend to have learning styles that contribute to their difficulties in communication, social interaction, and overly repetitive or restrictive activities. For example, stimulus overselectivity, which is the tendency to focus on only one element of a complex antecedent, may interfere with generalizing communication skills to novel situations (Wilkerson & McIlvane, 1997), establishing joint attention, and detecting social cues (Koegel & Koegel, 2006). Inability to form equivalence classes may impede acquisition of abstract concepts (Wilkerson & McIlvane, 1997). A need for consistent, immediate reinforcement may deter individuals with ASD from engaging in social situations, which often have unpredictable outcomes (Bijou & Ghezzi, 1999).

In sum, relying on just a few concepts, behavior analysts have offered descriptions of the defining features of ASD. Of course, the adequacy of these descriptions is open to debate, but they have provided the basis for a large number of intervention studies, to which this chapter now turns.

Research Methods

Although other interventions such as psychotropic medications are also tested scientifically, a distinctive feature of ABA is that the same methodology is routinely used in both research and applied settings. This methodology is largely one of single-case research design in which individuals serve as their own controls, and interventions are evaluated for each person to whom they are applied (Bailey & Burch, 2002). Typically, the design involves comparing a baseline phase in which individuals receive no intervention to one or more intervention phases, with data collected continuously through all phases. If the behavior improves relative to the baseline phase each time that the intervention is introduced, one can conclude that the treatment may have produced this improvement. If the behavior does not improve, the intervention is refined or changed.

One single-case methodology is the alternating treatment design, also called a multi-element design (Barlow & Hersen, 1984). In this design, intervention is implemented on alternate days or sessions; on the other days or sessions, there is no intervention. This design is used when the effects of an intervention are expected to occur immediately. It also can be deployed as an assessment tool. For example, in a procedure called analog functional analysis, different experimental conditions are presented in an alternating treatment design to identify factors that may be maintaining a problem behavior. As an illustration, Ahearn et al. (2007) examined vocal stereotypy displayed by four children with autism. Following a standard functional analysis procedure developed by Iwata et al. (1994), participants’ rates of vocal stereotypy were compared across four conditions, each of which was implemented in 5-minute sessions. In the alone condition, the participant was left by him- or herself. In the play condition, the participant was given the opportunity to play freely with toys. In the attention condition, the participant again played with toys, and the experimenter provided attention to the participant whenever the participant engaged in vocal stereotypy. In the demand condition, the experimenter made routine requests of the participants but withheld requests for 15 seconds in response to participants’ stereotypy. Figure 58-1 presents data for one participant, Mitch. Each line in the figure corresponds to one of the four experimental conditions. The data reveal that Mitch’s stereotypy occurred with the greatest frequency during the alone condition. This funding suggests that intervention strategies such as arranging the environment to minimize unstructured, alone time might be effective. The remaining participants showed different patterns in their data, indicating that appropriate interventions for them might not be the same as those for Mitch.

Figure 58–1. Example of an alternating treatment (multi-element) design. Percentage of observation intervals with stereotypic behavior for Mitch across four experimental conditions: Alone, Play, Attention, and Demand. Reprinted with permission from Ahearn, W. H., Clark, K. M., MacDonald, R. P. F., & Chung, B. I. (2007). Assessing and treating vocal stereotypy in children with autism. Journal of Applied Behavior Analysis, 40, 263–275. © Society for the Experimental Analysis of Behavior, 2007.

Figure 58–1.
Example of an alternating treatment (multi-element) design. Percentage of observation intervals with stereotypic behavior for Mitch across four experimental conditions: Alone, Play, Attention, and Demand. Reprinted with permission from Ahearn, W. H., Clark, K. M., MacDonald, R. P. F., & Chung, B. I. (2007). Assessing and treating vocal stereotypy in children with autism. Journal of Applied Behavior Analysis, 40, 263–275. © Society for the Experimental Analysis of Behavior, 2007.

When an intervention might take longer to have an impact, the alternating treatment design may not be suitable, but another option is the reversal design, in which a baseline of several sessions, days, or weeks is followed by an intervention, followed by a return to the baseline phase, and so on. A reversal design can yield particularly strong evidence that an intervention causes behavior change for an individual participant (Barlow & Hersen, 1984). For example, Anglesea, Hoch, and Taylor (2008) used a reversal design to test an intervention for slowing down three teenagers with ASD who ate too rapidly. During the baseline condition, participants wore the pager, but it did not vibrate. During the intervention condition, the pager vibrated at 10- to 30-second intervals. Figure 58-2 shows data for one participant, Mark. As indicated in the figure, the baseline condition (pager prompt absent) was in effect for seven sessions, followed by six sessions of the intervention condition (pager prompt present), back to the baseline condition for another seven sessions, and finally back to the intervention condition for seven sessions. The black line shows the average number of seconds that Mark took to consume each bite during the session, whereas the gray line shows the total number of bites per session.

Figure 58–2. Example of a reversal design. Total eating time in seconds and number of bites to consume target foods for Mark across sessions. “Pager Prompt Absent” is the baseline condition. “Pager Prompt Present” is the intervention condition. Reprinted with permission from Anglesea, M. M., Hoch, H., & Taylor, B. A. (2008). Reducing rapid eating in teenagers with autism: Use of a pager prompt. Journal of Applied Behavior Analysis, 41, 107–111. © Society for the Experimental Analysis of Behavior, 2008.

Figure 58–2.
Example of a reversal design. Total eating time in seconds and number of bites to consume target foods for Mark across sessions. “Pager Prompt Absent” is the baseline condition. “Pager Prompt Present” is the intervention condition. Reprinted with permission from Anglesea, M. M., Hoch, H., & Taylor, B. A. (2008). Reducing rapid eating in teenagers with autism: Use of a pager prompt. Journal of Applied Behavior Analysis, 41, 107–111. © Society for the Experimental Analysis of Behavior, 2008.

It can be seen that, going from the first baseline condition to the first intervention condition, Mark’s time to consume each bite greatly increased, and the number of bites decreased. When he returned to the baseline condition, he reverted to the rates he had shown during the first baseline condition. However, re-introduction of the intervention replicated the gains made in the first intervention condition. This result demonstrates that the vibrating pager was effective in bringing down Mark’s rate of eating.

Although useful for testing whether an intervention alters an already acquired behavior, alternating treatment and reversal designs are usually not appropriate for evaluating interventions intended to teach new skills. Such interventions should produce long-lasting increases in skill levels rather than gains that disappear as soon as intervention is withdrawn. A single-case methodology that allows for testing of more permanent effects is the multiple baseline design, which involves having two or more baseline phases that are of varying lengths and then applying treatment to one baseline at a time (Barlow & Hersen, 1984). For example, Betz, Higbee, and Reagon (2008) incorporated a multiple baseline design to evaluate an intervention for increasing peer interactions in three pairs of preschool children with autism. The intervention involved teaching each participant to follow a schedule that consisted of a series of photographs depicting games. The study included four phases: baseline, teaching, maintenance, re-scheduling (when the sequence of photographs was varied), and generalization (when new games were introduced). Figure 58-3 displays the results. The thinner line represents the percentage of intervals during which interaction occurred. The heavier line depicts the percentage of intervals during which instructors provided prompts for interaction. The first pair, Ali and Dillon (top of Figure 58-3), rapidly increased their rate of peer interaction and maintained this increase for the remainder of the study. At the same time, the rate of prompting decreased. A similar pattern emerged for the second pair, Brady and David (middle of Figure 58-3). This pair also participated in a reversal probe session during which the photographic activity schedule was removed (between the re-sequencing and generalization phases, as indicated in Figure 58-3). They seldom interacted during that session and thus appeared to depend on having the schedule available. However, they did interact during novel games in the generalization phase (with the schedule present). The third pair, Nathan and Jackson (bottom of Figure 58-3), also made gains when they were taught to follow the schedule. Overall, then, the schedule increased interactions across all three pairs of children with autism. Moreover, gains endured over time and extended to novel games, provided that teachers continued to provide a schedule.

Figure 58–3. Example of a multiple baseline design. Results of the joint activity schedule intervention for Ali and Dillon (top), Brady and David (middle), and Nathan and Jackson (bottom). The intervention is introduced in the teaching phase and extended across subsequent phases of data collection. Reprinted with permission from Betz, A., Higbee, T. S., & Reagon, K. A. (2008). Using joint activity schedules to promote peer engagement in preschoolers with autism. Journal of Applied Behavior Analysis, 41, 237–241. © Society for the Experimental Analysis of Behavior, 2008.

Figure 58–3.
Example of a multiple baseline design. Results of the joint activity schedule intervention for Ali and Dillon (top), Brady and David (middle), and Nathan and Jackson (bottom). The intervention is introduced in the teaching phase and extended across subsequent phases of data collection. Reprinted with permission from Betz, A., Higbee, T. S., & Reagon, K. A. (2008). Using joint activity schedules to promote peer engagement in preschoolers with autism. Journal of Applied Behavior Analysis, 41, 237–241. © Society for the Experimental Analysis of Behavior, 2008.

Despite their extensive use in ABA, single-case designs remain somewhat controversial. Many psychologists and educators regard such designs as rigorous tests of the efficacy of an intervention. The clinical psychology division of the American Psychological Association suggests designating interventions as evidence-based if there are either two randomized clinical trials (RCTs) or a series of nine or more independent, well-designed single-case studies (Chambless & Hollon, 1998). The Council on Exceptional Children requires only six such studies, but with more stringent methodological benchmarks (Horner et al., 2005). Some investigators use single-case designs to evaluate interventions that originated outside of ABA (e.g., Rogers et al., 2006).

In contrast, criteria for identifying evidence-based medical interventions characterize single-case experiments as weak forms of evidence, on a par with uncontrolled case studies (Guyatt et al., 2008; Higgins & Green, 2006). According to this perspective, single-case experiments offer little more than anecdotal information, and other methodologies—particularly RCTs—are necessary to establish an intervention as evidence-based.

A working group that was convened by the National Institute of Mental Health proposed a middle ground (Smith et al., 2007; see also Reichow, Volkmar, & Cicchetti, 2008). The group noted that single-case experiments have greater methodological rigor than case studies because they provide continuous measures of the outcome variable and systematic replication of intervention effects. The group also suggested that there are some circumstances under which single-case experiments might stand alone as evidence for an intervention, but other circumstances under which it would be important to conduct further evaluations in RCTs. Single-case studies are best suited for evaluating the immediate effects of a specific intervention on a particular behavior for an individual participant. As such, they often suffice for testing interventions such as procedures to teach a new self-help skill. However, they may need to be followed by RCTs if it is important to look at more long-term and global outcomes, test combinations of interventions or compare alternate interventions, or evaluate outcomes across large groups of participants. For example, it might be useful to compare ABA interventions for problem behavior to psychotropic medication or to a combination of ABA and medication. Also, it might be informative to put together a package of ABA interventions to increase peer interactions and assess outcomes on general indices of social functioning such as reductions in core features of autism and increases in the quality of friendships and relationships with family members (Smith et al., 2007).

Applied Behavior Analysis Intervention Strategies

Many ABA interventions for individuals with ASD have support from multiple single-case studies. These interventions focus on either overcoming behavioral deficits (increasing the skillfulness or frequency of a behavior) or reducing behavioral excesses (decreasing the rate or severity of challenging behavior). Interventions for overcoming behavioral deficits range from highly structured teaching methods to more loosely structured methods and incidental teaching in which instruction is embedded in the context of everyday activities. (Incidental teaching methods are described in more detail in Chapter 59). Interventions for reducing behavioral excesses are based on an assessment of antecedents that may trigger a behavior and consequences that may reinforce it. The focus is mainly on preventing the occurrence of such behavior, but it is usually also necessary to consider how to respond when the behavior is displayed.

Discrete Trial Training

An especially distinctive ABA intervention is discrete trial training (DTT), which is a highly structured teaching format characterized by (1) one-to-one interaction between the practitioner and the child in a distraction free environment; (2) clear and concise instructions from the practitioner; (3) highly specific procedures for prompting and fading; and (4) immediate reinforcement such as praise or a preferred toy for correct responding (Smith, 2001). As a learner masters a new skill in DTT, interventionists aim to promote generalization of the skill to everyday environments by systematically loosening the format. For example, they may conduct sessions in many different settings, vary the instructions, reduce the frequency of reinforcement, and spread out the times when they ask the learner to practice the skill.

DTT is commonly implemented to shape new behaviors that were not previously in the repertoire of an individual with ASD, such as new speech sounds or motor skills. It is also emphasized in discrimination learning tasks such as imitating actions performed by another individual, matching identical objects or pictures to each other, labeling objects expressively or receptively, comprehending language concepts such as opposite pairs (e.g., big/little) and prepositions, and completing cognitive or preacademic tasks (e.g., counting objects or sequencing pictures).

DTT has been found to be effective in many single-case experiments (Goldstein, 2002) and outcome studies of early intervention programs in which DTT is a primary intervention procedure (reviewed later in this chapter). Behavior analysts offer several reasons why DTT may work (Smith, 2001). First, it breaks the continuous flow of social interaction into separate units that have a clear beginning and end (Newson, 1998). This simplification may help individuals with ASD—particularly those who are young or developmentally delayed—to learn the basic structure of an interaction between two people. Also, the trials have a predictable structure, and DTT sessions often involve repeating an instruction multiple times while systematically reducing prompts. This format may fit the preference that many individuals with ASD have for routine over novelty. In addition, DTT often involves breaking down a skill into small steps and teaching steps individually. Such an approach may be consistent with the detail-oriented learning style of individuals with ASD. Further, because each trial is relatively short (usually 5–20 seconds), DTT affords a large number of learning opportunities, thereby promoting rapid acquisition of new skills. Finally, the one-to-one instruction allows close monitoring of an individual’s progress and careful tailoring of the instruction for the individual (Smith, 2001).

However, DTT also has important limitations (Smith, 2001). Because it requires setting up a tightly controlled environment with very specific cues, prompts, and instructional materials, skills may not generalize from DTT to everyday settings such as home or school even after interventionists systematically loosen the format. In addition, because it involves having children with ASD respond to cues from the interventionist, children may not initiate the use of skills that they acquire in DTT. Also, DTT is labor-intensive in that it consists of one-to-one instruction with the interventionist continually providing cues.

A more general concern is that DTT differs in many respects from the kinds of situations in which most children learn social and communication skills (Koegel & Koegel, 1995; Prizant & Wetherby, 2005). During the toddler and preschool years, most typically developing children learn these and other skills in the context of playful routines with caregivers, interactive games with peers and adults, make-believe activities, and independent exploration (Prizant & Wetherby, 2005). They seldom learn from being drilled. Moreover, typically developing children often learn by initiating activities to which others respond, rather than the other way around, as occurs in DTT. Although structured teaching becomes increasingly important as children grow older, unstructured times remain crucial for their development (Elkind, 2001).

For behavior analysts who rely on DTT, however, the differences between DTT and typical learning situations are precisely the point (Smith, 2001). Children with ASD present for treatment because, to varying degrees, they have been unsuccessful in learning social and communication skills in the same way that other children do. Although it sometimes may be possible to help individuals with ASD by finding or creating teachable moments during everyday activities, it may be necessary at other times to design an environment that better suits their learning styles (Lovaas & Smith, 1989).

DTT remains a central component of many long-established ABA programs, particularly for young children with ASD (Stahmer, Collings, & Palinakas, 2005). It is used in all comprehensive ABA programs that have been described in a manual and tested in published, controlled outcome studies of toddlers and preschoolers with ASD (cf. Rogers & Vismara, 2008). However, research indicates that it can be less effective than incidental or naturalistic teaching approaches (described in the next chapter) under some circumstances (Delprato, 2001), and outcome studies of comprehensive ABA models that place a greater emphasis on such approaches are currently underway. Also, as discussed, the highly structured format of DTT has both advantages and disadvantages. Therefore, DTT is not a standalone intervention for individuals with ASD. Rather, it needs to be implemented in conjunction with other intervention methods (Smith, 2001). In addition, there may be individual differences in how children with ASD respond to DTT as compared to incidental teaching. For example, Sherer and Schreibman (2005) found that although some children with ASD responded well to incidental teaching, others did not and might have fared better in an intervention program that emphasized structured teaching such as DTT.

Other Structured Intervention Methods

Other structured intervention methods in ABA have a more flexible format than DTT but still involve having the interventionist set the agenda, choose the skills to be taught, and provide direct instruction to the individual with ASD. One extensively studied set of approaches is called peer-mediated social skills training (Strain & Schwartz, 2001). These approaches involve coaching typically developing peers on how to engage individuals with ASD in social interactions and then having the peers and individuals with ASD play or work together in pairs or small groups. Research indicates that peer-mediated social skills training can significantly increase the rate of social interaction (McConnell, 2002) and also can be used to promote learning of academic skills (Kamps et al., 1999). Another set of approaches involves teaching individuals with ASD to follow a script, then fading out the script and systematically cuing individuals to use the script in appropriate contexts. A script might consist of a series of related conversational statements that the individual with ASD can make when talking with another person about a topic, a sequence of role-playing or make-believe activities, or a succession of actions involved in completing a self-help skill or activity of daily living. There are a variety of formats for presenting scripts. In video modeling, two or more models act out the script, and it is recorded for repeated viewing by the individual with ASD. A meta-analysis of single-case studies indicated that video modeling qualifies as an evidence-based intervention for enhancing skills in the areas of social communication, self-help, and on-task behavior during in-structional activities (Bellini & Akullian, 2007). Alternatively, modeling can be provided in vivo, and some research indicates that this approach also can be effective in promoting skill acquisition (e.g., Coe et al., 1990). Additional formats for presenting scripts include pictorial schedules, in which each picture corresponds to a part of the script (McClannahan & Krantz, 1998), or simply written words or picture symbols (McClannahan & Krantz, 2005). A number of single-case studies support the use of pictorial schedules or written scripts to promote social communication and independent completion of activities of daily living (McClannahan & Krantz, 2005).

Interventions to Reduce Challenging Behaviors

Behavior analysts hypothesize that in most instances, challenging behavior is maintained (often inadvertently) by reinforcement from environmental or physiological events such as attention from others, opportunities to obtain preferred activities, or pain relief (Iwata et al., 2002). The environmental and physiological factors that are associated with challenging behavior are evaluated using a process called functional assessment, functional behavioral assessment, or functional analysis. This evaluation assists in designing interventions. For example, if an individual engages in challenging behavior to gain attention, a target for intervention might be to teach the individual to recruit attention through a simple request and ignore the problem behavior when it occurs. If, however, the challenging behavior serves to avoid an activity, the intervention might involve either skipping the activity or teaching the individual to request a break.

The quickest approach to conducting a functional assessment is simply to administer checklists such as the Motivation Assessment Scale (Durand & Crimmins, 1988) or the Questions About Behavioral Function (Matson & Vollmer, 1995) to ask caregivers why they believe that an individual engages in challenging behavior. Interviews such as the Functional Assessment Interview (O’Neill et al., 1997) can provide more extensive information. Another option is to observe the individual directly in his or her everyday environment. Finally, experimental or analog functional analysis can be conducted. This approach involves systematically introducing and withdrawing the antecedents and consequences for problem behavior in a clinical, home, or school setting (Iwata et al., 1994), as illustrated in the study by Ahearn et al. (2007) described in the section on Research Methods.

The choice of prevention or intervention procedure depends on the function or functions the behavior serves for the individual. Common prevention strategies include practicing activities beforehand (priming or preteaching) or presenting visual schedules to help individuals with ASD anticipate upcoming events (Koegel, Koegel, & Frea, 2003; McClannahan & Krantz, 1998). Another approach is to use differential reinforcement, which involves reinforcing adaptive replacement behaviors for the challenging behavior. For example, in differential reinforcement for alternative behavior (DRA), an individual with ASD might be reinforced for saying, “I need help,” but ignored for flopping down to the floor. In differential reinforcement of incompatible behavior, behavior that is topographically incompatible with the target behavior is reinforced. For example, to reduce the frequency with which an individual with ASD gets up and leaves a teaching situation, in-seat behavior would be reinforced. Based on a systematic review of single-case studies, Odom et al. (2003) identified differential reinforcement as an evidence-based strategy for young children with ASD.

Strategies for responding to a challenging behavior and reducing the likelihood that it will recur include extinction (withholding reinforcement for previously reinforced behavior), time-out (placing an individual in a situation in which reinforcement is unavailable), and response cost (taking away preferred objects or activities). Another reductive procedure, overcorrection, consists of restitution (restoring the environment to a better state than it was in before the challenging behavior occurred) and positive practice. For example, if an individual with ASD throws a plate of food on the floor, she may be required not only to pick up the food but also to clean the surrounding areas and to practice throwing out food in the garbage. Until the mid-1980s, contingent aversives such as low doses of electric shock were sometimes used for severe challenging behavior such as self-injury that was causing significant tissue damage. Although research indicates that aversives often decrease challenging behavior rapidly (Matson & Taras, 1989), they are no longer implemented in the large majority of ABA programs because of ethical concerns, the potential for misuse, and the availability of non-aversive strategies (National Research Council, 2001). Behavior analysts currently recommend that if any reductive procedure is used, it should be based on a functional assessment and implemented as part of a multicomponent treatment plan that includes methods for preventing the occurrence of challenging behavior and increasing alternative, appropriate behaviors (Autism Special Interest Group, 2004). When implemented with these safeguards, single-case studies indicate that reductive procedures based on a functional assessment are often effective in decreasing challenging behavior, although additional studies are needed to examine the extent to which these improvements are maintained over time (Horner et al., 2002).

Applications of Applied Behavior Analysis to Teach Specific Skills to Individuals with Autism Spectrum Disorders

Social, Play, and Leisure Skills

Instruction on imitation is a standard feature of ABA and other intervention programs for toddlers and preschoolers with ASD (Dawson & Osterling, 1997; Rogers, 1998). The ability to imitate a verbal or physical action is an important prerequisite for learning more complex skills and is itself an important part of social interactions. ABA interventions to teach imitation usually involve one-to-one instruction in a DTT format. Instruction begins with a focus on imitation of simple gross motor actions (e.g., clapping hands) or actions with objects (e.g., putting a block in a bucket) and gradually progresses to more subtle actions (e.g., speech sounds) and chains of actions (e.g., sequences of motor movements). This approach can result in generalized imitation to new models (Young et al., 1994).

After an individual with ASD has acquired imitation skills, in vivo or video modeling can be used to teach a variety of social and play skills such as conversing with others, playing creatively, and taking turns during games (Bellini & Akullian, 2007). Peer-mediated social skills training also can boost such skills (Strain & Schwartz, 2001). Peers who are the same age as or slightly younger than the individual with ASD may be more effective than older peers (Lord & Hopkins, 1986).

Although these strategies produce immediate gains in social skills, generalizing these gains to new situations and maintaining them over time pose a challenge (Stahmer, Ingersoll, & Carter, 2003). Possible ways to improve generalization and maintenance include teaching individuals with ASD to self-monitor their interactions with others (Koegel et al., 1992), involving an entire class in implementing interventions (Kamps et al., 1994), providing scripts or cues of social interactions that the individual can use across a variety of peers or situations (Krantz & McClannahan, 1993) or systematically expanding on social initiations that some individuals with ASD spontaneously direct toward peers (Kennedy & Shukla, 1995).

Most of these interventions were developed for preschool and school-age children with ASD. Given that social demands change across the lifespan, it is unclear how effective the interventions are for adolescents and adults with ASD. Also, because the focus has been on specific target behaviors, the extent to which they produce more global improvements in core features of ASD and lead to improved quality of life (e.g., meaningful friendships with peers) requires further investigation.

Another important subpopulation that has received relatively little scientific study is children with high-functioning autism or Asperger’s Syndrome. Peer tutoring may be beneficial (Kamps et al., 1992; Thiemann & Goldstein, 2004). Preliminary evidence suggests that self-monitoring and contingency contracting also may be successful (Mruzek, Cohen, & Smith, 2007). Behavioral social skills training in a clinic is another potentially beneficial intervention (Barry et al., 2003), but results thus far have generally been disappointing (Bellini et al., 2007). A possible way to increase efficacy is to provide intervention within the context of a classroom throughout the school day (Lopata et al., 2006).

Communication

DTT is often used to establish communication skills in nonverbal individuals with ASD (Lovaas, 2003). Instruction usually begins with a focus on receptive language, particularly following simple requests such as “sit down” or “come here” and identifying familiar objects or people. Once an individual has established imitation skills, he or she may be taught to imitate saying individual words and then to use basic expressive communication such as saying a word to label an object.

For individuals with ASD who have limited or no expressive vocal language, ABA interventions may focus on augmentative and alternative communication systems. In the 1980s, most research focused on sign language and indicated that many individuals with ASD were successful in learning to sign despite making slow progress in acquiring vocal communication (Carr & Dores, 1981). In the 1990s, the focus shifted to systems in which individuals selected pictures to indicate what they wanted—notably, the Picture Exchange Communication System (Bondy & Frost, 2001). Research indicates that this too can be an effective strategy for establishing communication (Howlin et al., 2007; Yoder & Stone, 2006).

Enhancing an individual’s communication skills concurrently may decrease problem behavior. Functional Communication Training is an approach in which instructors teach or reinforce a functionally equivalent communicative response that can replace problem behavior (Carr & Durand, 1985). For example, an individual with ASD may learn to make a verbal request for a preferred object or activity instead of displaying aggression and may then begin to apply this new skill across settings (Durand & Carr, 1992).

Although ABA interventions have been developed to teach social communication skills such as conversing with others, repairing breakdowns in communication, and inferring implied meanings (e.g., Taylor & MacDonough, 2001), there is little research on the efficacy of such interventions. Also, as is true of interventions on social and play skills, the research that is available on interventions for social communication has focused mainly on preschool and school-age children with ASD and developmental delays. Consequently, research on adolescents and adults with ASD, as well as on individuals with high-functioning autism or Asperger’s Syndrome, is a priority.

Repetitive Behaviors, Circumscribed Interests, and Other Problem Behavior

Functional assessments of stereotypic or repetitive behavior indicate that many individuals with ASD display such behavior at high rates regardless of environmental factors (Fisher et al., 1998). In some cases, however, the behavior may increase in response to specific events such as presentation of demands (Durand & Carr, 1987) or entry into an unfamiliar situation (Runco, Charlop, & Schreibman, 1986). Only a few studies have tested ABA interventions for reducing repetitive behavior. Simply increasing the availability of competing activities such as toys is one potentially effective strategy (Eason, White, & Newsom, 1982). Another approach is to interrupt the behavior and immediately redirect the individual to another activity (Ahearn et al., 2007). However, additional research is needed to confirm the utility of these interventions and test whether improvements are maintained over time. Unfortunately, even less information is available on ABA interventions for higher-order repetitive behavior such as an insistence on following routines or an intense preoccupation with a particular topic (Bodfish, 2004).

Daily Living, Community, and Vocational Skills

ABA interventions are often implemented to teach daily living skills such as toileting, dressing, brushing teeth, and food preparation (Matson et al., 1996). These interventions usually involve conducting a task analysis and then using chaining procedures to teach each step of an activity. The use of visual schedules, in which steps of an activity are displayed in separate pictures or photographs, appears especially useful (McClanahan & Krantz, 1998). ABA interventions also have been implemented to establish appropriate community behaviors such as crossing the street, but generalization of skills outside of the training context has been inconsistent (Haring et al., 1987). In addition, ABA curricula have been developed to teach academic and vocational skills. These curricula are based on a task analysis of the skills and involve developing the skills in a series of carefully planned, small steps (Engelmann et al., 1988). However, because evaluations of the efficacy of these curricula for individuals with ASD have been sparse, this is an area that merits further research.

Comprehensive Applied Behavior Analysis Programs: EIBI

In addition to conducting studies on focal interventions for specific target behaviors, behavior analysts also have developed comprehensive intervention packages. One comprehensive strategy is EIBI. EIBI is characterized by 20 to 40 hours per week of treatment for 2 years or longer, beginning prior to age 5 years. EIBI involves carefully structured, one-on-one, and small group intervention based on a broad curriculum that emphasizes communication, social skills, cognition, and pre-academics (e.g., colors, shapes, letters, and numbers; Leaf & McEachin, 1999).

There are also comprehensive ABA models for older children and adults with ASD throughout the lifespan (Handleman & Harris, 2006; Holmes, 1997). These programs take place in specialized classrooms, residential living programs, or occupational settings. They differ from EIBI in that they focus less on intensive, individualized, structured teaching and more on fostering participation in group activities and independent completion of tasks (without direct supervision).

Research shows that many individuals with ASD in comprehensive ABA programs successfully learn a variety of new skills (e.g., McClannahan, Macduff, & Krantz, 2002). At present, however, EIBI is the only type of comprehensive ABA program for individuals with ASD to have been tested in studies of long-term outcome. Research on EIBI suggests that ASD may be remarkably malleable in some cases during the first years of life (Rogers & Vismara, 2008).

The UCLA Young Autism Project

In the first study to draw widespread attention to EIBI, Lovaas (1987) and his colleagues at UCLA (McEachin, Smith, & Lovaas, 1993) evaluated an intervention that consisted of an average of 40 hours per week of individualized ABA instruction for 2 years or longer. Children with ASD began intervention when they were 2 or 3 years old. Intervention initially took place in children’s homes and was conducted by teams of undergraduate students under close supervision by Lovaas, his graduate students, and other personnel who had 2 years of experience or more in Lovaas’s intervention model.

During the first year of intervention, DTT was the primary intervention technique. An emphasis was placed on teaching skills considered necessary for subsequent progress, including compliance to elementary directions, imitation of others, and discrimination between instructional stimuli i.e., selecting a correct item from among a field of items, such as matching colors or pointing to objects or pictures called out by the examiner). At the same time, interventions were implemented to reduce behaviors that interfered with learning (e.g., tantrums or aggression) through procedures such as extinction or time-out. More controversially, as a last resort, contingent aversives such as a slap on the thigh were occasionally used.

The second year focused on expressive and receptive language skills, including abstract language concepts (e.g., adjectives and other qualifiers, prepositions, pronouns), as well as generalization of new skills to preschool and other community settings. The third year emphasized pre-academics such as early reading and writing skills, observational learning (learning by watching other children learn), and peer interaction. Also, children spent increasing amounts of time in preschool or kindergarten. DTT was gradually reduced and replaced with more naturalistic instructional approaches.

Lovaas (1987) compared a group of 19 children with ASD who received this EIBI intervention to two control groups: a group of 19 children with ASD who received less intensive ABA based on the same intervention manual (Lovaas, 1981) and a group of 21 children with ASD who received services in the community. Assignment to groups was based on therapist availability. If sufficient therapists were available at intake to provide EIBI, a subject entered the EIBI group; otherwise, the subject entered the less intensive ABA group. Although the groups had similar IQs at intake, the EIBI group had a mean IQ of 83 at age 7 years, much higher than the mean IQ of 52 in the low-intensity intervention group and 57 in the community-intervention group that received community intervention. Nine children from the EIBI group (47%) achieved average intellectual functioning (IQ >85) and unsupported placements in general education classrooms. Lovaas (1987) concluded that these 9 children could be described as “normal functioning” and possibly even “recovered.” A follow-up evaluation took place when children averaged age 13 years (McEachin et al., 1993). This evaluation indicated that the EIBI group maintained its gains and also outperformed the low-intensity group on measures of adaptive behavior and psychopathology. (The community-intervention group was unavailable for follow-up.)

Some investigators hailed these findings as a breakthrough and identified a number of strengths in the study, including groups that appeared well-matched on most intake variables, use of an intervention manual, and outcome evaluations conducted by blind examiners (Baer, 1993). However, others pointed out many possible flaws, notably nonrandom assignment to groups, use of different IQ measures at intake and follow-up, failure to measure some potentially important outcomes such as changes in behaviors associated with ASD, and impracticality of implementing aspects of the intervention in community settings (e.g., 40 hours of intervention per week and occasional use of contingent aversives) (Gresham & MacMillan, 1997; Schopler, Short, & Mesibov, 1989). Lovaas and colleagues disputed these critiques but concurred that replications with improved methodological design were required (Lovaas, Smith, & McEachin, 1989; Smith & Lovaas, 1997; Smith, Lovaas, & McEachin, 1993).

Subsequent Early Intensive Behavioral Intervention Studies

Following the initial report by Lovaas and colleagues, a number of other studies on EIBI began to appear. At this writing, the literature totals 21 studies of ABA intervention in which toddlers or preschoolers received 15 hours or more of instruction per week, and outcomes were assessed on standardized tests. Table 58-1 lists these studies. Two studies were RCTs and are summarized in the first two rows of the table. Next, the table lists 10 quasi-experimental studies. In these studies, procedures other than random assignment were used (e.g., basing assignment on therapist availability or family preference). However, the EIBI group was matched to control groups on subject characteristics such as age and IQ. Finally, the table includes one study with a multiple baseline design and eight studies in which pre- and post-intervention scores were compared but that had no experimental controls.

Table 58–1. Peer-refereed studies on early intensive behavioral intervention for children with autism

M Intake

M Adaptive

EIBI

Age

M intake

M Tx

M

Behavior

General Ed

Study

N

N

(months)

IQ

Design

Control

Tx Site

Hrs/week

Follow-up

IQ change

Change

Placement

Sallows & Graupner, 2005*

23

23

33

51

RCT

Parent-directed EIBI

Home

36

Age 7–8 years

+23

+9

11 of 23

Smith et al., 2000b*

28

15

36

51

RCT

Parent training

Home & School

25

4 years tx

+16

–2

4 of 15

Cohen et al., 2006*

42

21

31

62

Quasi Exp

Community Tx

School

35-40

3 years tx

+25

+20

6 of 21

Eikeseth et al., 2002; 2007*

25

13

63

63

Quasi Exp

Community Tx

of equal intensity

School

18

Age 8 years

+25

+12

0 of 13

Howard et al., 2005

61

29

31

59

Quasi Exp

Center

35-40

14 months tx

+30

+11

Magiati et al., 2007

44

28

38

83

Quasi Exp

Home

33

2 years tx

-5

–2

23 of 28

Reed et al., 2007a*

27

14

43

57

Quasi Exp

Low intensity ABA

Home

30

10 months tx

+15

+2

Reed et al. 2007b

48

12

40

56

Quasi Exp

Community Tx

Home

9 months tx

+13

+3

Remington et al., 2007

44

23

36

61

Quasi Exp

Community Tx

Home

20-30

2 years tx

+12

**

Sheinkopf & Siegel, 1998

22

11

34

62

Quasi Exp

Community Tx

Home

20

20 months tx

+27

5 of 11

Smith et al., 1997*

21

11

37

28

Quasi Exp

Low-intensity ABA

Home

30

Age 5–20 years

+7

0 of 11

Zachor et al., 2007

39

20

29

76

Quasi Exp

Community Tx

Center

35

1 year tx

+2

Smith et al., 2000a*

6

6

36

50

Mult. Baseline

Home & Schonol

26

2-3 years tx

+4n

+5

5 of 6

Anderson et al., 1987*

14

14

43

58

Pre-Post

Center

15-25

2 years tx***

+14

10 months

0 of 14

Bibby et al., 2001

75

75

43

51

Pre-Post

Home

30

+1

+10

Birnbrauer & Leach, 1993

9

9

39

51

Pre-Post

Home & School

19

2 years tx

+14

+8

Harris et al., 1991

7

7

50

59

Pre-Post

Center

<30

1 year tx

+19

Handleman et al., 1991

6

6

40

47

Pre-Post

Center

<30

10 months tx

+11

Harris & Handleman, 2000

27

27

40

68

Pre-Post

Center

<30

4-6 years post-tx

+18

11 of 27

Perry et al., 2008

322

322

54

47

Pre-Post

Home & Center

20-40

18 months tx

+12

+1

Weiss, 1999

20

20

42

Pre-Post

Home

40

2 years tx

+34

15 of 20

* Study based on UCLA treatment manual, ** Raw scores reported, ***Year 1 results analyzed because of missing data at Year 2

Note. RCT = randomized clinical trial. Quasi Exp = Quasi-experimental design. Mult. Baseline - Multiple baseline design. Pre-Post = Comparison of pre- and post-intervention scores. Tx = treatment

In eight studies, including both RCTs and three quasi-experiments, intervention was described as adhering to the manual developed for Lovaas’s UCLA Young Autism Project (Lovaas, 1981, 2003). These studies are identified by an asterisk in the table. All of the studies on the UCLA model differed from Lovaas’s (1987) investigation in that contingent aversives were not used. With two exceptions (Cohen, Amerine-Dickens, & Smith, 2005; Sallows & Graupner, 2005), the studies also differed in that children received fewer intervention hours per week. The most common outcome measures, presented in the three rows at the right of the table, were IQ (assessed with a variety of measures), adaptive behavior (usually tested with the Vineland Adaptive Behavior Scales; Sparrow, Balla, & Cicchetti, 1984), and unassisted placement in general education classes (ascertained from school records).

One RCT (Sallows & Graupner, 2005) compared EIBI directed by clinic personnel to EIBI directed by parents. (State funding was available for parents to hire and supervise therapists.) There were few differences between the clinic-directed and parent-directed groups, but both made gains from pre- to post-intervention that were comparable to those in the study by Lovaas (1987). For example, 11 of 23 subjects (48%) obtained average IQs and unassisted placement in general education at follow-up, similar to the rate of 47% reported by Lovaas (1987).

The other RCT (Smith et al., 2000a) compared EIBI to in-home parent training on ABA techniques. At follow-up, the EIBI group obtained an average IQ score that was 16 points higher than the average in the control group. The EIBI group also had a higher rate of unassisted placement in general education (4 of 15 children, compared to 0 of 13 in the control group). These differences were statistically significant but were only about half the size of the effects reported by Lovaas (1987). The EIBI group also obtained higher scores than the control group on measures of nonverbal skills and academic achievement, although the groups did not differ significantly on measures of adaptive behavior, language, or level of behavior problems. Thus, the EIBI group made substantial gains relative to the control group on some measures, but the gains were more modest and circumscribed than in the Lovaas study (1987).

The three quasi-experiments on the UCLA Model (Cohen, Amerine-Dickens, & Smith, 2006; Eikeseth et al., 2002, 2007; Smith et al., 1997) yielded positive results on measures of IQ. Cohen et al. (2006) and Eikeseth et al. (2007) also reported gains in adaptive behavior, but this variable was not assessed in the study by Smith et al. (2007). In addition, Cohen et al. (2006) also found that children in the EIBI group were more likely than control children to have unassisted placements in general education, although Eikeseth et al. (2007) and Smith et al. (1997) did not obtain this result. These studies are noteworthy because they extended the UCLA Model in various respects: Cohen et al. (2006) provided intervention in a community agency rather than a university setting. Smith et al. (1997) focused on lower functioning children with ASD and severe developmental delay. Although children remained quite delayed following intervention, they made gains on two variables (IQ and acquisition of communicative speech). Eikeseth et al. (2007) studied children who were older than those in Lovaas’s (1987) study (age 4–7 years at intake), implemented intervention at school instead of in the home, and included a comparison group that received the same number of intervention hours as the EIBI group. Results were comparable to those obtained with younger children. The three remaining studies on the UCLA Model also yielded positive results (Anderson et al., 2007; Birnbrauer & Leach, 1993; Smith, Buch, & Gamby, 2000a), although Smith et al. (2000a) found more evidence of progress during the first few months of treatment than at a follow-up 2 to 3 years later.

Considering all eight studies on the UCLA Model, some investigators have classified the model as an efficacious treatment (Rogers & Vismara, 2008). Meta-analyses by Reichow and Wolery (2009) and Eldevik et al. (2009) also support this conclusion. However, another meta-analysis (Boyd & Spreckley, 2009) found that the evidence remains insufficient to support clear conclusions, and writers such as Howlin, Magiati, and Charman (2009) have identified many methodological limitations. For example, both RCTs had small numbers of participants. The control group in the Sallows and Graupner (2005) study received nearly the same intervention as the EIBI group. Concerns also have been raised about the procedures for monitoring fidelity to the intervention protocols, and the focus on developmental tests such as IQ (e.g., Kasari, 2002). Potentially important outcomes such as reductions in behaviors associated with ASD and the impact of intervention on the family have received relatively little attention. For such reasons, some investigators have classified the UCLA Model as only possibly efficacious (Faja & Dawson, 2006).

Some other models have support from studies without a control group (e.g., Harris & Handleman, 2000; Perry et al., 2008) or studies with quasi-random assignment (Howard et al., 2005; Reed, Osborne, & Corness, 2007a, b; Remington et al., 2007) but not studies with random assignment. As such, they have been regarded as promising but not yet established as efficacious or possibly efficacious (Rogers & Vismara, 2008). However, it should be noted that there are also studies that have failed to show benefits from EIBI (Bibby et al., 2002; Magiati, Charman, & Howlin, 2007). A possible reason is that these studies did not include procedures for assuring high-quality intervention (e.g., regular supervision of therapists), but in any event, they reveal that EIBI is not always effective.

Given that most EIBI studies have yielded positive outcomes, perhaps the next question is whether they have confirmed Lovaas’s (1987) assertion that some children with autism achieve “normal functioning” after EIBI. None of the EIBI studies published before 2000 identified any such children. In contrast, more recent studies have indicated that a substantial minority of children (ranging from 27% to 48%) do perform in the average range in post-treatment assessments (Cohen et al., 2006; Howard et al., 2005; Sallows & Graupner, 2005; Smith et al., 2000b). However, Cohen et al. (2006) pointed out that they did not have enough data to describe the children in their study as normal-functioning. For example, they did not have information on whether children showed reductions in characteristics of autism.

Overall, despite some conflicting findings, EIBI—especially the UCLA Model—has substantial scientific support. Initial assertions that some children could be described as normal-functioning following intervention have not been replicated, but nearly all reports have described significant gains in IQ and other measures. These results provide reason for optimism. Nevertheless, it would be premature to conclude that its efficacy has been definitively proven. Additional research, especially large studies with random assignment to groups, remains a high priority (Lord et al., 2005).

Areas for Future Research on Early Intensive Behavioral Intervention

EIBI studies have incorporated a relatively narrow range of outcome measures, focusing mainly on IQ and other measures of children’s level of functioning. Only three studies in Table 58-1 included tests of whether characteristics of autism were alleviated in EIBI. Remington et al. (2007) found an increase in joint attention following EIBI. Weiss (1999) and Zachor et al. (2007) reported a reduction in autism characteristics, but Sheinkopf and Siegel (1998) did not. Smith, McEachin, and Lovaas (1993) argued that tests such as the Vineland Adaptive Behavior Scales (Sparrow et al., 1984) could serve as proxy measures of autism characteristics. However, it is now known that many children with ASD perform well on such tests yet still display autism characteristics that interfere with their functioning (Klin, Volkmar, & Sparrow, 2000). Thus, more detailed assessments of autism characteristics will be necessary (Lord et al., 2005).

Little is known about “active ingredients” in EIBI, such as the choice of intervention procedures, dose or intensity of treatment, and content of the curriculum (Kasari, 2002). For example, regarding intervention procedures, two studies indicated that EIBI was more effective than community treatment of equal intensity (Eikeseth et al., 2002, 2007; Howard et al., 2005). These findings may indicate that the use of ABA procedures is an important component of intervention. However, in a third study, outcomes did not differ significantly between the EIBI group and the community treatment group (Magiati et al., 2007). Another issue pertaining to intervention method is that all EIBI studies in Table 58-1 emphasized DTT. No studies have been conducted comparing DTT-based EIBI to ABA approaches that rely more on incidental teaching (described in the next chapter) or to developmental models (Chapter 60).

Findings on intensity of intervention are similarly limited and inconsistent. The studies with the most number of intervention hours per week (Cohen et al., 2006; Sallows & Graupner, 2005) have yielded the most favorable outcomes, but a study in which children received nearly as many hours (Magiati et al., 2007) produced null findings. Apart from a small study by Reed et al. (2007a), direct comparisons of different levels of intervention intensity have not been conducted. Comparisons of interventions with different curriculum content also have not been performed.

Even in studies in which children with ASD showed large improvements following EIBI, there have been major individual differences in outcome. For example, the nine children who achieved the best outcomes in the Lovaas study (1987) made an average of 37 IQ points, but the remaining 10 children showed little change. However, it has been difficult to identify factors that predict differential response to interventions. For example, some studies suggest that intake IQ is positively correlated with outcome (e.g., Handleman & Harris, 2000; Sallows & Graupner, 2005), but other studies have not obtained evidence for such an association (Cohen et al., 2006; Smith et al., 2000b). Because EIBI requires considerable effort and resources, identifying factors that are associated with favorable outcomes has considerable practical importance.

Smith et al. (2007) recommended that following carefully designed RCTs to test efficacy and identify active ingredients, investigators should proceed to studies of effectiveness in community settings. This will be necessary for EIBI, which has already become widely available from community providers in many regions. For example, the Ontario Intensive Behavioral Intervention program was set up to provide services to children with ASD in the entire province of Ontario, Canada. A review of data on 322 children with ASD in this program indicated that children made gains on standardized tests and other measures from pretreatment to follow-up (Perry et al., 2008). Still, additional evaluations of such ambitious programs will be necessary to determine whether behavior analysts can “go to scale” and implement EIBI for much larger numbers of children than they have in the past.

Conclusion

ABA has become the most extensively studied psycho-educational intervention for individuals with ASD. On a practical level, ABA research has generated a number of potentially useful intervention techniques and comprehensive intervention packages—notably, EIBI—that may greatly enhance the functioning of individuals with ASD. On a theoretical level, ABA research has led to broad (although not universal) acceptance of single-case experiments as an appropriate strategy for evaluating interventions, increased understanding of the learning style of individuals with ASD, and suggested that ASD may be malleable if intervention begins early.

Challenges and Future Directions

  • Extending ABA research to older and higher-functioning individuals with ASD: Almost all ABA intervention studies have focused on individuals with ASD who are young, developmentally delayed, or both. Obviously, these individuals are deserving of attention. However, older and higher-functioning individuals with ASD have been somewhat neglected, and increased efforts to develop and test ABA interventions for such individuals are warranted.

  • Disseminating ABA teaching techniques: Some ABA intervention techniques have been refined over the course of many single-case studies but never presented in a format such as a published manual that would be accessible to non-specialists. Examples include peer-mediated social skills training and video modeling. These interventions also have not been tested in RCTs that would provide information on which individuals with ASD benefit most from them and what the long-term outcomes are. As a result, the interventions may be underutilized.

  • Addressing core features of ASD: Along with the focus in individuals with ASD who have developmental delays, behavior analysts have emphasized accelerating overall rates of learning. In EIBI studies, the primary outcome measures have been cognitive tests such as IQ. Certainly, speeding up skill acquisition in individuals who have delays is a reasonable goal. However, alleviating difficulties that are core features of ASD (e.g., reciprocal interactions with others and social communication) is also crucial. A more systematic effort to create and test interventions for such difficulties is vital, and collaborations between behavior analysts and experts on the ASD phenotype could facilitate this effort.

  • Conducting larger, more rigorous outcome studies: ABA research has involved either single-case experiments with small numbers of subjects or studies of EIBI at a single site. This state of affairs has allowed behavior analysts to work separately from one another and from other researchers. However, definitive tests of EIBI will require a concerted effort on the part of behavior analysts, probably in collaboration with investigators who have expertise in multisite RCTs and statisticians who can perform sophisticated analyses (e.g., to identify “active ingredients”).

Suggested Readings

Cooper, J. O., Heron, T. E., & Heward, W. L. (2007). Applied behavior analysis (2nd ed.). Upper Saddle Hill, NJ: Prentice-Hall.

National Autism Center (2009). National Standards Report. Retrieved September 24, 2009, from http://www.nationalautismcenter.org/pdf/NAC%20Standards%20Report.pdf.

Sturmey, P., & Fitzer, A. (Eds.). Autism spectrum disorders: Applied behavior analysis, evidence, and practice. Austin, TX: Pro-Ed.

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