Recent Article
Summaries
Welterlin, A. & LaRue, B. (2007). Serving the needs of immigrant families of children with autism. Disability and Society, 2 (7), 747-760.
Todd, T., & Reid, G. (2006). Increasing physical activity in
individuals with autism.
Focus on Autism and
Other Developmental Disabilities, 21(3),
167-176.
Carr, J. E. & Firth, A. M. (2005). The verbal behavior
approach to early and intensive
Welterlin, A. & LaRue, R., (2007). Serving the needs of immigrant families of children with autism. Disability and Society, 2 (7), 747-760.
Reviewer and
primary author: Aurelie Welterlin,
Psy.M.
The article
addresses the topic of increasing awareness of how immigrant families in the
The authors
begin by noting the rapid increase of immigrants in the
The first
consideration presented by the authors is how disability is defined and
interpreted across cultures. The authors
suggest that families who immigrate to the
The second
consideration presented by the authors is how impressions of normalization and
intervention may differ across cultures.
Whereas the dominant culture in the United States is based on a certain
set of beliefs and values that define the mainstream idea of a normal, good
quality of life (e.g. independence, self reliance, personal choice, etc.),
immigrant families may not share the same normalization principles as American
parents and professionals, and may not, as a result want the same intervention
goals. One example provided is the goal
of teaching sustained eye contact, which may be rejected by Asian-immigrant
parents who regard their children as disrespecting them if eye contact is established
(Shu-Minutoil, 1995).
The authors note that little research exists that examines the
assumptions and expectations of immigrant families on competency and skill
development of their disabled children, however, they do provide some of the
beginning evidence. Approaches to
treatment may also vary across cultures; state the authors, due to beliefs
about etiology. Some immigrant families
with established beliefs from their home country may rely on family members,
elders, and spiritual and folk healers for information and treatment. The authors end their discussion providing a
description of some of the practical barriers to receiving health care services
faced by immigrants, which are primarily based on lack of knowledge, financial
recourses, and ability to communicate.
The authors end their paper with a discussion of recommendations for both service providers and immigrant families concerning how to negotiate differences. For service providers, they suggest incorporating the components of a family's social and cultural environment to create a "best fit" intervention, which will lead to increased efficacy and compliance to an intervention. They suggest having frank discussions about views of diagnosis, etiology, and treatment with immigrant families and also provide suggestions of how practitioners can become culturally sensitive and competent. For immigrant families, the authors recommend taking an active role in developing and implementing interventions, educating themselves about assessment and intervention processes, and in teaching service providers about family and cultural norms, values, preferences, expectation, concerns, and priorities. They also provide Brookman-Frazee's (2004) criteria to help families become evaluative of practitioners, while normalizing the fact that providers may be sincere but merely uninformed.
References
Brookman-Frazee, L. (2004) Using parent/clinician
partnerships in parent education programs for children with autism. Journal of
Positive Behavioral Intervention, 4,
195-213.
Gallimore, R., Coots, J., Weisner,
T., Garnier, H., & Gunthrie,
D. (1996). Family responses to children with early developmental delays: II.
Accommodation intensity and activity in early and middle childhood. American
Journal on Mental Retardation, 101, 215-232.
Heller, T., Markwardt
R., & Rowitz L. (1994) Adaptation of Hispanic
Families to a Member with Mental Retardation. American Journal of Mental
Retardation, 99 (3), 289-300.
Moes, D. & Frea,
W. (2000) Using family context to inform intervention planning for the treatment
of a child with autism. Journal of Positive Behavioral Interventions, 2, 40-46.
Shu-Minutoli, K. (1995) Family Support: Diversity,
disability, and delivery. Yearbook in Early Childhood Education, 6, 125-140.
Aurelie
Welterlin is a graduate student in clinical
psychology at The
Todd, T., & Reid, G., (2006).
Increasing physical activity in individuals with autism.
Focus on Autism and
Other Developmental Disabilities, 21(3), 167-176.
Reviewed by:
Megan Atthowe, RN, BCABA
The benefits
of sustained physical activity to human health and fitness are
well-established, and initial research with individuals with autism suggests
that it may have the additional capacity to enhance desirable behaviors and to
reduce problematic ones. Unfortunately,
however, individuals with autism face a number of barriers to engaging in
physical activities, both by virtue of the characteristics of the disorder and
the dearth of research-based guidelines on how to intervene effectively. Self-monitoring (inclusive of
self-observation and self-recording) is one technique used to increase behavior
while limiting the extent of external feedback delivered. This technology is easy to replicate and is
conducive to use in a variety of settings.
Evidence from research on self-monitoring in both typically-developing
and mildly-disabled populations suggests that it can be an effective
intervention for increasing physical activity.
The purpose of the present study, then, is to extend this research to
individuals with autism by examining the effects of an intervention package
(self-monitoring, edible reinforcement, and verbal cuing) on participants'
physical activity during 30-minute exercise sessions.
Three
nonverbal, ambulatory young men with autism, ages 15-20 years, participated in
this study. All three participants
attended a Canadian school for people with developmental disabilities, had been
exposed to structured teaching, and had not used self-monitoring systems
previously. The investigators selected
two outdoor physical activities for intervention: snowshoeing (a total of nine
sessions during snowy months) and walking/jogging (23 sessions during spring
and early summer). Because these activities
are normative in
Sessions
occurred twice per week and lasted one hour (15 minutes each of preparation and
clean-up and 30 minutes of physical activity).
The activities were conducted on a soccer field; during inclement
weather, sessions were either cancelled or moved indoors (walking/jogging
only). Participants followed a 57m x 50
m, diamond-shaped course, demarcated by a bench in one corner of the diamond
and a flag in each of the other three corners.
The bench served as the starting and ending points of each lap and held
the participants' self-monitoring boards.
The
investigators used a changing conditions design to examine the effects of a
three-component intervention on participants' snowshoeing and walking/jogging
behaviors. Three conditions were
included: baseline (A); self-monitoring, edible reinforcement, and verbal cuing
(B); and self-monitoring and verbal cuing only (C). Data were collected on the number of laps
each participant completed, measured by the number of markers on the
self-monitoring board at the end of each session. Participants snow shoed during all four
sessions in condition A and during the first five sessions in condition B. Walking/jogging began during condition B (session
10) and continued through the end of the study.
The
self-monitoring component of the intervention consisted of a board with three
columns, each of which was labeled with a participant's name in an assigned
color. During conditions B and C, each
time a participant completed a lap, he placed a color-coded happy face marker
in the column under his name. The
investigators taught participants how to place the markers on the
self-monitoring board using hand-over-hand guidance during the first three sessions
of condition B. After the third session,
prompting was withdrawn unless the participants were unable to complete the act
independently. The investigator or a
staff person remained with the self-monitoring board throughout the study and
gave each participant a happy face marker to put on the board each time he
completed a lap.
The edible
reinforcement component of the intervention was incorporated to be consistent
with the participants' school program. During
condition A (baseline), no edibles were delivered. During condition B, edibles were given
initially at each corner of the diamond course (for a total of four edibles per
lap). Delivery of edibles was then
systematically faded by delivering one less edible per lap every four sessions
until participants received only one edible per lap (paired with delivery of
the happy face marker). During condition
C (the last four sessions of the study), no edible reinforcers were used.
The verbal
cuing component of the intervention consisted of verbal encouragement and
verbal directives, neither of which was manipulated systematically. Verbal encouragement included praise for
exercising or completing laps and statements intended to cue participants to
increase their pace if they slowed or stopped.
Verbal directives included instructions about following and staying on
the course. The number of verbal cues
delivered in a session was recorded every three sessions via a microphone.
The average
number of laps completed per session increased for all three participants over
the course of the study. By the end of
the nine snowshoeing sessions, all participants had increased their average
distance by 0.2 km. By the end of the
walking/jogging sessions, the three participants increased their average
distance by 1.26 km, 1.14 km, and 0.83 km, respectively. Distances increased despite the systematic
decrease in edible reinforcement. An
increase in the participants' independence was inferred from the decrease in
verbal cues provided over time.
Temporary increases in verbal cues were noted on the three days that the
course was moved to another outdoor area and on the day that jogging was
introduced.
While the
results of this study are promising and suggest that physical activity can be
increased and maintained with self-monitoring, the characteristics of the
changing conditions design limit the conclusions that can be drawn. First, we cannot know what component(s) of
the intervention served to reinforce and maintain the target behaviors. While participants' behaviors increased and
persisted despite a decrease in external reinforcement, we cannot conclude that
the self-monitoring (the only part of the intervention that remained constant
in conditions B and C) led to the behavior changes. That is, we do not know whether the
self-monitoring or something else led to changes in the dependent measures. Second, it is difficult to compare conditions
A and C with confidence, as the participants snow shoed during condition A and
walked/jogged during condition C. Thus,
part of the participants' increased distance could be due to a change in the
activity itself. Additional research
incorporating alternate designs, additional measures, and careful data analysis
is needed to clarify the effects of self-monitoring on physical activities.
Despite its
limitations, this study makes a valuable contribution to the small and
much-needed body of literature on physical activity in this population. First, the study demonstrates that it is
possible to increase the physical activity of students with autism and to
sustain the activity with decreasing levels of external feedback. Its findings are encouraging, particularly to
those working in settings where independence is expected and feedback is rare. Second, the target skills were well chosen
and may help the participants engage in behaviors that are more reinforcing to
others. Third, inasmuch as
self-monitoring may increase independence across a variety of settings and
behaviors, the field should continue to explore its use for individuals on the
autism spectrum, including adults. With
only emerging evidence to support its use in this population and in this area,
however, practitioners in applied settings who wish to try this or similar
interventions should take care to do so only when data-based decision making can
be assured.
Megan Atthowe
is a graduate student in the School of Nursing at the University of Virginia
and currently works as a program director at the Virginia Institute of Autism. Her interests include the development of
behavioral programs and community supports for older learners with autism and
underserved populations. Megan currently
holds a BCABA and is in the process of completing the requirements to sit for
the BCBA exam.
Taylor,
B., Hughes, C., Richard, E., Hoch, H., & Coello,
A., (2004). Teaching teenagers with
autism to seek assistance when lost. Journal of Applied Behavior Analysis, 37, 79-82.
Reviewed
by: Jennifer L. Buck, M.Ed., Special Educator,
Over
the past decade, it has become apparent that the safety of our children is of
the utmost importance. While walking
through a local store, we may hear small voices calling out "mommy"
or "daddy" in search of a parent that may have become momentarily
separated from their child. What
happens, however, when a child lacking social and/or communication skills
becomes separated from their parent(s)?
What happens if this young child has autism, and is unable to speak?
This
current study investigated different strategies to teach individuals with
autism how to seek help when lost in the community setting. This study evaluates the efficacy of teaching
individuals with autism to respond to a tactile prompt and seek assistance when
separated from a parent or teacher.
The
participants included three students that met the diagnostic criteria for
autism, and also had deficits in communication and socialization skills. Each of the participants were given a J Tech
vibrating pager and an identification card, which included the student's name,
a statement that he or she was lost, and an emergency contact information. The participants wore the J Tech pager on the
rim of their pocket or waist band during all training sessions.
The
dependent measure in this study was the percentage of correct responses to a
page during each teaching trial. During
each trial, a student was required to approach an adult, gain the attention of
an adult by saying "excuse me," hand their identification card to the
adult, and wait to be reunited with their parent or teacher.
Baseline
data were collected in five different community sites. Teaching sessions took place at two of the
five sites and at school, while the remaining three locations were used as
generalization settings. During baseline
probes, the student was accompanied by a teacher to each setting. The J Tech pager and identification card were
located on the student. An unseen
observer watched over the student as the teacher slipped out of view, and
collected data on whether the student approached an adult when the teacher
disappeared (the pager was not used).
Approximately two minutes after the trial began, it was ended when the
teacher returning to the student.
A
multiple baseline probe design across participants was used to assess the
effects of a tactile prompt in relation to seeking assistance when separated
from an adult. The participants were
first taught how to respond to a page by giving a familiar adult their
identification card. Physical guidance
was used to guide the student to the nearest adult, followed by a verbal prompt
of "excuse me.
The student was then manually guided the student to retrieve the
identification card to give to the adult.
Students were reinforced with praise and edibles for correct responses
and were eventually faded.
Community
teaching at two locations occurred only after the participants were able to
retrieve and give their identification card to a familiar adult. One or two teaching trials were conducted
during each outing. Community teaching
sessions involved all of the same procedural safeguards that were in place
during baseline data collection, with the exception that the teacher activated
the pager when the student became separated from him or her. The participant had 30 seconds to produce
their identification card, if the student was unable to do so, a least to most
prompting hierarchy was implemented.
Generalization
probes at new sites included no tangible reinforcement or error
correction. The student was given 30
seconds to produce their identification card.
If the student was unable to produce the card, the pager signaled again,
followed by praise, once the student was reunited with the teacher. If the student did not respond by retrieving
their identification card, the trial was abandoned and the student was reunited
back with his or her teacher. Parent
probes were conducted in the same manner as the community teaching sessions,
except the parent accompanied the student and activated the pager. The criterion for training at all locations
was 100% correct responses over three consecutive teaching trials.
Each
student that participated in this study was able to produce his or her
identification card in response to a tactile prompt, at school and in each of
the community training locations. More
importantly, these three participants were able to generalize this particular
skill across teachers, familiar adults and their parents and approach both
familiar and unfamiliar people for help.
Future studies should include seeking help from known community helpers,
such as, store personnel, security guards, or a cashier to protect students
from unsafe strangers.
With
the way that technology is ever changing, I see our young children evolving
with this change. Global positioning
systems are becoming more and more sophisticated each year, and may be
potentially useful in helping us locate lost children. Until then, this teaching strategy may help
give children the skills they need to find parents and other adults when lost,
rather than leaving the "finding" up to the adults.
Stromer,
R., Kimball, J.W., Kinney, E.M., Taylor, B.A., (2006) Activity Schedules,
Computer Technology, and Teaching Children with Autism Spectrum Disorders. Focus on
Autism & Other Developmental Disabilities 2(1), 14-24
Reviewed by: Sarah Land
Activity
schedules are commonplace additions to classroom and home settings for
individuals with autism. The more
traditional form of activity schedule is a notebook activity schedule. With technological advances, as well as
further research into video modeling, activity schedules can now utilize
computers. The authors discuss the
research on both types of activity schedules, as well as the benefits and
drawbacks of computer activity schedules.
Additionally, topics for future research are presented.
The authors
compare notebook activity schedules to "to do lists" because they
often serve as functional cues for skills that normally require prompting from
staff. Notebook activity schedules can
also promote independent task initiation and completion, while reducing
undesired behavior during transitions (Schmit, Alper, Raschke, & Ryndak, 2000).
Furthermore, notebook schedules can be used to teach new skills via
schedule- following. MacDuff,
Krantz, and McClannahan (1999)
found students could follow both trained and novel orders of schedules. The students also generalized to other
activities that they were familiar with, but that had not been included in the
original trained schedule.
There is a
large body of support for the benefits of notebook activity schedules. Parents who used the notebook schedules at
home increased engagement and social initiation, and decreased disruptive
behaviors (Krantz, MacDuff,
and McClannahan, 1993). Additionally, notebook schedules may have
more functions than simply that of an environmental modification. Notebook activity schedules can be utilized
to teach interventions for self-management and choice making. Students can be taught to choose the
activities, the order, and even the reinforcer.
Researchers have also combined notebook activity schedules with common
methods of increasing play and social skills.
Krantz and McClannahan
(1998) taught students to utilize photos and text within notebook schedules to
seek adult attention and praise for an activity. When the scripts were faded, the children
initiated scripted and unscripted comments.
They also initiated comments for different activities and solicited
attention from differing conversational partners.
Computers
have also been used to create activity schedules. This can be particularly helpful for children
with autism for a multitude of reasons.
First, using computers for schedules can be worthwhile because students
often are reinforced by computers. In
fact, students frequently prefer computer-based instruction over teacher
instruction (Romancyk, Weiner, Locksin,
& Lekdahl, 1999) and access to computer
activities can even be used as a reinforce (Thorp, 2001).
Second, one
of the additional benefits of computer activity schedules is the ability to
incorporate new technology, such as video modeling, into the schedules. Video modeling consists of the student
viewing a recording of an individual performing the desired skill at a criterion-level
of performance. Video modeling is
especially helpful because it is able to bring a multitude of settings to the
student, is consistent in demonstrations of the appropriate model, and may be
reinforcing for the student to watch.
Using video modeling may also be more effective than using live modeling
(Charlop-Christy et al. 2000). Video modeling has been used to teach skills
in purchasing, communication, play, and self-help.
Third, both
academic and play skills can be learned via computer schedules. Academic skills, such as spelling, math,
money, and number skills can be taught as embedded tasks using video modeling
within computer activity schedules (Vedora,
Bergstrom, Kinney, & Stromer, 2001; Kimmey et al., 2003). Kinney et al. (2003) utilized matrix
training to teach a young girl spelling skills.
After quickly learning the desired target word sets both picture and
dictation cues and learning to write schedules, she generalized both to
spelling untrained words and imitation of novel video displays.
In addition
to teaching academic skills, computer activity schedules have been used to
effectively teach play and commenting skills.
Kalagian, Kinney, Taylor, Stiner,
and Spinnato (2002) taught a 6-year-old girl to
follow a computer schedule including independent play, sociodramatic
play, and play bids. The girl learned to
manipulate and attend to the computer schedule properly, retrieve the materials
and script the dialogue. In addition,
play generalized to both notebook schedules with pictures and with only textual
messages.
A similar
example of using a computer activity schedule to teach play and commenting
skills can be found in Dauphin et al. (2004).
The researchers taught appropriate toy play skills to a 3-year-old boy
in the home setting via a schedule with photos and video models of an
8-year-old boy demonstrating appropriate play and comments. The study used matrix training to teach
generalization. After learning the three
target routines, the child was able to perform 6 untrained activities when
presented with only photos on both his computer and notebook schedule.
Finally,
computer schedules may assist in teaching students to attend to multiple cues
by using various auditory and visual stimuli.
Schedule following is not disturbed by rearranging sequences or presenting
various cues individually. The authors
suggest that students comprehend relations among stimuli and can attend to
stimuli even when they are not required to, evidenced by students who can
perform naming and matching tasks with cues when embedded in the schedule. The authors recommend researching whether
only some of the cues or some component of the schedule have stimulus
control. Also, research on whether having multiple stimuli facilitates learning
categories and classes of stimuli, as well as whether requiring a student to
actively name a stimuli facilates learning functional
verbal skills, is desired (Dauphin et al., 2004; Kalagian
et al., 2002; Kinney et al., 2003; Vedora et al.
2001).
Some issues
do arise with utilizing computers. Notably,
computers are not portable. Because of
this, the authors suggest transferring stimulus control to notebook schedules
quickly and to create a package intervention combining both notebook and
computer activity schedules to gain the unique advantages found in each while
facilitating independence. Also,
computers can be expensive and fragile, so the authors suggest using it for
multiple purposes to make it more cost-effective. In addition, there is a lack of commercially
available products and it can take a great deal of time for staff members to
become acquainted with the software and to produce effective schedules. For that reason, the authors promote teachers
developing skills using PowerPoint or HyperStudio. Finally, because computers are reinforcing to
students, students may not want to leave the computer. Finally, difficulties can arise in
generalizing from on-schedule behavior to off-schedule behavior (Bryan & Gast, 2000).
The authors
present various recommendations for future research. One such area is determining what type of
students would benefit most from the differing types of activity schedules as
well as identifying the critical skills needed and the teaching steps necessary
for students to learn from video modeling.
Research is also needed on how researchers can promote choice making and
engage a child when the schedule is not in use.
Another area of potential research entails understanding how to shift
control to photos or text, as well as from more cues to fewer cues. Finally, more research is needed to determine
whether computer activity schedules can promote skill acquisition faster than
conventional instruction.
In
conclusion, the authors deem activity schedules practical and beneficial tools
for students with autism. The current
evidence is persuasive enough to warrant the additional study of this topic.
Sarah Land
is an undergraduate student at
Hertzroni,
O.E. & Tannous, J., (2004). Effects of a computer-based intervention
program on the communicative functions of children with autism. Journal of Autism and Developmental
Disorders, 34(2), 95-113.
Reviewed by:
Melissa Ortega, M.A.
One of the
hallmark traits of autistic disorder includes impairments in communication. This may vary for individuals as delays in or
lack of communication, impairment in initiating or sustaining conversations, or
repetitive and stereotypic use of language (Wetherby
& Prizant, 2000).
Interventions to enhance communication for people diagnosed with autism
are continuously being developed and the utilization of technology (e.g.,
video, television, and computers) has been an area of interest to further
investigate to help create new approaches for teaching skills such as
functional communication. Historically,
computers have been found to be successful teaching instruments for children
with autism through various facets (Chen & Bernard-Optiz,
1993; Colby, 1973; Higgins & Boone, 1996; Panyan,
1984). Hertzroni
and Tannous developed a software program that is
based on daily life activities and was taught to study participants in a
controlled and structured setting to investigate whether children with autism
could learn specific language skills within this type of environment.
Hertzroni and Tannous
highlighted the difficulties children with autism have with the understanding
of concepts, communicative interactions, and representational thought. These deficits are said to be linked to the
theory of mind (ToM) (Baron-Cohen, 1988; Tager-Flusberg, 1997) which is the ability to use
predictive skills to understand relationships between external states of
affairs and internal states of mind.
Furthermore, ToM is associated with
understanding, organizing, using language appropriately in a functionally
communicative manner. Children with
autism can have impairments in these areas in various degrees of severity, and
can be expressed through immediate echolalic speech
(repetition of words heard immediately or later after being heard) and
irrelevant speech. Hertzroni
and Tannous sought to increase the opportunities to
interact in an environment that modeled language in appropriate settings to
enhance communication and ideally advance the development of language (Mesibov, Schopler, & Hearsey, 1994).
The study
included 5 participants (3 females, 2 males) between the ages of 7.8 and 12.5
years old. The criteria to participate
in the study required the formal diagnosis of autism, functional communication
mainly by immediate or delayed echolalic speech,
irrelevant speech, or intentional communication attempts, normal hearing,
vision, and mobility. The participants
also had access to a classroom computer.
A multiple-baseline design was implemented with computer-based training
with three distinct settings highlighted: playtime, hygienic activities, and
mealtime scenarios.
During
baseline, students were observed during the three natural training settings
(meals, hygiene, and play). Data was
collected on the dependent variables, which included frequency of delayed and
immediate echolalia as well as relevant speech.
Following baseline, the intervention was applied to the first setting
(play). Each student was trained in a
computer room outside of their classroom.
During the intervention, the student viewed scenes of the training
setting on the computer. The program
asked questions in the selected scenarios that would elicit the participant to
choose between items (e.g., toys, food items, or hygienic activities). Once the participant chose an item an
animation of the activity that was chosen would appear. This pattern was repeated throughout the
duration of the session with new activities for the participant to choose from,
each followed by animations. The
sessions were terminated by the participant (either from completing the
activity or because wanted to quit).
There were no verbal interactions that were required, simple neutral
praise was provided intermittently during the training phase on the computer.
During
intervention, observations of the students in the natural environment were
still conducted, coding for echolalia and relevant speech. After six sessions (approx. 10-min each) of
intervention in one setting, intervention was applied to the next simulated
setting. This pattern repeated until the
participant had been exposed to all of the trained settings.
The
intervention results indicate a significant reduction across all participants
was in sentences involving delayed echolalia.
Regardless of setting, all participants had reductions in sentences
spoken with delayed echolalia. The next
significant gain for participants was with relevant speech, especially during
play and mealtime activities. Initiation
of interactions and communication increased for all of the participants. Not all of the trained settings had
significant positive results, however. In
the hygiene setting, the improvements in the use of functional communication
were slight compared to the other two conditions. The authors hypothesized that this was due
the participants' activity preferences.
The most highly preferred activities involved food and toy items, while
hygienic activities were the least preferred for the participants.
The results
from this study support the effectiveness of computer-based functional
communication training in structured settings on daily activities. These results are promising for the future
development of programs to assist in the training of functional communication
in the natural environment. Furthermore,
the findings were significant in the reduction of inappropriate, noncommunicative speech across all settings. It is the authors' hope that computer
programs that enhance communication for children with autism and with different
communication deficits, could foster a greater understanding of the theory of
mind (ToM) and impairments of communicative
functioning.
This article
provides promising results for the future development of technologically
advanced methods for teaching functional communication to children with autism
and language deficits. The greatest
benefit with computer-based training programs is the consistency in training
and exposure the learner has to acquire new skills. Future studies should include computer-based
training programs in community settings and in the home environment.
Melissa Ortega, M.A., is a graduate
student in the
Stahmer,
A., Collins, N., & Palinkas, L., (2005). Early
intervention practices for children with autism: Descriptions from community
providers. Focus on Autism and Other
Developmental Disabilities, 20(2), 66-79.
Reviewed by:
Robert Babcock, Ph.D., BCBA
As the title
suggests, the aim of this study was to gain a better understanding of the early
intervention services provided to children with autism in community settings
using provider reports. This serves as
an initial step in research necessary to determine whether and how empirically
supported treatments are being adopted in community programs. The authors point out that several
behaviorally based - and a few non-behaviorally based - methods are supported by
research. Among the most efficacious,
research-based methods are Discrete Trial Training (DTT), Pivotal Response
Training (PRT), and Incidental Teaching.
In addition, effective programs have been demonstrated to contain common
elements, including individualized supports and services, systematic
instruction, an understandable and structured environment, a curriculum
tailored to the needs of children with autism, a functional approach to problem
behaviors, and family involvement.
The study
conducted four focus groups composed of primary service providers drawn from 22
early intervention (EI) programs in two counties within which a total of
approximately 550 children with autism ages 0-5 years received services. Almost all participating providers had a
bachelor's (11) or master's (8) degree, with an average of about 10 years of
experience working with children with autism spectrum disorders (ASD). Each participant gave a brief overview of
their program for children with ASD.
They then read two age-matched vignettes depicting case histories of
children with ASD and answered questions aimed at assessing what types of
programs they would set up for each child, the extent to which they would
individualize the programs for each child, which techniques they considered to
have adequate research supporting their effectiveness, additional techniques
they might use or that they did not like to use, and any techniques that they
had discontinued along with the reasons for discontinuation.
To conduct a
qualitative analysis, transcribed audiotapes were independently coded and final
codes were constructed by consensus, developing a list of themes, issues,
accounts of behavior, and responses to the presentations of the vignettes. Results yielded interobserver
agreement levels of 93% to 95% when the coding system was applied to the
transcripts. Primary themes included (1)
using research-based practices, (2) understanding which practices are supported
by evidence, (3) selecting interventions, (4) adapting interventions, and (5)
specific training. Transcripts were also
coded to identify best practice elements common to excellent autism
programs. For a quantitative analysis,
the numbers of participants reporting use of specific techniques were tallied.
Of 30 interventions
that were listed by participants, the most common methods they reported using,
in descending overall order, were picture exchange communication systems (PECS,
95%), occupational therapy (OT, 77%); applied behavior analysis (ABA), broadly
defined to exclude DTT and PRT (73%); Floor Time (68%); DTT (64%); Treatment
and Education of Autistic and Related Communication Handicapped Children
(TEACCH, 55%); Sign Language (50%); PRT (32%); Music Therapy (23%) and minimal
use of any specific intervention programs (18%). Techniques that participants considered to
have a solid evidence base were
Participants
also reported making adaptations of research-based procedures in their
programs, the most common adaptation being the inclusion of multiple techniques
in one program. Most participants (76%)
reported selecting interventions based on the child's characteristics, with DTT
being used more for children with limited skills; naturalistic techniques being
used to promote generalization, increase motivation, teach social interaction
skills; and sign language and
The authors
concluded that both evidence-based practices and inadequately supported
practices were in common use in public EI systems. While most participants expressed a desire to
use research-based practices, the selection of EI practices seemed to be based
more on factors such as marketing, availability of training, and provider and
parent preference than on research. According
to the authors, "[i]t appeared that if a
participant had attended a workshop or lecture on a method, she felt there was
sufficient research to support it" (p. 71). Practices that were used were also highly adapted
and providers reported being inadequately trained. A positive finding, however, was that most
participants reported using the common elements of effective intervention
programs mentioned above, with the most commonly endorsed elements being the
use of a specialized curriculum (77%) and family involvement (77%) and the
least commonly endorsed element being a structured environment (64%).
The article
points out a need for research on a number of closely related issues including
whether procedures should or should not be combined, how procedures should be
adapted to individual children, and the fidelity of field implementation of
specific methods. The authors also
discuss the limitations and the implications of this creative and helpful
study, offering the reader a textured and nuanced view of a number of
significant issues deserving substantial future consideration by both
researchers and policy makers. In sum,
this creative and innovative study uses techniques not typically found in the
applied behavior analysis literature, makes an important contribution to our
current understanding of early intervention practices, points to a number of
issues that clearly warrant further research, and merits careful consideration
by behavior analysts involved in the development, implementation, and
dissemination of behavioral early intervention technology for children with
autism.
Bob Babcock, Ph.D., BCBA,
is the Coordinator of Psychological and Outreach Services for The Learning
Tree, Inc. His current activities at TLT include increasing
the availability of applied behavior analysis services in community
schools for children at risk of referral for residential
school services, developing staff training initiatives to promote inclusion and
intensive behavioral intervention services for preschool and school-age
children with autism and related disabilities, and providing behavioral
coaching for adolescents and adults with Asperger's Syndrome and their
families.
Carr, J. E. & Firth, A. M.,
(2005). The verbal behavior approach to early and intensive
behavioral intervention for autism: A
call for additional empirical support. Journal
of Early Intensive Behavioral Intervention, 2(1), 18-27.
Reviewed by: Suzannah Ferraioli, B.A.
Since the
publication of Lovaas' 1987 seminal outcome study on
early and intensive behavioral intervention (EIBI), behavioral instructional
methodology has been the most widely implemented and evidenced-based treatment
for children with autism (McEachin, Smith, & Lovaas, 1993; Smith, 1999).
The Lovaas model incorporates discrete-trial
instruction, intensive treatment delivery (40 hours per week), and a
developmentally sequenced curriculum (Leaf & McEachin,
1999) to create a behavioral treatment that effects positive outcomes in
children with autism over a number of years.
In response
to the recent advent of the verbal behavior (VB) approach, practitioners and
consumers requested more services that follow this protocol; consequently,
treatment manuals (Sundberg & Partington,
1998) and related assessments (Partington & Sundberg, 1998) are being widely implemented. The authors propose the hierarchy of steps
necessary to better establish the efficacy of the VB approach and to justify
its dissemination and implementation.
Carr and
Firth highlight several similarities between the Lovaas
and VB models. Firstly, they each stress
the importance of environmental control through their utilization of contrived
instructional settings, with ready access to salient tangible items and
activities to be delivered contingently upon correct responding. Secondly, both approaches teach behavior
based upon the expressive/speaker and receptive/listener relationships. Lastly, the Lovaas
and VB models deliver instruction and consequences in a discrete-trial
instruction format. However, the VB
model uses DTI concurrently with Natural Environment Training (NET) while the Lovaas approach uses only DTI. This point highlights a primary difference
between the two models, their approach to language training. NET facilitates generalization through a
focus on teaching in naturalistic settings as well as under contrived
conditions, and by capitalizing on current motivating operations. This contrasts to the systematic, analog
environment evoked under the Lovaas model, although generalization
may be integrated into instructional programming. In addition, the VB model teaches language
using a hierarchy of functions (e.g., mand, tact, intraverbal), and through function-specific motivating
variables. Conversely, the Lovaas approach teaches language in discrete steps, without
specific regard for the functionally relevant antecedents and consequences.
The logic
behind the VB approach is empirically based (e.g., Braam
& Poling, 1983; Miguel, Carr, & Michael, 2002; Drash,
High, & Tudor, 1999). However, this
evidence indirectly supports the components behind verbal behavior, rather than
the efficacy of the model itself. The
authors offer the suggestion that longitudinal outcome studies of the VB model,
similar to those conducted for the Lovaas model, may
lend more direct evidence for the validity of this treatment. In addition, comparisons between the VB
approach and other EIBI methodologies would provide more sound justification
for the use of the VB model.
To date, one
such evaluation has been described by Williams and Greer (1993). The authors compared accuracy and frequency
of words used across training trials under VB and linguistic (similar to the Lovaas program) models.
The VB curriculum targeted responses based upon the function hierarchy,
and the linguistic curriculum sequentially targeted labels, possession and
color, and comparative relationships (e.g., size, location). Results showed a similar number of correct
trials for participants across curriculum conditions, but the VB sessions
elicited higher frequencies and varieties of words, as well as higher rates of
correct responding during maintenance probes.
This study gives preliminary evidence for the effectiveness of the VB
approach; however, the authors reiterate that future replications and longitudinal
studies are necessary.
Carr and
Firth recommend several successive steps for future research in the area of
verbal behavior. First, they point to
published case studies that focus on the treatment effects elicited by EIBI with
a VB basis. These studies would also
address the need for long-term evaluations of the VB approach. One such study details a toddler who began
EIBI at 1 year, 2 months, and continued the program until 4 years, 5 months
(Green, Brennan, & Fein, 2002). His
treatment is tracked with regard to changes in curriculum, program intensity,
and standardized outcome (e.g., age-equivalent scores). The current authors highlight this last
component as another crucial step for the analysis of the VB approach; collateral
gains in IQ and age-equivalencies have not yet been documented. Reports modeled after the Green and
colleagues case study are a significant step toward sound evidence for the VB
model.
Another key
effort is the publication of outcome data for multiple cases. A comparison of data from a variety of
studies would allow for a) an evaluation of the reliability of treatment
effects, b) the comparison of treatment effects with published data sets, and
c) preliminary correlations between treatment outcomes and potential predictor
variables (e.g., comorbid diagnoses, intensity of
program supervision). A study by Bibby, Eikeseth, Martin, Mudford, and Reeves (2001) describes the progress of
multiple children who received EIBI from their parents. Their analysis of treatment outcomes suggests
that children benefited less from this parent-implemented model than those in
the Lovass study.
Although this predictor variable did not achieve statistical
significance, these results indicate that sound treatment fidelity may
facilitate better outcomes. The authors
express a hope that multiple case studies of the VB approach could produce
similar information.
Lastly, the
authors underscore the need for experimental or quasi-experimental treatment
comparisons, a topic on which we touched earlier. This last step would require outcome studies
between the VB model and a control condition.
Historically, a variety of EIBI methods have been supported through a
comparison with a control condition (Lovaas, 1987; Sheinkopf & Siegel, 1998; Smith, Eikeseth,
Klevstrand, & Lovaas,
1997). Although the wide dissemination
of EIBI strategies may pose a difficulty in finding control groups, standard
treatment control groups are evidenced to be an effective basis for comparison
(Kazdin, 2003).
Additional considerations include the need for subject matching prior to
treatment implementation. It is the
authors' hope that these control studies will help standardize the procedures
of VB in practice and document the outcomes of the VB model on standardized
measures.
In
conclusion, the authors recognize the VB approach as a viable model that
deserves further empirical analysis. A
systematic progression from case studies to multiple comparisons, and finally
to experimental evaluations may provide evidence to justify the widespread
implementation of the VB model in a clinical setting.
Suzannah
Ferraioli is a graduate student in the Department of
Psychology at
Seligson-Petscher E., Bailey J., (2006). Effects of training, prompting, and
self-monitoring on staff behavior in a classroom for students with
disabilities. Journal of Applied Behavioral Analysis, 39, 215-226.
Reviewed
by: Jennifer L. Buck, M.Ed., Ellsworth,
Far
too often, paraprofessionals and instructional assistants are not trained to effectively
work with students with disabilities. While
the typical classroom rules and reprimands may be appropriate for some
students, they may not suit the needs of a student with a disability. Uncontrolled and unpredictable behavior exhibited
by a student with a disability can interfere not only with the student's
ability to learn but may also affect the teacher's ability to teach the
student. Therefore, effective staff
training and feedback sessions are warranted to train school staff to manage
student and classroom behavior.
Over
the past 8 years, three studies have evaluated the effectiveness of tactile
prompts in classroom settings. These
studies used vibrating pagers to improve the social initiations and
communication skills of children with disabilities (Shabani
et al., 2002; Taylor, Hughes, Richard, Hoch, & Coello,
2004; Taylor & Levin, 1998). In
contrast to these studies, the current authors explored the effectiveness of
tactile prompts in modifying the behavior of instructional staff rather than
students. In this study, vibrating
pagers were used to increase accurate implementation of a classroom token
economy system by instructional staff members.
Three
female paraprofessionals were selected as participants for the current study. Each instructional assistant had less than
one year experience in their current classroom placement. All participants worked in a self-contained
classroom for third- to fifth-graders with multiple disabilities (e.g.,
emotional handicaps, language impairments, Asperger's syndrome, mental
handicaps) in need of behavioral support.
A token economy was in place for all students, and the tactile prompt
intervention used in this study targeted each teacher's management of
disruptive behavior using a response cost system, delivery of bonus points to
students who were exhibiting appropriate behavior, and prompting students to
engage in appropriate behavior when a student was not engaged in the expected
activity.
The
current study used a moving treatments multiple baseline across behaviors
design (Bailey & Burch, 2002). Prior
to implementation of the intervention, baseline data was collected by observing
normal classroom conditions. Participants
in this study were aware of the observation but did not know the variables of
interest. Observers recorded occurrence
or nonoccurrence of the target teacher behavior. Following baseline, all 3 participants
attended one training session during which the experimenter described the
goals, procedures, dependent variables, and expectations of the classroom token
economy system using didactic training and modeling. Each participant took a post-test in which
they were asked to identify possible antecedents and appropriate responses to
different scenarios. Following this
training, data was collected in the classroom as it was collected in baseline
until stable responding was observed.
Once
stability was demonstrated across all participants, the intervention package
(prompting, self monitoring and accuracy feedback) was then applied to the
first targeted behavior, managing disruptions.
The trainer met with participants to discuss and demonstrate the use of
the pager and self-monitoring form. Participants
were required to clip the pager onto the pants or place it into a pocket. The trainer then explained that she would
send participants a tactile prompt via vibrating pager when there was an
opportunity to manage a disruption (or, for later target behaviors, deliver a
bonus-point or prompt appropriate behavior).
Correct and incorrect teacher responses to the student's behavior were
recorded. At the end of each 10 minute
session (conducted three times per day) the participants were asked to complete
a self-monitoring form indicating their perceived performance on the targeted
skill during the session. The
experimenter assessed the accuracy of the self-monitoring form by comparing
observation notes with completed self-monitoring forms. The experimenter then provided the teacher
with accuracy feedback on actual performance during the session, as measured
during observation, noting any discrepancies between teachers' perceived
performance and their actual performance.
When teachers
exhibited 100% appropriate responding and correct self-monitoring on three
consecutive sessions, the prompting layer of the treatment plan was then
removed from the first target behavior while self-monitoring and accuracy
feedback remained in place. The entire
intervention plan was then applied to the next targeted behavior, bonus-point
delivery. Once all 3 participants were
able to consistently meet the goal for bonus point delivery, the prompting
component was removed from the second target behavior (bonus-point delivery)
and the full intervention plan was then applied to the last targeted behavior,
prompting appropriate behavior. The
prompting layer was removed from this behavior when all participants met
criteria on prompting appropriate behavior.
When a final demonstration of stable responding was observed, the self-monitoring
and accuracy feedback layers of the intervention plan were then removed from
all three target behaviors and maintenance data was collected. Maintenance sessions gradually increased from
10 minutes to 60 minutes during which data collection still occurred.
All 3
participants exhibited dramatic increases in performance of the target behavior
following the implementation of the prompting and self-monitoring procedure. While teacher training on the rationale and
expectation of the token economy led to variable and low performance among
teachers, prompts and self-monitoring led to high, stable performance. This behavior was maintained following the
removal of prompting while only self-monitoring remained in place, though for
some teachers performance was slightly lower and more variable in this phase. All teachers demonstrated lower and more
variable responding in the maintenance phase, though the authors point out that
this should be interpreted with caution due to the decreased opportunities for
teacher response in the classroom during the maintenance phase.
In
conclusion, the current research shows that the implementation of tactile
prompting and self- monitoring forms show an increase from near-zero levels
during baseline and training sessions to consistently high rates after the
initial implementation of the intervention package. In addition, high teacher performance levels
were maintained with the absence of the prompting layer of the intervention
package. It is possible that the prompting
procedure was responsible for the overall increase in consistency rather than
the self-monitoring procedure. Future
studies should include isolation of tactile prompting as an intervention to
improve staff behavior. Self-monitoring,
however, seemed to maintain skills at a level not seen when it was discontinued
in the maintenance phases. Self-monitoring
may be an important component for maintenance in teacher performance. From a teacher's perspective, I believe that
any teacher, not only those who work with the disabled student, would benefit from
this intervention package.
References
Bailey, J. S., & Burch, M. R.
(2002). Research methods in applied behavior analysis.
Shabani, D. B., Katz, R. C., Wilder, D. A., Beaucham, K., Taylor, C. R., & Fisher, K. J. (2002). Increasing social initiations in children with
autism: Effects of a tactile prompt. Journal of Applied Behavior Analysis, 35, 79-83.
Taylor, B. A., Hughes, C. E., Richard,
E., Hoch, H., & Coello, A. R. (2004). Teaching
teenagers with autism to seek assistance when lost. Journal of Applied Behavior Analysis, 37, 79-82.
Taylor, B. A. & Levin, L. (1998).
Teaching a student with autism to make verbal initiations: Effects of a tactile
prompt. Journal of Applied Behavior
Analysis, 31, 651-654.
Jennifer Buck, M.Ed., is a graduate
student in the
Nock, M. K., & Kurtz, S., (2005).
Direct behavioral observation in school settings: Bringing science to practice.
Cognitive and Behavioral Practice, 12,
359-370.
Reviewed by: Nanci Valente, L.D.T.C., M.A., Secaucus
Child Study Team,
The
reauthorization of the Individuals with Disabilities Education Act (IDEA, 2005)
mandates that a school observation be a required component of evaluations for
students who may exhibit behavior concerns.
Further, IDEA recommends that functional behavioral assessments for
these students also be carried out as part of the evaluation process.
According to
the authors of this article, however, a gap exists between strictly formatted,
objective assessment procedures detailed in the literature and less structured,
subjective methods that are more customarily used to evaluate student behavior
in school settings. This paper
recognizes the value of conducting an observation of a child in the school
setting and provides clinicians with a framework to perform meaningful, valid
and research-based evaluations of child behavior in the school environment.
School
settings provide a structured environment with opportunities to observe and
assess children across a variety of domains.
Direct observation provides the observer with the opportunity to witness
specific behavior, which results in a more precise, descriptive evaluation of
target behavior. Observation allows for
an assessment of the function of such behavior, as well as the typical
frequency and severity measures that could be provided by a rating scale. Such observations are based on direct,
objective data, and have the additional advantage of assessing the antecedent
and consequences of the behavior episodes (Nock et al, 2004). As behavior analysts would agree, such
information is essential to the development of functionally relevant behavior
reduction plans.
Behavior
rating scales have traditionally been utilized to measure possible problem
behavior in the classroom. The authors
discuss several standardized frameworks that have been developed for assessing
behavior. The Classroom Observation Code
(COC) discriminates between hyperactive and non-hyperactive children across 14
categories of observation (Abikoff & Gittelman, 1985). The
School Observation Coding System (SOCS) and Revised Edition of the School
Observation Coding System (REDSOCS) code dimensions of behavior into categories
such as appropriate versus inappropriate, compliant versus noncompliant, and
off task versus on-task (Jacobs et al, 2000; McNeil et al, 1991).
Direct
observation coding systems, such as the Direct Observation Form included in the
Child Behavior Checklist (CBCL, Achenbach, 1986) and the Student Observation
System included in the Behavior Assessment System for Children (Reynolds & Kamphaus, 1998) measure predetermined behavior problems and
are meant to supplement teacher-, parent-, and self-report forms. While these measures assess a wide range of
behavior exhibited in a natural setting, they lack the specific descriptions
that are provided by other observation methods.
Further, standard observation formats may not be applicable to the
behavior deficits demonstrated by all children, including individuals with
autism. If a standard observation format
does not appropriately address the behavior of a specific individual, the
authors suggest conducting an observation based on the principles of behavioral
assessment. Their description of such an
assessment follows.
The authors
propose that a school-based observation offers many advantages such as the
ability to assess behavior in a natural, typical environment, which provides a
valid and realistic profile of problem behavior. To assist the practitioner in conducting an
effective behavioral assessment observation, user-friendly information about
identifying, defining and assessing behavior is outlined and discussed in the
article. Sample entries for coding
behavior are also provided.
The authors
recommend that the target behavior should be clearly defined, using criteria
that are observable and measurable. The
description of the target behavior should include a discussion of the events
and influences that may contribute to the behavior, as well as the consequences
for the behavior. Once the behavior has
been clearly defined, direct observation is conducted to assess the occurrence
of the behaviors. A variety of methods,
such as descriptive format, checklists, frequency recording or interval
recordings will provide objective, data-based behavioral assessment. The descriptive method is indicated when
specific characteristics and determinants of the behavior are unknown. An objective account of the mechanics of the
behavior, its duration and intensity are noted in a descriptive chart
format. A checklist method may also be
used to record the occurrence of behavior.
Checkmarks are coded during the direct observation, which indicate the
frequency of the behavior in a time interval, or in a specific environment. Interval methods may be used to code whether
a behavior occurred during a specific time interval. Interval recording techniques may also be
used to code antecedent-behavior-consequence sequences. Information generated from these methods can
be converted to a data-based format for analysis and interpretation.
A final note
regarding behavioral assessment: While the occurrence of maladaptive behavior
may be the reason for a behavioral assessment, the ultimate purpose of an
intervention is to provide a replacement behavior. This alternative behavior should be equally
specific, and in direct opposition to the problem behavior. The current frequency of a possible
replacement behavior (e.g., requests for breaks, tangible items, attention,
etc.) should be noted during an observation.
The
evaluation report framework should be guided by the above noted criteria. The authors suggest a format that delineates
the following categories:
- Descriptive
information, including demographics of the child as well as specific
environmental details of the observation.
-
Reason
for observation, including the goals, primary referral questions and behavior
to be targeted.
-
A
teacher interview that defines the problem behavior, provides a history of
interventions, and identifies behavior triggers.
-
The
observation techniques should be identified and described. Results should incorporate the severity,
frequency and duration of target behavior with supporting data described.
-
The
narrative of the child's observed behavior and activities should incorporate
functional observation as well as the evidence-based data.
-
Recommendations
are strengthened by the use and interpretation of the data. There should be a clear connection between
the initial behavioral concerns and the data, to the summary, to the
recommendations.
This article
provides many powerful and important considerations for collecting the information
necessary to develop potentially effective treatments. Best practices have emerged which provide the
practitioner with an established set of procedures and rules for conducting a
systematic behavior analysis and subsequent intervention strategies (Hanley,
Iwata & McCord, 2003). Ongoing
refinement of environment-based assessments through continued research will
continue to strengthen the efficiency and effectiveness of this clinical
practice.
As many
readers are aware, the journal Cognitive
and Behavioral Practice is read by psychologists and other professionals
who may be more inclined to use a cognitive behavioral versus a behavior
analytic approach, and may be more familiar with nomothetic
assessment methods versus idiographic assessment methods. Therefore, the publication of this article in
such a journal will hopefully encourage and support individuals in the use of
assessment methods that are hallmark to applied behavior analysis.
References
Abikoff, H., & Gittelman,
R. (1895). Classroom observation code: A modification of the Stony Borrk code. Psychopharmacology
Bulletin, 21, 901-909.
Hanley, G. P., Iwata, B. A., &
McCord, B. E. (2003). Functional analysis of problem behavior: A review. Journal of Applied Behavior Analysis, 36,
147-185.
Jacobs, J. R., Boggs, S. R., Eyberg, S. M., Edwards, D., Durning,
P., Querido, J. G., McNeil, C. B., & Funderburk, B. W. (2000).
Psychometric properties and reference point data for the Revised Edition
of the School Observation Coding System. Behavior
Therapy, 31, 695-712.
McNeil, C. B., Eyberg,
S. M., Eisenstadt, T. H., Newcomb, K., & Funderburk, B. (1991). Parent-child interaction therapy
with behavior problem children: Generalization of treatment effects to the
school setting. Journal of Clinical Child
Psychology, 20, 140-151.
Nock, M. K., Goldman, J. L., Wang, Y.,
&
Nanci Valente is a Learning Disabilities
Teacher Consultant for the Secaucus NJ Child Study Team. She is a certified
Speech Language Specialist and Special Education Teacher, and has a
Masters in Supervision and Administration from
Rapp, J.T. and Vollmer, T.R.,
(2005). Stereotypy II: a review of
neurobiological interpretations and suggestions for an integration with
behavioral methods. Research in Developmental Disabilities, 26, 548-564.
Reviewed by
Anna Lewis, B.A.
Studies on
stereotypic behaviors have been conducted by researchers from either a
behavioral or neurobiological perspective.
Although the models for stereotypy used by these two groups are not
mutually exclusive, there has been little convergence between the two bodies of
literature. The divide between
behavioral and neurobiological research has widened considerably over the past decade. The authors of this paper strongly advocate
the reversal of this trend, highlighting areas in which integrative research
holds the greatest promise. They provide
an overview of neurobiologically based research on
stereotypy over the past few decades, looking first at pharmacological and
neurobiological interpretations of stereotypic behaviors, and then at possible
pharmacological interventions for such behaviors.
Neurobiological
researchers have generated several hypotheses regarding the etiology and
persistence of repetitive behaviors in nonhumans. This line of research has investigated the
effects of environmental deprivation, injections of neurotransmitters,
chemically induced lesions, and stress-inducing events on stereotypic behavior. The major point of agreement across research on
all of these conditions is that the dopaminergic
system plays an important role in the stereotypy of nonhumans, a hypothesis
supported by earlier findings that stereotypy can be induced by a dopamine
agonist and then reduced by a dopamine antagonist. Unfortunately, the results of many of these
studies are difficult to interpret due to methodological issues (i.e., lack of
relevant controls).
A number of
pharmacological interventions have been used to treat stereotypy in
developmentally disabled individuals.
Much of the literature has examined the effects of serotonin reuptake
inhibitors (SSRIs) and opiate agonists.
Though antipsychotic medications were once popular choices for the
treatment of stereotypy, research on this class of medications has decreased in
recent years, due to the potential for development of debilitating side
effects, such as tardive dyskinesia.
A
considerable amount of research has investigated the effects of serotonin
reuptake inhibitors on stereotypic behaviors.
These medications presumably work by increasing the availability of
serotonin in the brain. The results of
these studies have been mixed, and again, the results have been difficult to
interpret due to limitations in experimental methodology, such as
non-replicating treatment designs, variations in dosage of the medication under
investigation, subjects concurrently taking other psychoactive medications, and
disagreements in ratings between different groups of observers.
Opiate
antagonists are often considered by researchers as possible treatments for
self-injurious behavior (SIB) as well as stereotypic behaviors. The main biological hypotheses for the
occurrence of SIB in individuals with developmental disorders involve
endogenous opiates - chemicals in the brain that produce euphoric
sensations. Some researchers suggest
that individuals engage in SIB or stereotypy in order to facilitate the release
of endogenous opiates, while others think that the function of SIB/stereotypy
is to avoid the effects of opiate withdrawal, or that individuals who exhibit
SIB/stereotypy naturally produce excessive levels of endogenous opiates, which
blocks pain sensation. Opiate
antagonists block endogenous opiates at the receptor cite, preventing the opiates
from producing euphoric effects, and are therefore potentially useful in the
treatment of SIB and stereotypy. Similar
to other pharmacological studies, the effects of opiate antagonists have
yielded mixed results (e.g., often not designed to evaluate stereotypy
specifically, incomplete designs).
Ultimately,
the fundamental differences in methodology between pharmacological studies and
applied behavioral studies of stereotypy have made it difficult to make
inferences between findings in the two literatures. For instance, studies of pharmacological
interventions have most often used indirect measurement methods, such as rating
scales, to gauge overall changes in multiple response forms, while applied
behavioral studies have mainly used direct observations of single response
forms. With methodological differences
such as these, the same investigation of the same participants using the two
approaches could very possibly yield very different results. This is not to suggest that one of the two
approaches is better, but rather that different circumstances call for
different approaches. For example, it
may be best to limit group designs to studies in which each participant
exhibits a common response form, as recent studies suggest that different brain
regions may be responsible for inducing specific stereotypic response forms in
non-humans. At the same time, it would
be wise for behavioral studies to add rating scales to their direct observation
methods, in order to gauge the social validity of any behavior change that may
be produced. In all of these studies,
direct observational measures of stereotypy should be emphasized, with clearly operationalized definitions of the behaviors under
evaluation. Studies in the future should
also explore the possibility of beneficial interactions between pharmacological
and behavioral interventions. Several
studies have suggested that certain pharmacological treatments seem to change
the reinforcing value of specific events, and potential improvements in the
outcomes of dual-modality interventions could be achieved by determining the
degree to which such a value change takes place in the presence of various
dosages of a given drug. Another
promising area in which little to no research has been conducted is the effect
of behavioral interventions on stereotypy following successful pharmacological
intervention. If a given pharmacological
intervention decreased stereotypy, it is possible that the right behavioral
intervention might maintain this decrease, thereby reducing the need for
ongoing use of medication.
The authors
conclude with the assertion that, while large-scale placebo-controlled studies
of pharmacological interventions for stereotypy should continue, research in
this area should also incorporate behavioral methods including single-subject
experimental designs and differentiated measurement of individual response
forms. They also advocate the use of
functional analysis and descriptive analysis to identify specific subtypes of
stereotypy that may be resistant to environmental manipulation, and thus are
cases in which pharmacological interventions are most appropriate. Primarily, however, they advocate a more
universal adherence to traditional behavioral standards for response
definitions, direct observation, repeated measurement, and experimental controls,
in the hopes that more of the research in this area will obtain findings that
can be both understood and applied to further work by researchers on both sides
of the neurobiological-behavioral divide.
Elder, J.H., Shankar, M.,Shuster, J., Theriaque, D.,
Burns, S., and Sherrill, L., (2006). The Gluten-Free, Casein-Free Diet in
Autism: Results of a preliminary double blind clinical trial.
Journal of Autism and Developmental Disorders, 36 (3), 413 - 420.
Reviewed by
Jana Horowitz, Psy.M.,
The complex
and still misunderstood nature of autism often leads individuals to utilize
various, treatments, such as the Gluten-Free, Casein-Free (GFCF) diet that have
yet to be empirically validated.
Anecdotal parent report suggests that children with Autistic Spectrum
Disorder (ASD) who follow the GFCF diet demonstrate improvement in language and
social skills; however, there is currently a lack of empirical support for
these claims. The authors cite
preliminary evidence for the benefits of a "structured" diet for
children with autism, but explain that previous studies were methodologically
limited.
In the
current study, the researchers randomized 15 children with ASD to either the
experimental group, who received the GFCF diet, or the control group, who
received a placebo diet (similar, specially prepared meals that were not gluten
and casein free). All meals were
provided by the investigators.
Participants and the investigators were blind as to which subjects were
receiving the diet. The dependent
variables of interest were measured using the Childhood Autism Rating Scale
(CARS), to measure the different symptoms of autism; Urinary Peptide Levels
(UPL), to determine the levels of casein and gluten peptides; the Ecological
Communication Orientation (ECO) Language Sampling Summary, to examine
linguistic skills; and in-home observation, to examine behaviors such as "child
initiating, child responding, and intelligible words spoken."
The
researchers did not find any significant differences between the experimental
and the control group on any of the measures utilized to test the dependent
variables. However, several parents
reported improvement in their children and made the decision to continue with
the diet even after the study results were disseminated. The authors point out that their study had
several methodological limitations such as a small, heterogeneous sample,
potential diet noncompliance, the inability of the CARS to detect subtle behavioral
changes and possible placebo effect impacting parent report of the diet's
effectiveness. Despite these limitations
and the non significant findings, this study presents a well-constructed design
that could be utilized by future researchers to test the GFCF and other
structured diets.
Codding,
R. S., Dunn, E. K., Feinberg, A. B., & Pace, G. M., (2005). Effects of immediate performance feedback on
implementation of behavior support plans.
Journal of Applied Behavior
Analysis, 38, 205-217.
Reviewed by:
April Poulsen, M.Ed.
The No Child
Left Behind Act can be praised for its efforts to further accountability in
public school settings. This is
consistent with the interest of a number of researchers who are developing and
evaluating effective and efficient strategies to promote the integrity of
school based interventions. One
intervention strategy that has shown to be successful in enhancing treatment
integrity is performance feedback (Mortenson &
Witt, 1998; Noell et al., 1997, 2000, 2002; Witt et
al., 1997).
In the
literature, several components of performance feedback are often highlighted,
including: review of data, reinforcement for accurate/adequate
implementation, corrective
feedback, and addressing questions or
comments. The implementation of academic
interventions, such as peer tutoring (Noell et al.
2000), contingent praise (Jones, Wickstrom, & Friman, 1997, Martens, Hiralall,
& Bradley, 1997), and implementation of behavior management interventions,
more specifically data collection (Noell et al. 2002)
has already been targeted for improvement via performance feedback. In the current study, Codding,
Dunn, Feinberg, & Pace (2005) also examined the effects of performance
feedback on data collection; however, it was noted by the authors that Noell and colleagues used performance feedback to address
only one aspect of behavior management: data collection. Although reliable data collection is
essential, the current study extended the existing literature by examining two
other aspects of plan implementation: 1) Implementation of antecedent
interventions to decrease the likelihood of problem behavior; and 2)
Implementation of consequences. As a
special education teacher, I can appreciate the need for these two areas to be
examined more closely within the literature.
The
participants in this study were five special education teachers who worked in a
private school for students with acquired brain injury, with between 6-30
months experience working at this school.
All of the teachers had bachelor degrees and were enrolled in masters degree
programs in special education. It is
important to note that the participating teachers had both general and student
specific formal training in the implementation of behavioral support
plans. As will be discussed later, these
experiences may put some constraints on the generalizability
of these findings. Each teacher was
paired with a male student between the ages of 10-19 years old with acquired
brain injury (3 with non-traumatic, 2 with traumatic brain injury) who
exhibited significant behavior problems.
This student sample represented about 10% of the school population.
Teacher-student
dyads were observed for approximately 60 minutes, every two weeks on a
variable-interval schedule, within a classroom setting (two teacher-student
dyads were in Classroom 1 and three teacher-student dyads were in Classroom
2). Baseline observations were conducted
until stable or decreasing performance in baseline was demonstrated by either
the percentage of antecedent or consequence components implemented as written. On the same day as each observation, the
experimenter met with the teacher for an average of twelve minutes, outside of
the classroom. During this time,
behavior support plans were reviewed and feedback was provided for all
components that were observed.
Performance feedback was ended after improved performance was stabilized
and 1-3 maintenance sessions (identical to baseline) were conducted with 5 week
intervals, for each dyad.
Overall
results of the study demonstrated that the accuracy with which a behavior plan
was implemented improved across all five teacher-student dyads following
performance feedback. In addition,
results of the performance feedback were maintained for up to 15 weeks after
the study was completed. There were,
however, some differences noted in the amount of improvement of antecedents
versus consequence components between the two classrooms. Classroom 2 showed a greater improvement for
antecedent interventions following feedback than the two dyads in Classroom
1. The authors noted that antecedent
procedures may have operated as a part of the daily classroom routine in
Classroom 2 and therefore affected the implementation of antecedent components
to a greater degree.
The results
of this study suggest that performance feedback is an acceptable and effective
intervention for improving the treatment integrity of special education
teachers' administration of antecedent and consequence components of behavior
support plans. There are however, a
number of factors that may influence the effectiveness of performance feedback
and warrant future study. Some of these
possible directions include: the social validity of performance feedback for
teachers, how a teacher's active role in developing support plans affects their
implementation of such plans, and the role and effect of previous instruction
and training in support plan implementation.
On a more practical note, the article appendix contains a copy of the
Integrity Assessment for Behavior Support Plans. I found this checklist to be very useful and
will be using it with my staff this upcoming school year.
References
Jones, K. M., Wickstrom,
K. F., & Friman, P. C. (1997). The effects of observational feedback on
treatment integrity in school-based behavioral consultation. School
Psychology Quarterly, 12, 316-326.
Martens, B. K., Hiralall,
A. S., & Bradley, T. A. (1997). A
note to teacher: Improving student
behavior through goal setting and feedback. School
Psychology Quarterly, 12, 33-41.
Mortenson, B. P., & Witt, J. C.
(1998). The use of weekly performance
feedback to increase teacher implementation of a pre-referral academic
intervention. School Psychology Review,
27, 613-627.
Noell, G. H., Duhon,
G. J., Gatti, S. L., & Connell, J. E.
(2002). Consultation, follow-up, and
implementation of behavior management interventions in general education. School
Psychology Review, 31, 217-234.
Noell, G. H., Witt, J. C., Gilberston, D. N., Ranier, D. D.,
& Freeland, J. T. (1997). Increasing
teacher intervention implementation in general education settings through
consultation and performance feedback. School Psychology Quarterly, 12, 77-78.
Noell, G. H., Witt, J. C., LaFleur, L. H., Mortenson, B. P.,
Ranier, D. D.,
& LeVelle, J. (2000). Increasing intervention implementation in
general education following consultation:
A comparison of two follow-up strategies. Journal
of Applied Behavior Analysis, 33, 271-284.
Witt, J. C., Noell,
G. H., LaFleur, L. H., & Mortenson,
B. P. (1997). Teacher use of interventions
in general education settings: Measurement and analysis of the independent
variable. Journal of Applied Behavior Analysis, 30, 693-696.
Sallows,
G. O. & Graupner, T. D., (2005). Intensive
Behavioral Treatment for Children with Autism: Four-Year Outcome and
Predictors. American Journal on Mental
Retardation, 110 (2), 417-438.
Reviewed by:
Lara Delmolino, Ph.D., BCBA, & Karen Lenard, MS.Ed.
Douglass
Developmental
The evidence
that intensive early behavioral intervention is an effective intervention originated
with the Lovaas study, published in 1987. That study showed dramatic improvements in
the experimental group with post treatment scores increasing to the average
range. However subsequent attempts to
replicate these results were not as striking, casting doubt on the importance
of Lovaas' findings.
Sallows and Graupner
(2005) sought to replicate the UCLA results without the use of aversive stimuli
and including additional behavioral techniques that have demonstrated
effectiveness. The researchers compared
outcomes between a clinic-directed group, providing the supervision and
intensity of treatment hours in the UCLA study with and a parent-directed
group, in which supervision was lower and parents selected the intensity of
treatment hours they wanted. Twenty-four
participants (nineteen boys and four girls) participated in the study. Participants began treatment between 35 and
37 months of age, with treatment lasting for up to four years. All children met the criteria for autism as
outlined in the DSM-IV and in the Autism Diagnostic Interview - Revised
(ADI-R).
Children were
randomly assigned to either the clinic-directed group or the parent-directed
group, which was intended to be less intensive.
The actual weekly means of direct treatment differed by about 7 hours,
39 for the clinic-directed and 32 for the parent directed group during the
first two years. The clinic-directed
group received approximately 6-8 hours per week of supervision and weekly
review by a clinic supervisor, while the parent-directed group received 6 hours
per month of supervision by a senior therapist and review every other month by
a clinic supervisor.
To evaluate
pre-treatment levels of performance and post-treatment gains, measures included
instruments to assess IQ, language, adaptive behavior, and early learning
rates, including: Bayley Scales of Infant
Development, 2nd edition, Merrill-Palmer Scale of Mental Tests, Reynell Developmental Language Scales, and Vineland
Adaptive Behavior Scales. Follow-up
tests administered annually included IQ - Wechsler Preschool and Primary Scale
of Intelligence-Revised (WPPSI), or the Wechsler Intelligence Scale for
Children (WISC-II), or the Bayley II, and the Leiter-R. Language
tests included the Clinical Evaluation of Language Fundamentals, 3rd edition
(CELF III) or the Reynell Developmental Language
Scales. The Vineland Adaptive Behavior
Scales was re-administered to all children.
Post-treatment
social, behavioral, and adaptive functioning was measured using the Autism
Diagnostic Interview-Revised (ADI-R), the Personality Inventory for Children
(PIC), the Child Behavior Checklist (CBC), and both parent and teacher Vineland
scores. When the children reached seven
years of age, academic functioning was measured using the Woodcock-Johnson II Test
of Achievement. Treatment curriculum
included that described by Lovaas minus the aversive
procedures and additionally including procedures supported by more recent
research. Learning sessions initially
began at 30 seconds in length and were interspersed with playful interactions
with therapists/parents to increase compliance and social responsiveness as
well as to teach generalization of new skills in less structured settings.
RESULTS
Of the 11
rapid learners, 5 received services in the clinic-directed model and 6
participated in the parent-directed model.
The clinic-directed rapid learners were found to have higher
pre-treatment IQ's, Vineland Scores and Verbal Imitation abilities than those
in the parent-directed group, which prevented the planned comparison between
rapid learners in the clinic-directed and parent-directed groups.
Regression
analyses were used to identify pretreatment predictors of outcome. The authors found that post treatment IQ was
best predicted by the Early Learning measure, pretreatment IQ, and ADI-R
communication and social interaction scores.
Additionally, acquisition of social skills and language skills were
predicted by pretreatment ability to imitate.
Change after one year was also a strong predictor of outcome. Although absence of expressive language (at
36 months) was associated with more moderate learning, regression of speech was
not. Lastly, the number of hours of
treatment each week was less related to outcome measures than were pretreatment
measures.
Overall, the
study demonstrated that the UCLA model of intensive intervention could be
replicated outside of a university setting, utilizing both clinic-directed and
parent-directed treatment models, with all children demonstrating improvement
across skill areas over four years of treatment. Further, and consistent with Lovaas' 1987 study, 48% of the 23 children receiving
treatment made large gains with post treatment IQ, language, and socialization
scores in the average range and effective participation in regular education
after four years. The present study
offered confirmatory evidence of Lovaas' 1987 finding
that nearly half of the children receiving intensive behavioral intervention
could achieve average functioning.
May 12,
2008