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BRIEF REPORT
Brief Report: A Pilot Summer Robotics Camp to Reduce Social
Anxiety and Improve Social/Vocational Skills in Adolescents
with ASD
Juhi R. Kaboski •Joshua John Diehl •
Jane Beriont •Charles R. Crowell •
Michael Villano •Kristin Wier •Karen Tang
ÓSpringer Science+Business Media New York 2014
Abstract This pilot study evaluated a novel intervention
designed to reduce social anxiety and improve social/
vocational skills for adolescents with autism spectrum
disorder (ASD). The intervention utilized a shared interest
in robotics among participants to facilitate natural social
interaction between individuals with ASD and typically
developing (TD) peers. Eight individuals with ASD and
eight TD peers ages 12–17 participated in a weeklong
robotics camp, during which they learned robotic facts,
actively programmed an interactive robot, and learned
‘‘career’’ skills. The ASD group showed a significant
decrease in social anxiety and both groups showed an
increase in robotics knowledge, although neither group
showed a significant increase in social skills. These initial
findings suggest that this approach is promising and war-
rants further study.
Keywords Autism spectrum disorder Intervention
Treatment Robotics Vocational Social skills
Autism spectrum disorder (ASD) is a developmental dis-
order that can cause lifelong challenges; however, in con-
trast to a plethora of early childhood interventions for very
young children with ASD, there is a dearth of evidence-
based interventions that specifically target adolescents with
ASD (Hendricks 2010; Webb et al. 2004). This lack of
support is problematic considering that some of the most
challenging aspects of ASD related to socialization deficits
usually do not remit with natural development (Locke et al.
2010; Shattuck et al. 2007). To the contrary, these deficits
could become more debilitating and distressing in adoles-
cence due to the fact that social demands become
increasingly complex with age (Webb et al. 2004). Ado-
lescents with ASD who fail to smoothly navigate their
social milieu can often become targets of victimization and
rejection by peers (Shtayermman 2007). As adolescents
with ASD grow more conscious of their own social diffi-
culties, many of them develop symptoms of social anxiety
and depression (Gillott et al. 2001; Sterling et al. 2008);
consequently, social anxiety is likely to lead to diminished
social initiation, thereby self-limiting natural opportunities
to practice social skills (White and Roberson-Nay 2009).
Considering their social difficulties and frequently
accompanying mental health issues, it is not surprising that
adults with ASD are reported to be among the least suc-
cessful groups of individuals in terms of community inte-
gration, post-secondary education, and employment
outcomes, even when compared to populations with other
forms of disability (Newman et al. 2011; Orsmond et al.
2004; Schall 2010). In order to promote more positive adult
outcomes in this vulnerable population, development of
J. R. Kaboski J. J. Diehl (&)J. Beriont
C. R. Crowell M. Villano K. Wier K. Tang
Center for Children and Families, University of Notre Dame,
1602 N. Ironwood Dr., South Bend, IN 46635, USA
e-mail: joshua.diehl@nd.edu
J. R. Kaboski
e-mail: juhi.kaboski@nd.edu
J. Beriont
e-mail: jberiont@nd.edu
C. R. Crowell
e-mail: ccrowell@nd.edu
M. Villano
e-mail: mvillan1@nd.edu
K. Wier
e-mail: Kristin.G.Wier.1@nd.edu
K. Tang
e-mail: ktang@nd.edu
123
J Autism Dev Disord
DOI 10.1007/s10803-014-2153-3
evidence-based and targeted interventions to help adoles-
cents with their social competence and vocational devel-
opment should be of high priority.
Traditional interventions to build peer interaction skills
of older children with ASD generally fall into two cate-
gories: (1) social skills training (SST) provided by an adult
instructor to children with ASD, either in a 1:1 or group
setting (Bellini et al. 2007; Rao et al. 2008; White et al.
2007); and (2) peer-mediated interventions (PMI), in which
typically developing (TD) peers and children with ASD
purposefully interact under the supervision of an adult
instructor, and the TD children are usually given special
training in how to engage the child with ASD (Bass and
Mulick 2007; Maheady et al. 2001; McConnell 2002;
Sperry et al. 2010). Both approaches are considered evi-
dence-based, with comparative advantages and disadvan-
tages. For example, direct SST is delivered by trained
professionals under a controlled setting, allowing for more
targeted and explicit instructions; however, it can be
extremely costly and generalization of the acquired skills to
the child’s natural environment has been poor (Bellini et al.
2007; Rao et al. 2008; White et al. 2007). Although PMI
may result in better generalizability and cost-effectiveness
(Kasari et al. 2012), it may not be appropriate for high-
functioning adolescents. There is some evidence that in
older children interventions that provide TD children with
descriptive information regarding a co-participant’s illness/
disability tend to improve the TD children’s cognitive
understanding of the illness/disability but do not always
lead to social acceptance and instead could have the
unintended effect of stigmatizing the child with disability
(Potter and Roberts 1984; Bell and Morgan 2000). This
may be due to the tendency of adolescents to distance
themselves from peers with disabilities, possibly because
they perceive those peers as different from themselves
(Rosenbaum et al. 1988; Ryan 1981).
We designed an intervention incorporating the beneficial
aspects of PMI while minimizing its pitfalls by focusing on
the unique strengths and special interests of adolescents
with ASD, rather than on their social deficits or on pro-
viding special training to TD peers. This method is based
on an exploratory approach designed by Koegel et al.
(2012) with elementary school-aged children. The inter-
vention by Koegel and colleagues targeted social skills
performance rather than social skills acquisition:itis
appropriate for children with ASD who have already
acquired requisite social skills but who do not consistently
practice or perform those skills in their natural social set-
tings. Using this approach, investigators brought together
elementary-age children with ASD and their TD peers into
a structured activity for which both of the groups indicated
a shared preference. Koegel and colleagues reported a
dramatic increase in positive social initiation and integra-
tion among their sample.
One promising candidate domain for applying this
approach with adolescence is science, and more specifi-
cally robotics. There is a growing body of literature
showing that many individuals with ASD show an interest
in and an aptitude for using technology, and robots in
particular have shown promise for use in the diagnosis and
treatment of ASD (e.g., Dautenhahn and Werry 2004;
Diehl et al. 2012,2014; Feil-Seifer and Mataric
´2009;
Scassellati 2007). Still, many of the interventions involving
technology are designed for younger children, and have yet
to be adapted for the needs and interests of adolescents
with ASD. One particular exception is a study by Wainer
et al. (2010) that used a collaborative robotics class to
increase interactions between individuals with ASD. It is
important to understand whether this type of approach
shows similar promise for interactions between individuals
with ASD and their peers.
Our intervention involved a weeklong summer camp
during which adolescents with ASD and their TD peers
learned to program a humanoid robot while working col-
laboratively in pairs. Based partly on Koegel et al.’s 2012
model of social performance, participants were taught
social/vocational skills and were given supervised oppor-
tunities to practice these skills in an environment in which
they had a shared interest with their peers (i.e., robotics).
We hypothesized that this intervention would lead to a
significant reduction in social anxiety, and an improvement
in social skills performance in individuals with ASD.
Finally, we predicted that every participant, regardless of
their diagnostic status, would acquire increased robotics
knowledge as a result of the intervention.
Methods
Participants
Participants were eight individuals with ASD and eight TD
peers (ages 12–17 years) recruited from the community.
ASD diagnoses were independently confirmed (or for TD
participants, ruled out) using the Autism Diagnostic
Observation Schedule, Second Edition (ADOS-2; Lord
et al. 2012), Social Communication Questionnaire-Life-
time form (SCQ; Rutter et al. 2003), and clinical judgment
using criteria from the Diagnostic and Statistical Manual of
Mental Disorders, 5th Edition (APA 2013). Criteria for
inclusion in the study were: (1) inclusion in general edu-
cation science classes during the academic year (with or
without an aide); (2) an interest in robotics; (3) absence of
an untreated psychiatric disorder or other developmental
J Autism Dev Disord
123
problems not related to ASD, as reported by the parents,
that might interfere with study participation.
A total of 74 applicants indicated an interest in the
program, 32 of whom met inclusion criteria and were
invited for additional screening. These 32 applicants
received a diagnostic (ADOS, SCQ-L), brief cognitive
(Wechsler Abbreviated Scales of Intelligence, Second
Edition; WASI-2; Wechsler 2011), and language (Clinical
Evaluation for Language Fundamentals, Fourth Edition;
CELF-4; Semel et al. 2003) evaluation to facilitate pair-
wise matching. From these 32 individuals, we were able to
pair-wise match eight individuals with ASD with eight TD
peers on chronological age, gender, grade in school, IQ,
and language skills (see Table 1). Females were not
intentionally excluded; however, only two females met the
initial criteria and upon testing, it was determined those
two were not good matches for each other in terms of the
established matching criteria described above; as a result,
the final sample consisted of exclusively male participants.
Participants who were not selected for the camp were given
the opportunity to participate in a 1-day camp (not part of
the study) in which they were given the chance to program
a robot. All participants who completed screening evalua-
tions received a small monetary compensation and their
parents received a written clinical report of their child’s
performance on assessments. Participants who completed
the posttests received additional monetary compensation.
Procedure
Baseline and Posttest Measures
On the first day of the camp, participants and their parents
came in 1 h early for an orientation and baseline data
collection. They came back within a week of the conclu-
sion of the camp for an hour-long post-intervention data
collection. Social anxiety was measured using the self-
report Social Anxiety Scale for Children-Revised (SASC-
R; La Greca and Lopez 1998) or Social Anxiety Scale
Adolescents (SAS-A; La Greca and Stone 1993) depending
on their age. The SAS-A is equivalent to the SASC-R, with
some minor modifications in wording of the survey items
to be more appropriate for adolescents, and they are often
used together (e.g., La Greca and Lopez 1998; Millea et al.
Table 1 Descriptive characteristics of the sample, and baseline scores on dependent variables
Measures ASD (n=8)
M(SD)
TD (n=8)
M(SD)
tp d
Descriptive characteristics
CA 14.05 (1.73) 13.83 (1.45) .27 .79 0.14
WASI-2 106.00 (18.56) 112.00 (10.77) -.79 .44 0.40
CELF-4 97.00 (11.41) 111.88 (6.71) -3.18 .01** 1.59
ADOS-2 13.50 (6.48) 5.75 (3.45) 2.99 .01** 1.49
SCQ-lifetime 17.90 (4.70) 4.00 (3.85) 6.45 \.001** 3.23
Baseline scores
SAS-A/SASC-R: total score 43.38 (9.15) 32.63 (10.43) 2.19 .05* 1.10
FNE 17.13 (3.80) 13.88 (5.08) 1.45 .17 0.74
SAD-New 16.13 (3.80) 12.25 (4.59) 1.84 .09 0.92
SAD-General 10.13 (2.80) 6.50 (1.69) 3.14 .01** 1.57
SSIS: Social Skills Scale 74.13 (16.49) 109.75 (8.71) -5.40 \.001** 2.70
Robotics knowledge quiz .98 (1.40) .40 (.48) 1.12 .28 0.55
Post-test scores
SAS-A/SASC-R: total score 37.38 (6.82) 32.75 (9.35) 1.13 .28 0.57
FNE 14.88 (2.47) 13.75 (5.60) .52 .62 0.26
SAD-New 14.13 (3.04) 12.50 (3.25) 1.03 .32 0.52
SAD-General 8.38 (3.07) 6.50 (1.85) 1.48 .17 0.74
SSIS: Social Skills Scale 79.38 (14.46) 109.25 (11.23) -6.04 \.001** 2.31
Robotics knowledge quiz 7.98 (1.52) 5.15 (1.73)
Robotics knowledge quiz is out of a possible ten points. CA =chronological age; WASI-2 =Wechsler Abbreviated Scale of Intelligence, 2nd
edition; CELF-4 =The Clinical Evaluation for Language Fundamentals-Fourth Edition; ADOS-2 =The Autism Diagnostic Observation
Schedule, Second Edition; SCQ-Lifetime =Social Communication Questionnaire-Lifetime; SASC-R =Social Anxiety Scale for Children-
Revised; SAS-A =Social Anxiety Scale Adolescent; FNE =Fear of Negative Evaluation; SAD-New =Social Avoidance and Distress in New
Situations; SAD-General =Social Avoidance and Distress in General; SSIS =Social Skills Improvement System
*p\.05; ** p\.01
J Autism Dev Disord
123
2013). A score of 50 or greater on the SAS-A/SASC-R
indicates a clinical level of social anxiety, and a score of 36
or less is considered a low level of social anxiety. Social
skills were measured using the parent-report Social Skills
Improvement System (SSIS; Gresham and Elliott 2008).
The SSIS is a standardized norm-referenced assessment of
social skills and competing problem behaviors. The SSIS
yields two scales: The Social Skills scale and Problem
Behaviors scale. In this study, only the Social Skills scale
was considered since the intervention did not target prob-
lem behaviors. Robotics knowledge was measured using a
short factual quiz to test their practical knowledge of robots
and robotics. One-quarter of the quizzes were scored by a
second coder, and the two coders achieved 92.5 % reli-
ability (range =80–100 %).
Intervention
Two consecutive, weeklong camps were offered, with eight
participants (four ASD and four TD) in each camp.
Throughout the camp, camp facilitators were kept naı
¨ve to
participant diagnosis, and the same social/vocational
training was given to all participants regardless of diag-
nosis. Parents and participants were not told that some
participants had an ASD diagnosis. Moreover, we did not
advertise the camp as an intervention targeting individuals
with ASD. When we explained the nature of the camp to
the participants and parents, we told them we would be
teaching robotics knowledge as well as ‘‘career skills
necessary to become a scientist.’’ However, based on the
fact that the camp was held at a lab known in the com-
munity for ASD research, and some participants were
recruited from previous ASD studies, some parents might
have assumed the camp was an ASD intervention.
The intervention lasted 3 h/day for five consecutive
days. The first 4 days had the same daily schedule: during
the first part of the day, students received a group
instruction on robotics and ‘‘career skills’’ (e.g., how to
work collaboratively); during the second part of the day,
students programmed an interactive robot. Participants
worked in pairs (1 ASD : 1 TD) that were pre-assigned to
work as partners for the duration of the summer camp.
Topics each day were interrelated; for example, on day two
of the camp, participants learned to program voice recog-
nition and face tracking, and their ‘‘career skill’’ involved
strategies on how to listen to others and understand them
better. During programming practice, participants had the
opportunity to actively program an interactive robot under
the guidance of two camp facilitators. The camp facilitators
were undergraduate students who had received specific
training in ASD and were closely supervised by the authors
throughout the camp. One facilitator had the role of
teaching and supervising the programming of the robot,
while the other facilitator taught ‘‘career skills,’’ supervised
interactions between pairs, and provided career skills
coaching to pairs when necessary.
On the fourth day of the camp, each pair had to decide
together the topic of the final project on which they would
work collaboratively for the last 2 days. The final project
was to be a culmination of all of the knowledge and skills
they had acquired and honed throughout the camp. The
main rules were that they had to program the robot to be
social (i.e., interact) with the crowd, and they had to
demonstrate each of the programming skills they had
learned. The nature of the projects was such that collabo-
ration and discussion were integral to each participant’s
accomplishing his team’s project. At the conclusion of day
five, a reception was held with family and friends. During
the reception, each team had the opportunity to present
their final project in front of their family and fellow
campers, and the crowd was encouraged to ask questions of
the participants. All 16 participants completed the camp,
including baseline and posttest sessions.
1
Materials
The robot was a NAO platform, a 23-inch tall humanoid
robot from Aldebaran Robotics that is capable of online
text-to-speech communication and 25 degrees of freedom
in movement that allows for human-like social gestures.
This robot was chosen because of its ability to roughly
simulate human movement and because it is publicly
available for purchase. Each participant pair worked on
their own computer and created/programmed movements
using Choregraphe, a programming software developed for
NAO. Once participant pairs created a movement or
sequence, they signed up for a time to test it out on the
NAO, under the supervision of a facilitator.
Results
Social Anxiety
At baseline, the average SAS-A/SASC-R total score was
43.38 (SD =9.15, range =29–60) for the ASD group and
32.63 (SD =10.43, range =19–46) for the TD group.
Only one case from the ASD group and none from the TD
group scored above clinical level of social anxiety. One
case from the ASD group and 50 % of the TD group scored
below the low socially anxious cutoff of 36. The average
score of the ASD group differed significantly from the
average score of the TD sample with a very large effect
1
One participant missed 1 day of camp due to his school’s freshman
orientation.
J Autism Dev Disord
123
size, t(14) =2.19, p\.05; d=1.10. Examining the sub-
scales reveals that the ASD group contrasted most sharply
from the TD group on the SAD-General subscale, which
represents general social inhibition, distress, and discom-
fort, t(14) =2.19, p\.01; d=1.57.
We predicted that the intervention would reduce self-
reported social anxiety in participants with ASD. A series
of paired samples ttest was conducted to compare the
baseline data with post-intervention data on the SAS-A/
SASC-R, separately for the ASD group and the TD group
(see Table 2). As predicted, the ASD group showed a
significant reduction in self-reported social anxiety
between baseline and posttest, t(7) =2.89, p\.05;
d=.74. The posttest mean of 37 is identical to the general
population mean for boys as estimated by La Greca and
Lopez (1998) using this measure and almost reached the
‘‘non-socially anxious’’ cut-off of 36. It should be noted
that seven of the eight participants with ASD reported a
reduction in social anxiety. As expected, the TD group did
not show a reduction in social anxiety, t(7) =-.12,
p=.91; d=.01, which is likely due to the group’s low on
social anxiety baseline scores.
Social Skills
Baseline measurement of the Social Skills Scale of the
SSIS yielded the following scores: ASD group averaged
74.13 (SD =16.49, range =48–98), 1.5 standard devia-
tions lower than the general population mean of 100; the
TD group scored 109.75 (SD =8.71, range =98–122),
consistent with the general population mean. The score of
the ASD group of this sample is almost identical to the
average score of the nationally representative sample of the
ASD population published in the SSIS manual (Gresham
and Elliott 2008): 74.6 (SD =15.9), confirming the rep-
resentativeness of our sample. As expected, the ASD group
showed fewer social skills than their TD peers at baseline
(see Table 1). Consistent with literature on the relationship
between social skills and anxiety, correlational analysis
involving the SSIS and SAS-A/SASC-R measures revealed
that there were very strong relationships between most
dimensions of the participants’ self-reported social anxiety
and their social skills (see Table 3).
We also predicted that the intervention would lead to an
increase in social skills exhibited by the group with ASD.
A series of paired samples t-tests was conducted to com-
pare the baseline data with post-intervention data on the
parent-report SSIS measure, separately for the ASD group
and the TD group (see Table 2). Contrary to our prediction,
there was not a statistically significant increase in social
skills exhibited by the ASD group, t(7) =-1.79, p=.12,
Table 2 Pre-intervention
versus post-intervention data
Robotics knowledge quiz is out
of ten possible points. SASC-
R=Social Anxiety Scale for
Children-Revised; SAS-
A=Social Anxiety Scale
Adolescent; FNE =Fear of
Negative Evaluation; SAD-
New =Social Avoidance and
Distress in New Situations;
SAD-General =Social
Avoidance and Distress in
General; SSIS =Social Skills
Improvement System
*p\.05; ** p\.01
Measures Pre-intervention
M (SD)
Post-intervention
M (SD)
tp d
ASD group (N =8)
SAS-A/SASC-R: total score 43.38 (9.15) 37.38 (6.82) 2.89 .02* .74
FNE 17.13 (3.80) 14.88 (2.47) 2.83 .03* .70
SAD-New 16.13 (3.80) 14.13 (3.04) 2.37 .05* .28
SAD-General 10.13 (2.80) 8.38 (3.07) 1.70 .13 .29
SSIS: Social Skills Scale 74.13 (16.49) 79.38 (14.46) -1.79 .12 .17
Robotics knowledge quiz 2.17 (1.52) 7.98 (1.52) -13.03 \.001** 2.73
TD group (N =8)
SAS-A/SASC-R: total score 32.63 (10.43) 32.75 (9.35) -.12 .91 .01
FNE 13.88 (5.08) 13.75 (5.60) .36 .73 .02
SAD-New 12.25 (4.59) 12.50 (3.25) -.32 .76 .06
SAD-General 6.50 (1.69) 6.50 (1.85) .00 1.0 .00
SSIS: Social Skills Scale 109.75 (8.71) 109.25 (11.23) .20 .85 .05
Robotics knowledge quiz 1.42 (1.30) 5.15 (1.73) -7.16 \.001** 2.47
Table 3 Bivariate correlations among variables measured at pre-
intervention
SISS
SS
SISS
PB
SAS-
total
SAS-
FNE
SAS-
new
SAS-
general
SISS SS –
SISS PB -.94* –
SAS total -.55* .60* –
SAS-FNE -.40 .47 .91** –
SAS-NEW -.54* .57* .91** .70** –
SAS-general -.59* .62** .90** .75** .76** –
*p\.05; ** p\.01
J Autism Dev Disord
123
d=.17, even though six of the eight participants showed
an increase in their overall SSIS score. As expected, the TD
group, which was functioning in the typical range of social
skills at the beginning of the study, showed no difference
between baseline and posttest, t(7) =.20, p=.85;
d=.05.
Knowledge of Robots and Robotics
All 16 participants experienced a significant improvement
on the measure of their knowledge of robots and robotics
that we developed specifically for this study (see Table 2).
When comparing the ASD group with the TD group, there
was no statistical group difference in the baseline level of
knowledge or the amount of improvements the participants
made from pre- to post-intervention.
Discussion
The results of this study provide preliminary support for
the effectiveness of a summer robotics camp at reducing
self-reported social anxiety in highly verbal adolescents
with ASD and increasing knowledge of robotics in both
individuals with ASD and their TD peers. In fact, self-
reported anxiety in participants was reduced to levels
equivalent to the population mean reported by La Greca
and Lopez (1998). By placing the focus of the program on
the strengths rather than deficits of the participants with
ASD and by providing an intrinsic shared interest, the
intervention did not necessitate disclosing the ASD diag-
nosis to the TD peers nor risk creating a power imbalance
within the pairs. Concurrently, this approach offers inher-
ent benefits to both individuals with ASD and TD peers and
creates a natural motivation for them to participate, leading
to a comfortable social and collaborative context in which
all adolescents involved could learn and practice good
social/vocational skills. We did not find a statistically
significant improvement in social skills, although the small
sample size and the choice of measure (parent report, rather
than real-time behavioral measures) might have contrib-
uted to the absence of an effect in this area.
This pilot study did not specifically examine whether the
use of a ‘‘robotics’’ camp was better than other types of
camps (e.g., music, art, math); however, there are reasons
to believe the use of robots may have unique advantages
for this population. First, individuals with ASD are often
drawn to technology (see Dautenhahn and Werry 2004;
Diehl et al. 2012,2014; Feil-Seifer and Mataric
´2009;
Scassellati 2007, for reviews), which creates a natural and
powerful motivation for many adolescents with ASD to
seek participation in interventions such as this one. Second,
programming robots to carry out behaviors or
conversations makes one more aware of the function and
effectiveness behind the gestures and words used in natural
interactions. For example, in order to program a robot to
tell a joke, participants in this study had to think about
pragmatics of language, eye contact, gestures, when to
pause, and when to follow up with a question. Still, future
studies should examine whether the effects that were seen
in this study were specifically driven by a mutual interest in
robotics, or whether the improvement is related to the
broader issue of having a shared interest with a peer.
The results reported here should be interpreted with
caution due to several limitations inherent to pilot studies.
This study had a small sample, which limited our ability to
detect small to medium effect sizes and limited the number
of covariates we could test. Furthermore, because the post-
intervention evaluation took place immediately following
the intervention, one cannot make any assumptions about
possible long-term effects of the program. A longitudinal
study design would allow one to evaluate the long-term
benefits of this program on important measures of success,
such as community integration and postsecondary educa-
tional and vocational outcome. It is also important to note
that our data were based on self-report and parent-report
measures only. Direct observation of the participants dur-
ing their interactions with peers is needed to specifically
examine the real-time social performance beyond parent-
report measures of social skills in order to determine if
there are quantifiable improvements in social performance.
For example, the SSIS is designed to measure both social
skills acquisition and social performance, but it is not
designed to differentiate between improvements in one
area or the other. Thus, subtle improvements in social
performance might have been missed with this measure.
Measurement of symptom change in this population is a
serious challenge (see Bolte and Diehl 2013), and
employing varied data collection methods should minimize
the possible problem of inflated associations between the
variables under study that can arise from a shared method
variance. Therefore, future research should focus on rep-
licating the results of this pilot study with a larger and more
heterogeneous sample, providing more intensive and/or
longer period of intervention, and employing a longitudinal
study design with a wide range of data collection methods.
The present study offers at least two practical benefits
and implications. First, an intervention that does not dis-
close ASD diagnosis to TD peers is not only possible (e.g.,
Koegel et al. 2012), but desirable. Any intervention tar-
geted toward adolescents should be sensitive to the fact that
this is an age when social acceptance is crucial. In fact, a
number of participant pairs were seen informally
exchanging phone numbers at the end of the study. Second,
the reductions in social anxiety experienced by the par-
ticipants with ASD in this study emphasize the importance
J Autism Dev Disord
123
of developing interventions targeted to helping this vul-
nerable, yet often neglected, population. Given the prom-
ising results from this pilot study, we believe that this
approach warrants further study in adolescents with ASD,
with a larger, more diverse sample, and using multiple
levels of analysis of behavioral change.
Acknowledgments The study was supported in part by the Institute
for Scholarship in the Liberal Arts, the Career Center, and the Glynn
Family Honors programat the University of Notre Dame. We would like
to thank Heidi Miller, B. S. W., for overseeing many crucial tasks
involved in recruitment of participants and data entry. We would also
like to thank the following research assistants who conscientiously
carried out a wide range of tasks at various stages of the project: Tara
Crown, Catherine Grace Connolly, Theresa Gorman, Kailey Kawalec,
Whitney McWherter, Megan Sullivan, Haley Van Steenwyk, Michelle
Won, and Julaine Zenk. We would like to thank the children and families
who have contributed their time to this research.
Conflict of interest The authors declare that they have no conflict
of interest, and received no monetary compensation or had any
affiliation with robotics companies as part of this study.
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