Brief Report: Above and Beyond Safety: Psychosocial and Biobehavioral Impact of Autism-Assistance Dogs on Autistic Children and their Families

Abstract

Autism-Assistance Dogs (AADs) are highly-skilled service animals trained primarily to ensure the safety of an autistic child by preventing elopement and mitigating ‘meltdowns’. Although anecdotal accounts and case-studies have indicated that AADs confer benefits above and beyond safety, empirical support anchored in validated clinical, behavioral, and physiological measures is lacking. To address this gap, we studied children and their families before and after receiving a well-trained AAD using a within-subject, repeated-measures design. Notably, this study is the first to assess change in a biomarker for chronic stress in both autistic children and their parents. Final analyses included pre-/post-AAD data from 11 triads (parent/handler-dog-child) demonstrating significantly positive psychosocial and biobehavioral effects of AADs.

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Vol.:(0123456789)
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Journal of Autism and Developmental Disorders
https://doi.org/10.1007/s10803-021-05410-0
BRIEF REPORT
Brief Report: Above andBeyond Safety: Psychosocial
andBiobehavioral Impact ofAutism‑Assistance Dogs onAutistic
Children andtheir Families
AngelaTseng1
Accepted: 14 December 2021
© The Author(s) 2022
Abstract
Autism-Assistance Dogs (AADs) are highly-skilled service animals trained primarily to ensure the safety of an autistic child
by preventing elopement and mitigating ‘meltdowns’. Although anecdotal accounts and case-studies haveindicated that
AADs confer benefits above and beyond safety, empirical support anchored in validated clinical, behavioral, and physiologi-
cal measures is lacking. To address this gap, we studied children and their families before and after receiving a well-trained
AAD using a within-subject, repeated-measures design. Notably, this study is the first to assess change in a biomarker for
chronic stress in both autistic children and their parents. Final analyses included pre-/post-AAD data from 11 triads (parent/
handler-dog-child) demonstrating significantly positive psychosocial and biobehavioral effects of AADs.
Keywords Autism-assistance dogs· Canine assistance· Service dogs· Psychosocial effects· Chronic cortisol
concentration· Parent/child stress
Introduction
Autism spectrum disorder (ASD), a heterogeneous neu-
rodevelopmental disorder (NDD) comprising lifelong chal-
lenges in social, communication, and behavioral domains,
has reached an unprecedented prevalence estimate of 1-in-
54 in the United States (Maenner etal., 2020). Frequently,
treatment plans not only need to address core ASD symp-
toms, but also a variety of co-occurring developmental,
psychiatric, neurologic, or medical diagnoses that further
impact daily functioning and quality of life (Masi etal.,
2017). One approach with the potential to address a number
of concerns for autistic individuals and their families is the
incorporation of animal-assisted interventions (AAIs)1 into
home, school, and hospital settings (Dimolareva & Dunn,
2020; Esposito etal., 2011; Johnson etal., 2002); several
studies have reported positive effects when human-animal
interactions (HAI) have been integrated into ASD therapies
(Dimolareva & Dunn, 2020; Droboniku & Mychailyszyn,
2021; Funahashi etal., 2014; OHaire etal., 2013). Anec-
dotal accounts have also accrued attesting to the benefits
of well-trained autism-assistance dogs (AADs) who engage
with their human partners on a daily basis. Yet, despite
rising interest in the field, the evidence-base for AAIs for
ASD remains limited—due, in large part, to considerable
variability in research methodologies, implementation, and
reporting (Kazdin, 2017; O’Haire, 2013, 2017). Even sparser
still are systematic evaluations of whether and how well-
trained AADs can impact the lives of autistic children and
their families (Butterly etal., 2013).
The primary trained duties of an AAD stemmed from a
critical need to prevent child elopement; a foremost con-
cern for many parents of autistic children is that their child
may bolt or wander and “expose him or herself to potential
danger by leaving a supervised, safe space or the care of
a responsible person” (Anderson etal., 2012). One study
collected data on missing person cases in the US involving
elopement by individuals with ASD across a 5-year period
(2011–2016) and reported that, of the 808 cases evaluated,
17% resulted in death, 13% required medical attention, 38%
carried a heightened risk of bodily harm (i.e., “close calls),
* Angela Tseng
atseng@umn.edu
1 Department ofPsychiatry & Behavioral Sciences,
University ofMinnesota, 717 Delaware St. SE, Minneapolis,
MN55414, USA
1 For the sake of clarity, the term “animal(s)” will be used to signify
“non-human animal(s)” throughout the manuscript.

Journal of Autism and Developmental Disorders
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and 1% were still considered missing (McIlwain & Fournier,
2017). Trained AAD teams increase a child’s safety by
working as a triad; in public, the child may wear a specially
designed belt that connects to the dog’s vest while an adult
handler holds the dog’s leash. AADs are taught to resist
passively with their body weight if their child attempts to
bolt and the tethering system keeps the child with their dog.
Caregiver and case study reports have related that AADs
can prevent elopement effectively while providing a sense of
security for both parents and children (Burgoyne etal., 2014;
Burrows etal., 2008). In fact, this trained ability to prevent
a child with autism from wandering away confers ‘service
animal’ status to AADs, defined by the US Department of
Justice as a dog that is individually trained to do work or per-
form tasks directly related to a person’s disability. Service
dogs are permitted to accompany people with disabilities
in all areas where members of the public are allowed to go
(ADA, 2010).
Another troubling issue affecting families of autistic chil-
dren is the health and well-being of parents/caregivers who
report experiencing higher physiological stress, parenting-
related stress, and fatigue than parents of typically-devel-
oping (TD) children and children with other NDDs (Baker-
Ericzén etal., 2016; Estes etal., 2013; Fecteau etal., 2017;
Smith etal., 2009); these experiences may increase parental
risk for mental (e.g., anxiety, depression) and physical health
(e.g., adrenal, cardiovascular) problems (Foody etal., 2014;
Seymour etal., 2012). Myriad factors including child char-
acteristics and behavioral challenges (Olson etal., 2021),
as well as sociocultural and economic circumstances (e.g.,
access to resources, stigma associated with mental health,
financial burden of care), can compound to distress parents
and affect both child and overall family outcomes by means
of transactional pathways (Bonis, 2016; Iadarola etal., 2019;
Rodriguez etal., 2019).
Encouragingly, reports of collateral benefits have emerged
from families with AADs trained chiefly for safety. One
seminal study noted that the contribution of service dogs to
family outcomes extended beyond physical welfare to behav-
ioral and psychosocial domains; parents reported that they
experienced improved quality of sleep and a greater sense of
independence while their children exhibited fewer negative
behaviors (e.g., “meltdowns”, “tantrums”, “bolting”) and
families overall experienced an increase in social acknowl-
edgement and a decrease in embarrassment or shame in
public (Burrows etal., 2008). AADs have also been trained
to disrupt potentially harmful repetitive or self-stimulating
behaviors as well as provide a modified form of pressure
touch therapy practiced by occupational therapists to help
autistic individuals reduce levels of arousal and anxiety
(Bestbier & Williams, 2017; Grandin, 1992; Krauss, 1987).
Further, because simple language is used to work with
AADS, children may gain rewarding interactive experiences
that then scaffold socialization with other humans (Solomon,
2010). Broadly, these dogs may serve as social catalysts
for their human partners by enhancing social interactions,
increasing social networks, and reducing instances of social
discrimination (Becker etal., 2017; Camp, 2001; Carlisle,
2015; Mader etal., 1989; McNicholas & Collis, 2000).
Yet, while the positive, multidimensional impact of these
AADs has been oft reported in anecdotal accounts and case
studies, empirical research substantiating these gains is
limited. Moreover, documentation is sparse specifying how
service dog providers collect outcome data when evaluat-
ing the success of their canine placements (Butterly etal.,
2013). In order to strengthen the evidence-base for this field,
systematic pre-/post-AAD assessments employing validated
instruments are warranted. Also, although a handful of stud-
ies have been published on the effects of assistance dogs
on human psychosocial health and well-being (See Rod-
riguez etal., 2020 for review), few have focused on dogs
trained expressly for ASD.Whereas mostadult handler-dog
teams (e.g., mobility, seeing, hearing, diabetes)are dyadic,
to evaluate the benefits of AADs, we must consider the
unique dynamics of the handler-dog-child triad in conjunc-
tion withthe vast heterogeneity of ASD diagnoses which
are often comorbid with other NDDs. Finally, the use of
biological measures when possible may provide key objec-
tive insights into the long-term effects of having an AAD.
To date, however, few studies have included a biomarker
measure in their evaluations of AAD success. A review of
the extant literature revealed only two such investigations
that measured changes in cortisol (salivary), the primary
glucocorticoid produced by the activation of the hypotha-
lamic pituitary adrenal (HPA) axis in response to a stressor.
Specifically, both studies examined the cortisol awakening
response (CAR), a core biomarker of HPA axis regulation
related to psychosocial stress and stress-related psychiatric
disorders (Fries etal., 2009), and reported decreases of CAR
for both parents and children after they receiving trained
service dogs (Fecteau etal., 2017; Viau etal., 2010).
The overarching objective of the present study has been
to investigate empirically the impact of AADs by collecting
psychosocial and biobehavioral data by means of validated
instruments designed to betterunderstand the functioning of
children and families affected by ASD. In addition to assess-
ment data collected via parent-report (child) and self-report
(parent), we included a biological measure of chronic stress
in both parents and children to augment our understanding of
how AADs may affect physiological health. Chronic cortisol
concentrations (CCC) assayed from a single collection of a
keratinized matrix (e.g., hair/nails) sample have been shown
to represent an accumulation of cortisol secretions over a
time frame of months (Meyer & Novak, 2012; Phillips etal.,
2021). In contrast, cortisol samples collected from saliva
or urine are limited in time (< a few days) and can require

Journal of Autism and Developmental Disorders
1 3
repeated measurements across 24-hours over several days to
obtain average chronic concentrations (Wosuet al., 2013).
Comparative studies examining the correspondence of CCC
obtained from scalp-near hair segments to 30-day (3 × daily)
average salivary cortisol area-under-the curve levels demon-
strated strong associations between CCC and prior 30-day
integrated cortisol production measures (Fries etal., 2009;
Short etal., 2016). Thus, the use of CCC can also reduce
the burden of data collection for participants, particularly
vulnerable populations, in addition to providing a gauge of
chronic stress retrospectively.
To our knowledge, the present study is among the first to
assess CCC in autistic children and the only investigation
to examine CCC in both parents and children with ASD.
Additionally, no previous reports of the effects of AAD have
incorporated CCC measures. Critically, we collected data
both before and after participants received their dogs so that
we would be able to evaluate outcomes within-subjects.
Our study objectives were thus to contribute both quantita-
tive and qualitative data from well-validated instruments to
address the question of whether children and their families
benefit from these human-canine partnerships across mul-
tiple domains.
Method
All study procedures were approved by the University of
Minnesota’sInstitutional Review Board and all parents
completed informed consent procedures. Participants were
informed that their decision to participate would have no
bearing on their current or future relationships with the uni-
versityor the canine training program.
Participants
Using non-probability, purposive sampling, we recruited
families from the top of a regional assistance dogtrain-
ing program’s(Can Do Canines, New Hope, MN, USA)
3–5-year-long waiting list of applications to receive an AAD.
Can Do Canines
Can Do Canines (https:// cando canin es. org/) is an interna-
tionally recognized, Assistance Dogs International (ADI)
accredited, nonprofit organization that trains assistance dogs
for hearing loss, mobility challenges, seizure disorders, Type
1 Diabetes, as well as ASD in children. Families are pro-
vided with the dogs free-of-charge and the economic bur-
den and time-investment for each certified handler/dog team,
combined with the assiduous training and placement stand-
ards enforced by the organization, limits severely the num-
ber of dogs placed each year. Clients of the assistance dog
provider receive AADs whose temperaments/talents were
carefully matched to families by highly-experienced train-
ers. Trainers are able select for certain characteristics (e.g.,
hypoallergenic breeds) and tailor final training to meet the
needs of individual families. To apply for an AAD, children
(Ages: 2–7years when applying) must have a confirmed
ASD diagnosis, live within the state, and families must be
physically and financially able to take full responsibility for
the dog after certification (See Fig.1 for Study Flow Dia-
gram). An age restriction was established to accommodate
the lengthy waitlist and the fact that size must be considered
if dogs will be trained to prevent child elopement. By the
time they are ready for final training, potential AADs may
have already had more than 18months of socialization, gen-
eral training, assessments, and intensive training specific to
their assistance dog careers. Once the match is made, one
caregiver undergoes training to become the primary dog
handler and works with trainers and the AAD without their
child present. When they are ready to have the dog move
into the home, trainers then work with the triad (handler-
dog-child) together to build their partnerships and skills
in everyday life. These AAD teams require approximately
8–12weeks to complete team training and certification.
Participant Characteristics
Since our potential participant pool was limited to the fami-
lies who would be receiving an AAD during our period of
data collection, our only criteria for inclusion beyond those
of the training program were that parents/caregivers be able
to provide informed consent and complete questionnaires
in English. In total, we enrolled 13 families to participate in
the study. Final analyses included data from 11 teams; we
were unable to collect post-AAD data from one family and
one team experienced a change in family circumstances and
had to return their dog. Mean AAD age was 2.9 ± 0.5years
when matched with a family, 45.5% were females, and
mean weight was 62.2 ± 7.1 pounds. With the exception of
one Standard Poodle, all AADs were Labrador Retrievers,
Golden Retrievers, or Labrador/Golden crosses. The desig-
nated adult dog handler was the primary parent participant;
100% were mothers, 27% families identified as single-parent
households. Secondary parent/caregiver data were collected
when possible but were insufficiently powered for further
analysis. Formal diagnosis of ASD was confirmed through
parent-provided records by the assistance dog organization
while additional medical history, including diagnoses of
co-occurring neurodevelopmental conditions, was collected
via parent-report. All children had a confirmed diagnosis of
ASD and 45.5% were non-verbal. Detailed parent and child
characteristics are reported in Table1.

Journal of Autism and Developmental Disorders
1 3
Given that we would not be able to control for hetero-
geneity in family characteristics and child medical his-
tory and treatment, we implemented a repeated measures
design that would allow us to examine changes over time
within each family. We did, however, ask parents to report
ongoing treatments at each assessment and no significant
changes in ASD-related treatments between pre-/post-
AAD measures were recorded; 36.3% were receiving
therapy (e.g., occupational, speech and language, physi-
cal, applied behavioral analysis,), 45.5% were receiv-
ing therapy and medications, and 18.1% were receiving
therapy and “other” treatments (e.g., assistive technology,
adaptive sports). We should also note that one common
factor amongst the families who chose to remain on the
3–5-year long waitlist for an AAD is a willingness and
commitment to bringing an AAD into their lives and the
belief that an AAD might be beneficial. Further, fami-
lies would not likely apply for an assistance dog if their
child had known sensory aversions to canines (Grandin
etal., 2010) that would preclude meaningful interaction.
Applicants were able to make special requests for hypoal-
lergenic breeds but those limitations could lengthen wait-
times substantially.
Fig. 1 Study-flow diagram

Journal of Autism and Developmental Disorders
1 3
Study Design
Our assessment battery consisted of parent-report (child)
and self-report (parent) questionnaires as well as CCC
sample (parent and child) collection. We asked partici-
pants to complete pre-AAD (T1) measures after being
taken off the waitlist and before receiving their dogs. A
follow up assessment (post-AAD; T2) was administered
8–12weeks after teams were certified. Participants were
given the option of completing measures remotely or in-
person. Paper questionnaires and consent forms were con-
verted to REDCap (Research Electronic Data Capture),
a secure, web-based software platform designed to sup-
port data capture for research studies (Harris etal., 2009,
2019). Participants were also given the option to have the
researcher collect hair/nail samples in-person or self-col-
lect at home and submit to our laboratory by mail.
Two post-intervention time points were included in the
original study design. However, due to institutional research
and canine training facility restrictions during the COVID-
19 pandemic, we were unable to complete all planned data
collection. Moreover, we were concerned that results might
be confounded bythe considerable stress and changes in rou-
tine brought on by the pandemic alongside concurrentcivil
unrest in our regional community. Consequently, we lim-
ited our final data set to teams who completed both of their
pre-and post-AAD assessments either before (N = 7) or after
Spring 2020 (N = 4). In other words, although we contin-
ued to collect follow-up data remotely when possible, we
decided to only include data in our final analysis if families
completed T2 before March 2020 or if they enrolled after
Spring 2020. Ultimately, because the training facility was
also required to shut down for a period of time, we did not
enroll the next new participant family until October 2020.
While participants had been given the option to complete
procedures remotely/online before pandemic restrictions
were put in place, the latter group of participants were
offered the remote/online option only. We report herein on
data collected from families before receiving their AAD and
8–12weeks following team certification.
Table 1 Participant
Characteristics
a Confirmed ASD diagnosis required to apply for AAD
A. Child B. Parent (AAD handler)
Age (years) Age (years)
Mean 9.1 Mean 41.3
SD 1.5 SD 4.6
Sex (%) Sex (%)
Female 16.7 Female 100.0
Ethnicity (%) Ethnicity (%)
Hispanic/Latino 9.1 Hispanic/Latino 9.1
Race (%) Race (%)
American Indian/Alaska native 9.1 American Indian/Alaska native 0.0
Asian 9.1 Asian 0.0
Black/African American 9.1 Black/African American 9.1
White/Caucasian 81.8 White/Caucasian 81.8
Other/more than one race 18.2 Other/More than One Race 9.1
Neurodevelopmental disorders (%) Highest level of education (%)
Anxiety 90.9 Did not graduate from high school 9.1
Attention-deficit/hyperactivity 36.4 Some college 27.3
Autism spectrum 100.0aCollege graduate 36.4
Conduct 27.3 Graduate degree(s) 27.3
Global developmental delay 27.3 Annual household income (%)
Intellectual disability 63.6 $31,000–$40,000 18.2
Motor 18.2 $41,000–$50,000 0.0
Obsessive–compulsive 18.2 $51,000–$60,000 9.1
Seizure 27.3 $61,000–$70,000 18.2
Sleep 72.7 $71,000–$80,000 9.1
Speech and language 45.5 $81,000–$90,000 9.1
$91,000 + 36.4

Journal of Autism and Developmental Disorders
1 3
Behavioral/Psychosocial Measures
Behavioral features of children were assessed by having
parents complete a pre-/post-AAD battery of question-
naires (see Table2 for descriptions) including the Social
Responsiveness Scale—2nd Edition (SRS-2) (Constantino
& Gruber, 2012), the Child Behavior Checklist (CBCL)
(Achenbach & Rescorla, 2001), and the Autism Spectrum
Quotient—Child (AQ-Child) (Baron-Cohen etal., 2001).
In order to gather information about parent/family experi-
ences and concerns, parents also completed the Autism
Parenting Stress Index (APSI) (Silva & Schalock, 2012),
State-Trait Anxiety Inventory (STAI) (Spielberger, 1989),
the Autism Family Experience Questionnaire (AFEQ)
(Leadbitter etal., 2018), and the Perceived Stress Scale
(PSS) (Cohen etal., 1983). At the second time point, we
also asked parents for canine signalment and to respond
briefly to some open-ended questions about the AAD’s
integration into their household.
Biological Measures
To explore AAD impact using a biological measure of
chronic stress, we collected samples of scalp hair (posterior
vertex) or nail clippings from parents and children for corti-
sol extraction and analysis by enzyme immunoassay (Cooper
etal., 2012; Meyer & Novak, 2012). Although we planned to
measure hair cortisol concentration (HCC) only originally,
hair collection from some of our initial participants proved
to be prohibitively difficult and/or not possible due to lack
of scalp hair. Subsequently, participants were also given the
option to submit fingernail clippings (Phillips etal., 2021)
as an alternative method (Liu & Doan, 2019). Participants
provided the same (hair or nail) samples for their pre- and
Table 2 Parent (self-report) and child (parent-report) measures
AFEQ (Leadbitter etal., 2018); APSI (Silva & Schalock, 2012); PSS (Cohenet al., 1983); STAI (Spielberger, 1989); AQ-Child (Baron-Cohen
etal., 2001); CBCL (Achenbach etal., 2001); SRS-2 (Constantino & Gruber, 2012)
Name Description Retest Reliability Time (minutes)
Parent (Self-report)
Demographics form Includes questions about household composition,
socio-economic status, family medical history
including neurodevelopmental disorders
~ ~ 10–15
Autism Family Experience Questionnaire (AFEQ) 48-item questionnaire that assesses family quality
of life, includes 4 domains: experience of being a
parent; family life; child development and social
relationships; child's feelings and behavior
0.83 10
Autism Parenting Stress Index (APSI) 13 items grouped into 3 categories (core social dis-
ability, difficult-to-manage behavior, and physical
issue) designed to measure aspects specific to
families of children with an ASD diagnosis
0.88 5
PerceivedStress Scale (PSS) 10-item instrument that measures degree to which
situations in one’s life are appraised as stressful.
Items query how unpredictable, uncontrollable, and
overloaded respondents find their lives
0.85 5
State-Trait Anxiety Inventory (STAI) 40-item instrument designed to assess levels of state
anxiety and trait anxiety; state anxiety defined as a
transient momentary emotional status that results
from situational stress while trait anxiety represents
a predisposition to react with anxiety in stressful
situations
0.69–0.89 5
Child (parent-report)
Autism Spectrum Quotient- children’s version (AQ-
Child)
50-item parent-report questionnaire designed to
measure autism trait severity (4–11years old)
0.85 10
Child Behavior Checklist/6–18 (CBCL) 113-item questionnaire addressing child’s competen-
cies and problem behaviors, including internalizing
and externalizing behaviors
0.80–0.94 15–20
Social Responsiveness Scale, second edition (SRS-2) 65-item rating scale measuring deficits in social
behavior associated with ASD, total score reflects
social deficit severity with five treatment subscale
scores (Social Awareness, Social Cognition, Social
Communication, Social Motivation, Restricted
Interests & Repetitive Behavior)
0.88–0.95 10–15

Journal of Autism and Developmental Disorders
1 3
post-AAD measures. Parents were also asked to complete a
questionnaire for each hair or nail sample to capture data on
hair care and medication use that may affect cortisol assay
results (Doan etal., 2018; Hamel etal., 2011). Ultimately,
we had to limit our final analysis to the subset of participants
from whom we received both pre-/post-AAD samples (Par-
ent, N = 6; Child, N = 5); inclusion/collection of complete
datasets was hindered by difficulty with collection, low sam-
ple weight, and the presence of steroid medications that may
have inflated final concentrations.
Data Analysis
Using SPSS 25.0 (Statistical Package for Social Sciences,
Version 25) we conducted Shapiro–Wilk tests to assess data
for normality and Wilcoxon signed-rank tests to assess pre-/
post-AAD changes. Both full scale and subscale scores were
included when applicable. We used raw scores rather than
t-scores for the CBCL and SRS-2 because, at the high end
of the distribution, raw scores may be more precise than
t-scores (Achenbach & Rescorla, 2001; Constantino &
Gruber, 2012). Significance levels were set at alpha = 0.05
(two-tailed). We also examined associations between parent
and child data on change in stress and cortisol levels using
Pearson correlations.
Chronic Cortisol Concentration
We collected 20–50mg of scalp hair from the posterior ver-
tex region and stored samples at room temperature in dry
and dark conditions (Cooper etal., 2012); hair was then wet-
ted with isopropanol, minced into 2mm pieces, and washed
four times with 0.5mL of isopropanol at room temperature
for 30s to remove external contamination. For fingernail
samples, clippings were collected from all ten fingers and
then stored and processed using an analogous protocol.
Samples were dried under a nitrogen stream and weighed.
Cortisol was extracted with 1mL of methanol overnight at
55°C, 1mL acetone for 5min, and then 1mL of methanol
overnight at 55°C one more time (Slominski etal., 2015).
Pooled solvent fractions were removed under a nitrogen
stream. 1mL of acetone was added and evaporated under a
nitrogen stream to chase off the solvents' remnants. Samples
were then dissolved in in an assay diluent, randomly distrib-
uted on different plates to avoid a batch effect, and analyzed
in duplicate using Salimetrics cortisol enzyme-linked immu-
nosorbent assay (ELISA) (Miller etal., 2013). If readings
for a sample differed by more than 10% or if readings were
too high due to high concentration, the measurements were
repeated; also, 5% of samples were randomly reanalyzed to
ensure reproducibility.
Results
Using within-subjects contrasts, we compared measures col-
lected before families received their AAD (T1) and after they
had time to complete training and integrate the AAD into their
daily lives (T2). Overall, we found significant, positive changes
over time for parent, child, and family measures. Complete
results are reported in Table3 and Figs.2, 3, 4.
Given the small size of our sample, we employed Shap-
iro–Wilk tests to assess normality and found that, overall,
our data were not normally distributed. Hence, we opted
to use non-parametric tests to compare pre- and post-AAD
measures. Specifically, Wilcoxon signed-rank tests revealed
reductions in levels of experienced and perceived stress on
the: PSS, Z = − 2.361, p = 0.018; APSI, Z = -2.255, p = 0.024;
STAI (State), Z = − 2.045, p = 0.041; STAI (Trait), Z = − 2.398,
p = 0.016; and the AFEQ (Total Score) Z = − 2.936, p = 0.003.
We also found significant improvements in parent-reports
of child behavior and ASD symptomatology: AQ-Child,
Z = − 2.503, p = 0.012; CBCL (Total Problems), Z = − 2.603,
p = 0.009; SRS-2 (Total), Z = − 2.003, p < 0.045.
We also analyzed CCC levels for both parents and children
in the subset of participants who provided both pre- and post-
AAD hair/nail samples using Wilcoxon signed-rank tests and
found that CCC levels were lower at T2 than at T1 in Parents,
F(1,5) = 20.852, p = 0.006 and Children, F(1,4) = 30.600,
p = 0.005. Inter-plate variability was 2.2% and high, median,
low values for final cortisol concentration (%RSD) were
20.35pg/mg (5.87), 6.85 pg/mg (1.77), and 2.54 pg/mg
(0.265), respectively.
For the parent and child dyads with complete cortisol data,
we detected a correlation in concentration change (T1-T2) sig-
nificant at the 0.05 level (1-tailed), r(0.822), p = 0.044 indicat-
ing a reduction in cortisol levels for both parents and children.
We also found a significant correlation (1-tailed) for T1-T2
parental cortisol levels and parental PSS scores, r (0.814),
p = 0.047, indicating that reductions in chronic cortisol levels
corresponded with reductions in parent perceived stress levels.
Also, T1-T2 child cortisol levels were even slightly more cor-
related (1-tailed) with T1-T2 parental PSS scores, r (0.852),
p = 0.034.
Finally, we asked parents to describe briefly their child’s
relationship with their AAD. While we did not collect enough
text to conduct thematic analysis, comments were notably
positive and highlighted individual differences in each team.
Some examples of parental observations are included below.

Journal of Autism and Developmental Disorders
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Table 3 Pre-/Post-AAD results
Pre-AAD (T1) Post-AAD (T2) ZarAsymp. Sig.
(2-tailed)
Exact Sig. (2-tailed)
Mean SD Median Mean SD Median
A. Parent (self-report) and child (parent-report) measures
Parent
AFEQ (N = 11)
Child development, understanding, social relationships 50.82 6.76 27.00 44.55 4.72 22.00 − 2.675 0.807 0.007** 0.005**
Child symptoms (feelings and behavior) 35.91 3.05 60.00 34.55 3.27 58.00 − 2.952 0.890 0.003** 0.001**
Experience of being a parent of a child with autism 33.91 3.70 33.00 31.91 3.75 32.00 − 1.636 0.493 0.102 0.109
Family life 27.64 3.32 25.00 24.36 4.20 21.00 − 2.398 0.723 0.016* 0.014**
AFEQ total 148.27 9.55 149.00 135.36 10.11 132.00 − 2.936 0.885 0.003** 0.001**
APSI (N = 10b) 21.80 5.81 24.00 17.40 4.33 16.50 − 2.255 0.713 0.024* 0.023*
PSS (N = 11) 21.45 6.96 23.00 17.55 5.43 16.00 − 2.361 0.712 0.018* 0.016*
STAI (N = 11)
State anxiety 46.36 13.57 48.00 40.64 9.79 40.00 − 2.045 0.617 0.041* 0.043*
Trait anxiety 49.64 12.18 54.00 44.45 10.29 46.00 − 2.398 0.723 0.016* 0.014**
Child
AQ-child (N = 11) 50.91 13.97 54.00 45.55 13.19 51.00 − 2.503 0.755 0.012** 0.012**
CBCL (N = 11)
Anxious/Depressed subscale 6.00 4.47 6.00 3.82 3.19 4.00 − 2.273 0.685 0.023* 0.023*
Withdrawn/Depressed subscale 3.91 0.94 4.00 3.64 1.43 4.00 − 0.796 0.240 0.426 0.410
Somatic Complaints subscale 3.18 3.46 1.00 2.27 2.65 1.00 − 1.613 0.486 0.107 0.172
Social problems 6.64 3.01 7.00 5.09 2.39 5.00 − 2.582 0.779 0.010** 0.010**
Thought problems 9.64 2.66 9.00 9.18 2.68 9.00 − 0.621 0.187 0.535 0.580
Attention problems 12.73 3.04 12.00 11.27 3.13 11.00 − 2.676 0.807 0.007** 0.007**
Rule-breaking behavior 2.64 1.91 2.00 2.18 1.40 2.00 − 0.741 0.223 0.458 0.547
Aggressive behavior 12.00 5.31 12.00 7.82 4.00 6.00 − 2.454 0.740 0.014** 0.012**
Internalizing problems 13.09 7.08 12.00 9.73 5.31 8.00 − 2.680 0.808 0.007** 0.004**
Externalizing problems 14.64 6.83 14.00 10.00 4.94 9.00 − 2.315 0.698 0.021* 0.019*
CBCL Total problems 27.73 12.62 26.00 19.73 9.11 21.00 − 2.603 0.785 0.009** 0.006**
SRS-2 (N = 11)
Social awareness 15.73 2.80 16.00 15.45 2.84 16.00 − 0.051 0.015 0.959 1.000
Social cognition 22.73 3.50 23.00 20.45 3.47 21.00 − 2.149 0.648 0.032* 0.035*
Social communication 39.27 7.67 38.00 35.55 8.38 35.00 − 2.347 0.708 0.019* 0.016*
Social motivation 18.09 4.11 19.00 15.73 5.12 18.00 − 2.363 0.712 0.018* 0.016*
Restricted interests and repetitive behavior 21.18 3.92 22.00 21.09 4.46 22.00 − 0.211 0.064 0.833 0.844
SRS total 117.00 15.92 121.00 108.27 19.20 111.00 − 2.003 0.604 0.045* 0.048*

Journal of Autism and Developmental Disorders
1 3
Parent 1: “Child1 takes AAD1 to school every day. The tether system
has stopped Child1's elopement. AAD1 can help Child1 calm down
when upset and ease his anxiety. Child1's peers like AAD1 so they
interact more with Child1 than they did in the past. Child1 feeds
AAD1 and will throw a tennis ball for him. Child1 gives AAD1
some instructions but does not initiate a lot of play or petting.
Child1 will pet or hug AAD1 when prompted. They sleep in the
same room but not the same bed because Child1 does not appreci-
ate AAD1's kisses (licking his face).”
Parent 2: “AAD2 and Child2 are best buddies. AAD2 helps Child2
manage his anxiety, stay safe in public places, and allows our fam-
ily to access our community in a way that we've never been able to
do. Awesome!”
Parent 3: “You wouldn't necessarily know by interaction how impor-
tant AAD3 is to [non-verbal] Child3 but Child3 loves AAD3 and he
is very important to him. AAD3 sleeps with Child3 and assists when
we are out in the community.”
Discussion
Our primary study objective was to assess the multidimen-
sional impact of well-trained AADs on autistic children and
their families across key domains of function. By recruiting
from the top of a wait-list for AADs, we were able to enroll
participants shortly before they received their dog, thus
allowing us to collect pre-/post-AAD data using a battery
of psychosocial and biobehavioral assessments. Our find-
ings provide substantive support for the positive effects of
AADs above and beyond their duties as a child’s “sentinel
of safety” (Burrows etal., 2008).
The observed benefits of AADs may not be surprising
since young children, as early as 9-months of age, have
demonstrated an attraction to animals, often preferring them
to inanimate objects (DeLoache etal., 2011; Kahn, 1997;
Lobue etal., 2013; Ricard & Allard, 1993). Positive inter-
species interactions have also been associated with increased
concentrations of oxytocin and decreased cortisol levels in
both humans and canines (Handlin etal., 2015; Nagasawa
etal., 2015; Odendaal & Meintjes, 2003). During medical
procedures, the presence of a companion animal has been
shown to reduce a child’s physiological arousal and behav-
ioral distress (Nagengast etal., 1997; Vagnoli etal., 2015).
Correspondingly, during a laboratory-based stressor, rise in
perceived stress for TD children (7–12years) was buffered
significantly by the presence of the family pet dog, relative
to children who were alone or with a parent (Kertes etal.,
2017). As invaluable sources of socio-emotional support
(Melson, 2003), animals may also serve as transitional
objects, through which children can transfer their established
bonds to humans (Martin & Farnum, 2002). For children
especially, dogs provide multisensory experiences and direct
feedback in the context of nonverbal actions that may be
a Wilcoxon signed ranks test: based on positive ranks
b Missing data in responses from one Pre-AAD APSI
**p ≤ 0.01
*p ≤ 0.05
†p ≤ 0.10
Table 3 (continued)
Pre-AAD (T1) Post-AAD (T2) ZarAsymp. Sig.
(2-tailed)
Exact Sig. (2-tailed)
Mean SD Median Mean SD Median
B. Cortisol concentration measures
Chronic cortisol concentration (pg/mg)
Parent (N = 6) 10.255 6.098 7.710 6.127 4.176 3.975 − 2.201 0.898 0.028* 0.031*
Child (N = 5) 9.164 2.774 8.400 5.526 1.518 4.910 − 2.023 0.905 0.043* 0.063†

Journal of Autism and Developmental Disorders
1 3
more easily deciphered at early developmental stages (Pro-
thmann etal., 2009; Redefer & Goodman, 1989).
Prior research has suggested that dogs are particularly
adroit at eliciting prosocial behavior, acting as social
catalysts with humans, as well as reducing physiological
arousal and stress in children and adults (Fecteau etal.,
2017; McNicholas & Collis, 2000; Viau etal., 2010). Con-
sistent with these findings, our data show significant pre-/
post-AAD improvements for children on the AQ-Child, the
CBCL (CBCL Total Problems; Anxious/Depressed, Social
Problem, and Attention Problem Subscales; Internalizing
and Externalizing Problem Composites), and the SRS-2
(SRS Total; Social Cognition, Social Communication, and
Social Motivation Subscales). Parents self-reported signifi-
cantly reduced stress and anxiety on the APSI, PSS, and
STAI (State and Trait) and significantly improved fam-
ily experiences overall on the AFEQ (AFEQ Total; Child
Development, Understanding, & Social Relationships; Child
Symptoms—Feelings & Behavior; Family Life Subscales).
Both parents and children with pre-/post-AAD CCC data
showed a reduction on our objective physiological measure
of chronic stress. However, while the majority of outcome
measures indicated significant pre-/post-AAD improve-
ments, it is worthwhile to consider those areas that yielded
Fig. 2 Pre-/Post-AAD mean
score differences on parent self-
report measures demonstrating:
A improved family experiences
on the AFEQ, B reduction of
parenting stress on the APSI,
C reduction of perceived stress
on PSS; and D reduction of
anxiety on the STAI (*p ≤ 0.05;
**p ≤ 0.01)

Journal of Autism and Developmental Disorders
1 3
trend improvements on the AFEQ (Experience of Being a
Parent of a Child with Autism Subscale, p = 0.102) and the
CBCL (Somatic Complaints Subscale, p = 0.107) and t hose
measures that returned non-significant results on CBCL
Subscales (Withdrawn/Depressed, Rule-Breaking Behavior,
Thought Problems) and SRS-2 Subscales (Social Awareness,
RRBs). By differentiating between domains that are more
or less susceptible to the presence of an AAD, we may be
afforded insight into the potential mechanisms of actions
subserving the dynamic, ongoing relationships within par-
ent/handler-dog-child triads.
In evaluating how the integration of a well-trained AAD
can result in long-term changes in the lives of autistic chil-
dren and their families, adopting a dynamic biopsychosocial
perspective may be useful to contextualize the role of AADs
(Gee etal., 2021; Lehman etal., 2017). Within this frame-
work, the AAD’s role in preventing a child’s elopement may
be construed as a continuous interplay between biological,
psychological, and social factors within a non-static envi-
ronment. For example, by consistently and effectively pre-
venting a child from eloping, the AAD helps alleviate some
of the acute safety concerns reported by parents/caregiv-
ers of autistic children (Bonis, 2016; Burrows etal., 2008;
Rodriguez etal., 2019). Over time the increased sense of
security and social acknowledgment afforded by the AAD
may reduce chronic physiological and psychological stress
in parents, improving overall quality of life for the family
(Eddy etal., 1988; Mader etal., 1989). Further, parents have
reported that having the AAD to support their child enables
them to go on family outings, feel more independent, and
Fig. 3 Pre-/Post-AAD mean score differences on parent-report measures demonstrating improvements (decrease in problem scores or reduction
in challenges) on the A, B CBCL, C SRS-2, D AQ-Child (*p ≤ 0.05; **p ≤ 0.01)

Journal of Autism and Developmental Disorders
1 3
be more connected socially, processes that can also serve to
augment mental health and well-being more broadly (Bur-
goyne etal., 2014; Smyth & Slevin, 2010).
Limitations
While findings from this investigation provide significant
support for the benefits of AADs, the data are limited in a
number of ways.
First, we must note the conclusions drawn from these
AAD-teams should be considered in view of their highly-
specialized training and stringent certification criteria and
may not be generalized across animals described as emo-
tional support, therapy, comfort, or companion animals who
have not received comparable levels of training.
Second, we did not include a wait-list control group
(families who applied for an AAD but did not receive a dog
during the same period of time) or a non-wait-list control
group (families from the community who had not applied
for an AAD). Given the highly multifactorial nature of each
family’s individual characteristics, the unpredictable length
of time each family might be on the wait-list, and the lim-
ited number of AADs available, we decided to constrain
the study to a single group, repeated measures design. The
additional variability introduced by families who had not
applied for an AAD (non-wait-list controls) would render
comparison data even more difficult to interpret. Addi-
tionally, including a control group from further down the
wait-list would require participant families to remain on the
wait-list for the duration of the study collection period and
we did not wish to interfere with standard operating pro-
cedures of the training program. In particular, we did not
want study participation to be a factor if an AAD candidate
proved to be a good match for a control-family as collect-
ing an appropriately-timed T2 assessment would delay the
process of getting the AAD team started. Moreover, families
unlikely to receive a dog during our collection period (i.e.,
bottom of the 3–5year wait-list) would include a younger
cohort of autistic children who would be poorly matched to
the active group if we implemented a cross-sectional design.
Further, families on the wait-list could not be restricted from
introducing, discontinuing, or modifying therapies/medica-
tions during the study period; yet, these alterations would
inexorably confound comparisons to the active group. While
families who did receive an AAD were also not constrained
from altering their treatment plans, the training process of
becoming an AAD team is quite involved and we surmised
that families would not have the time to modify their existing
treatment plans substantially; we did not note any significant
alterations in child therapies/medications pre-post-AADs in
our sample but we could have factored in those changes to
our final analysis as needed.
Third, due to the high demand and low supply of qualified
AADs, our sample size was expectedly quite small. In antici-
pation of this limitation, we chose a within-subject design to
examine pre-/post-AAD changes for each family; we were
able to demonstrate significant, quantifiable changes from
T1 to T2. Also, because we were unable to collect all data
from the third time point as originally planned, we were
precluded from gauging if improvements were maintained
long-term. Additional data points could have provided
insight into whether continued interaction with AADs would
lead to sustained and/or greater/fewer changes over time.
For example, while we posit that some AAD effects follow
a more protracted time course through indirect pathways,
these may not be evident until more time has passed. One
putative mechanism entails the proximal reduction of physi-
ological arousal stress and an increase in feelings of physical
safety with the AAD that may impact sleep quality distally in
time. Several parent participants reported that their children
have difficulty sleeping which, in turn, affected their own
sleep quality. Sleep deprivation indubitably plays a role in
mental health and well-being, which can then impact multi-
ple levels of family systems and behavior (Mihaila & Hart-
ley, 2018). However, several families noted that with the
AAD’s presence, their children began sleeping through the
night, perhaps due to an increased sense of security or their
canine’s de-arousing capabilities.
Next, we could not control for the myriad variables that
may have contributed to changes over the study timeline.
For example, we cannot rule out the impact of developmen-
tal change over the study months and families maintained
their ongoing treatment and medication schedules while par-
ticipating. Although our T2 data demonstrated significant
improvements in participants relative to their T1 data, we
Fig. 4 Pre-/Post-AAD differences in chronic cortisol concentration
levels for parents and children (*p ≤ 0.05)

Journal of Autism and Developmental Disorders
1 3
cannot be certain that changes were not due to variables
such as maturation, concurrent treatments, or unknown envi-
ronmental factors. Also, most measures were parent-report
and parent-self report assessments, which may be subject
to response bias. Yet, given that the autistic children in our
study were quite young, heterogeneous in their presentation,
and all had co-occurring challenges (e.g., non-verbal, co-
morbid NDDs), it was not feasible to administer an objective
task-based or observational measure that would be develop-
mentally appropriate for all participants. We were, however
cautiously selective in the measures chosen for inclusion in
our assessment battery; all instruments were validated, reli-
able (see Table2), behavioral and psychosocial instruments
that have been developed for and used widely to evaluate
child functioning and development.
Finally, we experienced difficulty when collecting sam-
ples for cortisol assay because several participants had very
short or no scalp hair. Similar issues when collecting finger-
nail samples arose because some individuals bit their finger-
nails or kept their nails quite short. An alternative option that
may offset some of these issues in future studies might be
the use of toenail clippings to ascertain cortisol concentra-
tion. Overall, considering the heterogeneity of our partici-
pantfamilies, we are reasonably confident that receiving an
AAD, the one consistent change for all families during the
study collection period, was a driving factor in positive out-
comes. Nevertheless, findings based on our limited sample
size must be interpreted with caution.
Conclusions
To our knowledge, the present study is the first to examine
psychosocial and biobehavioral effects of assistance dogs
trained specifically for ASD using validated and standard-
ized measures of family experience, parental stress, autism
symptom severity, and child behavior; these data are also
the first to evaluate a biological marker for chronic stress in
both children and parents/caregivers. Our findings augment
significantly our evidence-base for the benefits of AADs on
autistic children and their families across multiple domains.
At present, well-trained assistance dogs, particularly
those for ASD, remain a highly limited ‘commodity’,
requiring considerable, often prohibitively high, investment
of resources by families and service dog providers. Aver-
age wait times for well-trained AADs can exceed 3years
and the estimated total cost to raise and train just one dog
can surpass $55,000 (Cooper, 2021; Ensminger, 2010;
Konrad, 2009). Further, after team certification, families
must assume all financial responsibilities for canine care.
Currently, no health insurance policies cover any of these
expenses beyond the possible application of pre-tax health-
care accounts, (Internal Revenue Service, 2020), and most
service dog providers require that families contribute at least
part of the costs themselves. Additionally, while US federal
law mandates access for service animals to all public areas
including schools, the Americans with Disabilities Act also
requires that the animal be under the handler's control at
all times (ADA, 2010). However, because public facilities
are not themselves responsible for service animals, schools
do not have to provide handlers. AADs are trained to work
as part of a triad, and unless an adult dog-handler is avail-
able, the child is still prohibited from bringing their AAD to
school. Given that these considerable financial and regula-
tory barriers remain, further work is needed to broaden the
scope of our research to more service dog providers and
autistic individuals both within the US and internationally.
An enhanced understanding of factors contributing to the
effectiveness of AADs will serve to refine canine placement
procedures and training approaches, with the ultimate goal
of increasing availability and accessibility of AADs for fam-
ilies who may benefit substantially from these specialized
human-canine partnerships.
Acknowledgments This research was supported by a Grant from the
Frank J. and Eleanor A. Maslowski Charitable Trust. We are most
grateful to members of the Project to Assess Assistance Dogs (PAAD)
Study (https:// paad. umn. edu/) and to Can Do Canines in New Hope,
MN (https:// cando canin es. org/) for their partnership and support
throughout this project. Special acknowledgment to Alan Peters (Can
Do Canines' Founder) for his leadership and vision, and to Can Do
Canines’ extraordinary team of staff and volunteers for their dedication
and commitment to enhancing quality of life for people with disabili-
ties. We are humbled by the strength and resilience of our participant
families and their hard-working canine partners, without whom this
work would not have been possible. We thank our collaborator, Dr.
Kestutis Bendinskas, and his research group in the Department of
Chemistry at the State University of New York at Oswego for perform-
ing all cortisol extraction and measurement procedures.
Author Contribution AT conceived of the study and performed all
aspects of study design, data collection, data analysis, and manuscript
preparation.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.

Journal of Autism and Developmental Disorders
1 3
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