A comparative study of sensory processing in children with and without Autism Spectrum Disorder in the home and classroom environments

Abstract

Sensory processing and higher integrative functions impairments are highly prevalent in
children with ASD. Context should be considered in analyzing the sensory profile and
higher integrative functions. The main objective of this study is to compare sensory
processing, social participation and praxis in a group of 79 children (65 males and
14 females) from 5 to 8 years of age (M = 6.09) divided into two groups: ASD Group (n = 41) and Comparison Group (n = 38). The Sensory Processing Measure (SPM) was used to evaluate the sensory profile of the children: parents reported information about their children’s characteristics in the home environment, and teachers reported information about the same characteristics in the classroom environment. The ASD Group obtained scores that indicate higher levels of dysfunction on all the assessed measures in both environments, with the greatest differences obtained on the social participation and praxis variables. The most affected sensory modalities in the ASD Group were hearing and touch. Only in the ASD Group were significant differences found between the information reported by parents and what was reported by teachers: specifically, the teachers reported greater
dysfunction than the parents in social participation (p = .000), touch (p = .003) and praxis
(p = .010). These results suggest that the context-specific qualities found in children with
ASD point out the need to receive information from both parents and teachers during the
sensory profile assessment process, and use context-specific assessments.

Full text

A
comparative
study
of
sensory
processing
in
children
with
and
without
Autism
Spectrum
Disorder
in
the
home
and
classroom
environments
M
a
Inmaculada
Ferna
´ndez-Andre
´s
a,
*,
Gemma
Pastor-Cerezuela
b
,
Pilar
Sanz-Cervera
c
,
Rau
´l
Ta
´rraga-Mı
´nguez
c
a
Developmental
and
Educational
Psychology
Department,
Faculty
of
Psychology,
University
of
Valencia.
Av.
Blasco
Iba
´n
˜ez,
21,
46010
Valencia,
Spain
b
Basic
Psychology
Department,
Faculty
of
Psychology,
University
of
Valencia,
Av.
Blasco
Iba
´n
˜ez,
21,
46010
Valencia,
Spain
c
Teaching
and
Scholastic
Organization
Department,
Faculty
of
Philosophy
and
Educational
Sciences,
University
of
Valencia,
Av.
Tarongers,
s/n,
46022
Valencia,
Spain
1.
Introduction
In
the
recently
published
DSM-5
(APA,
2013),
Autism
Spectrum
Disorder
(ASD)
is
considered
as
a
neurodevelopmental
disorder
characterized
by:
(1)
‘‘persistent
deficits
in
social
communication
and
social
interaction
across
multiple
contexts’’,
and
(2)
‘‘the
presence
of
restricted,
repetitive
patterns
of
behavior,
interests
or
activities’’.
The
possible
inclusion
of
sensory
Research
in
Developmental
Disabilities
38
(2015)
202–212
A
R
T
I
C
L
E
I
N
F
O
Article
history:
Received
13
October
2014
Received
in
revised
form
20
December
2014
Accepted
20
December
2014
Available
online
6
January
2015
Keywords:
Autism
Spectrum
Disorder
(ASD)
Sensory
processing
Higher
integrative
functions
Sensory
processing
measure
(SPM)
Home
and
classroom
environments
A
B
S
T
R
A
C
T
Sensory
processing
and
higher
integrative
functions
impairments
are
highly
prevalent
in
children
with
ASD.
Context
should
be
considered
in
analyzing
the
sensory
profile
and
higher
integrative
functions.
The
main
objective
of
this
study
is
to
compare
sensory
processing,
social
participation
and
praxis
in
a
group
of
79
children
(65
males
and
14
females)
from
5
to
8
years
of
age
(M
=
6.09)
divided
into
two
groups:
ASD
Group
(n
=
41)
and
Comparison
Group
(n
=
38).
The
Sensory
Processing
Measure
(SPM)
was
used
to
evaluate
the
sensory
profile
of
the
children:
parents
reported
information
about
their
children’s
characteristics
in
the
home
environment,
and
teachers
reported
information
about
the
same
characteristics
in
the
classroom
environment.
The
ASD
Group
obtained
scores
that
indicate
higher
levels
of
dysfunction
on
all
the
assessed
measures
in
both
environments,
with
the
greatest
differences
obtained
on
the
social
participation
and
praxis
variables.
The
most
affected
sensory
modalities
in
the
ASD
Group
were
hearing
and
touch.
Only
in
the
ASD
Group
were
significant
differences
found
between
the
information
reported
by
parents
and
what
was
reported
by
teachers:
specifically,
the
teachers
reported
greater
dysfunction
than
the
parents
in
social
participation
(p
=
.000),
touch
(p
=
.003)
and
praxis
(p
=
.010).
These
results
suggest
that
the
context-specific
qualities
found
in
children
with
ASD
point
out
the
need
to
receive
information
from
both
parents
and
teachers
during
the
sensory
profile
assessment
process,
and
use
context-specific
assessments.
ß
2014
Elsevier
Ltd.
All
rights
reserved.
*
Corresponding
author.
Tel.:
+34
963983350.
E-mail
addresses:
m.inmaculada.fernandez@uv.es
(M.I.
Ferna
´ndez-Andre
´s),
gemma.pastor@uv.es
(G.
Pastor-Cerezuela),
pipi2@alumni.uv.es
(P.
Sanz-Cervera),
raul.tarraga@uv.es
(R.
Ta
´rraga-Mı
´nguez).
Contents
lists
available
at
ScienceDirect
Research
in
Developmental
Disabilities
http://dx.doi.org/10.1016/j.ridd.2014.12.034
0891-4222/ß
2014
Elsevier
Ltd.
All
rights
reserved.

criteria
–
‘‘hyper-
or
hypo-reactivity
to
sensory
input
or
unusual
interest
in
sensory
aspects
of
the
environment’’
(APA,
2013)
–
has
been
considered
under
diagnostic
criterion
2.
Sensory
processing
refers
to
the
way
the
central
and
peripheral
nervous
systems
manage
incoming
sensory
information
from
the
sensory
organs,
namely
visual,
auditory,
tactile,
taste,
smell,
proprioception
and
vestibular.
Sensory
Integration
Theory
(Ayres,
Robbins,
&
McAtee,
1979)
proposes
that
the
processing
and
integration
of
sensory
inputs
is
a
critical
neurobehavioral
process
that
strongly
affects
development.
Sensory
functioning
characteristics
include
registration
(or
detection)
of
stimuli,
modulation
(regulation
of
level
or
intensity),
discrimination
and
praxis
(planning
of
new
motor
acts).
Sensory
processing
impairment
is
a
neurological
dysfunction
affecting
the
adequate
reception,
modulation,
integration,
discrimination
or
organization
of
sensory
stimuli,
and
the
behavioral
responses
to
sensory
input
(Tomchek,
2001).
In
children,
behavioral
problems,
learning
difficulties,
motor
coordination
difficulties,
attentional
problems
and
even
maladaptive
social
functioning
may,
in
many
cases,
be
attributable
to
dysfunctions
in
any
of
these
sensorial
processes,
since
difficulties
at
the
level
of
sensory
processing
often
contribute
to
impairments
in
higher
level
integrative
functions,
such
as
social
participation
and
praxis
(or
the
ability
to
plan
and
organize
movement).
On
the
basis
of
Ayres’
theory,
Dunn
(1997)
proposed
a
model
for
classifying
patterns
of
sensory
processing
dysfunction
according
to
individuals’
behavioral
response
to
stimuli
and
neurological
thresholds.
This
model
described
four
patterns:
sensory
sensitivity
(distress
and
distraction
from
sensations),
sensation
avoiding
(controlling
or
limiting
the
amount
and
type
of
sensations),
low
registration
(lack
or
low
awareness
of
sensations),
and
sensation
seeking
(enjoyment
and
interest
in
increasing
sensations).
Both
sensory
sensitivity
and
sensation
avoiding
represent
hypersensitivity,
whereas
low
registration
and
sensation
seeking
represent
hyposensitivity.
In
the
case
of
children
with
ASD,
sensory
processing
impairments
have
been
reported
to
be
highly
prevalent
(Baranek,
David,
Poe,
Stone,
&
Watson,
2006;
Costa
&
Lampreia,
2012;
Kientz
&
Dunn,
1997;
Liss,
Saulnier,
Fein,
&
Kinsbourne,
2006;
Watling,
Deitz,
&
White,
2001).
Sensory
dysfunctions
are
not
always
present
in
or
exclusive
to
ASD,
as
they
are
also
present
in
other
disorders
and
disabilities
(Cheung
&
Siu,
2009;
Ermer
&
Dunn,
1998;
Leekam,
Nieto,
Libby,
Wing,
&
Gould,
2007;
O’Brien
et
al.,
2009;
Rogers,
Hepburn,
&
Wehner,
2003;
Wiggins,
Robins,
Bakeman,
&
Adamson,
2009).
Several
studies
have
compared
sensory
processing
characteristics
of
children
with
ASD
with
those
of
children
with
typical
development,
finding
significantly
higher
dysfunctions
in
the
case
of
children
with
ASD
(Ashburner,
Ziviani,
&
Rodger,
2008;
Ben-Sasson
et
al.,
2007,
2009;
Dickie,
Baranek,
Schultz,
Watson,
&
McComish,
2009;
Dunn,
Myles,
&
Orr,
2002;
Kern
et
al.,
2006;
Kientz
&
Dunn,
1997;
Lai,
Chung,
Chan,
&
Li-Tsang,
2011;
Tomchek
&
Dunn,
2007;
Watling
et
al.,
2001).
The
sensory
modalities
that
have
shown
more
differences
are
hearing
and
touch
(Ashburner
et
al.,
2008;
Kientz
&
Dunn,
1997;
Rogers
et
al.,
2003;
Tomchek
&
Dunn,
2007;
Wiggins
et
al.,
2009)
with
hypersensitivity
being
the
most
common
in
people
with
ASD-,
although
differences
have
been
also
found
in
the
other
sensory
modalities
(both
external
and
internal).
The
most
common
way
to
assess
sensory
processing
characteristics
in
children
with
ASD
has
involved
parent
or
teacher
reports
on
standardized
questionnaires.
Standardized
questionnaires
such
as
the
Sensory
Profile,
SP
(Dunn,
1999),
and
the
Sensory
Processing
Measure,
SPM
(Parham,
Ecker,
Kuhaneck,
Henry,
&
Glennon,
2007),
allow
a
detailed
assessment
of
the
child’s
sensory
profile
based
on
estimates
by
adult
references
of
observed
behavior.
Moreover,
since
behavior
is
influenced
by
the
context,
this
variable
should
also
be
considered
in
analyzing
the
sensory
profile.
Thus,
each
setting
contains
unique
characteristics
that
can
support
children
and/or
create
challenges
for
their
performance.
Each
setting
also
contains
inherent
sensory
features
(Dunn,
Saiter,
&
Rinner,
2002).
Hence,
the
aforementioned
assessment
instruments
contain
different
versions
that
are
applicable
in
different
contexts.
For
example,
in
the
case
of
SPM,
psychometric
validation
studies
conducted
with
Chinese
(Lai
et
al.,
2011)
and
US
populations
(Parham
et
al.,
2007)
obtained
low
correlations
across
settings
(home
and
classroom).
In
general,
the
literature
on
multiple
informants
indicates
that
when
parents
and
teachers
are
asked
the
same
question,
the
correlations
of
the
answers
are
low
(De
los
Reyes
&
Kazdin,
2005).
The
study
by
Brown
and
Dunn
(2010)
also
used
correlation
analysis
to
compare
the
sensory
processing
characteristics
of
a
group
of
children
with
ASD
in
the
two
contexts
(home
and
school),
based
on
information
provided
by
the
children’s
parents
and
teachers
in
the
Sensory
Profile.
In
this
study,
only
two
sensory
processing
patterns
were
analyzed
(sensation
avoiding
and
sensation
seeking),
but
the
scores
obtained
in
each
of
the
different
sensory
modalities
in
the
two
contexts
were
not
compared.
To
date,
we
have
not
found
any
other
studies
conducted
in
children
with
ASD
that
compared
their
sensory
processing
characteristics
in
different
settings.
The
current
study
had
several
aims:
(1)
to
compare
the
characteristics
of
sensory
processing,
social
participation
and
praxis
of
a
group
of
children
with
ASD
(ASD
Group)
and
a
group
of
children
with
typical
development
(Comparison
Group)
in
the
home
environment
(information
reported
by
parents);
(2)
to
compare
the
characteristics
of
sensory
processing,
social
participation
and
praxis
of
the
ASD
Group
and
the
Comparison
Group
in
the
classroom
(information
reported
by
teachers);
and
(3)
to
compare
–
in
each
group
separately
–
the
characteristics
of
sensory
processing,
social
participation
and
praxis
reported
by
parents
with
what
was
reported
by
teachers.
This
third
objective
is
justified
by
the
important
effect
of
context
on
behavior
and
the
probable
existence
of
inherent
and
unique
sensory
features
in
each
context.
Thus,
in
the
case
of
the
school
environment,
certain
environmental
factors
such
as
the
demands
of
school
assignments
and
stimulation
overload
could
lead
to
a
noteworthy
sensory
dysfunction
in
the
case
of
the
ASD
Group.
In
sum,
considering
the
previous
studies
mentioned
above,
we
hypothesize
that
the
ASD
Group
will
obtain
higher
levels
of
dysfunction
than
the
Comparison
Group
(in
both
contexts),
and
that
the
ASD
Group
will
obtain
a
higher
level
of
dysfunction
in
the
classroom
environment
than
in
the
home
environment.
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
203

2.
Materials
and
methods
2.1.
Participants
In
the
present
study,
participants
were
the
parents
and
teachers
of
a
total
of
79
children.
The
children’s
ages
ranged
from
5
to
8
years
old,
and
their
performance
IQ
ranged
from
75
to
135
on
the
Raven
test
(Raven,
1996).
The
79
children
were
divided
into
two
groups:
The
ASD
Group
(n
=
41)
was
composed
of
36
males
and
5
females
with
a
mean
age
of
6.09
years
(SD
=
1.06)
and
a
mean
IQ
performance
of
97.88
(SD
=
20.47);
and
the
Comparison
Group
(n
=
38)
was
composed
of
29
males
and
9
females
with
a
mean
age
of
6.56
years
(SD
=
1.19)
and
a
mean
IQ
performance
of
97.53(SD
=
17.90).
Children
in
the
ASD
Group
had
a
clinical
diagnosis
of
ASD,
according
to
the
criteria
of
the
DSM-IV-TR
(APA,
2000),
and
they
met
the
diagnostic
criteria
for
level
2
of
the
DSM-5
(APA,
2013).
They
were
diagnosed
by
neuropediatric
services
from
different
hospitals
in
the
national
health
system.
These
neuropediatric
services
were
responsible
for
checking
compliance
with
these
diagnostic
criteria,
and
they
referred
the
children
who
met
the
diagnostic
criteria
to
early
care
units,
where
the
diagnosis
was
confirmed
using
more
specific
instruments
such
as
the
ADOS.
Moreover,
all
of
them
obtained
an
autism
index
score
85
on
the
Gilliam
Autism
Rating
Scale,
Second
Edition
(GARS-2),
indicating
a
high
likelihood
of
the
disorder
(Gilliam,
2006).
The
scores
ranged
from
85
to
135
(M
=
98.65,
SD
=
9.99).
The
children
in
the
ASD
Group
were
attending
school
in
TEACCH
classrooms
for
students
with
disorders
affecting
language
and
communication
integrated
in
regular
public
schools
in
Valencia
(Spain).
The
children
in
the
Comparison
Group
were
children
with
typical
development,
without
any
clinical
diagnosis,
who
attended
the
same
schools
as
the
ASD
Group,
but
in
the
regular
modality.
To
obtain
this
sample,
schools
with
integrated
TEACCH
classrooms
were
asked
to
participate
in
this
research.
Out
of
18
schools
that
voluntarily
agreed
to
participate,
67
five-to-eight
year
old
children
with
ASD
were
selected,
but
6
were
ruled
out
because
they
were
not
able
to
understand
the
Raven
test.
Of
the
61
selected
children,
only
41
parents
participated
voluntarily
in
an
interview
with
the
school
psychologist
to
fill
out
a
series
of
questionnaires.
As
for
the
teachers,
all
18
teachers
of
the
TEACCH
classrooms
agreed
to
participate
in
the
interview
with
the
school
psychologist.
The
Comparison
Group
was
initially
made
up
of
350
children
who
were
also
between
5
and
8
years
old
and
attended
11
of
the
18
schools
where
the
children
with
ASD
were
enrolled.
The
two
groups
of
children
were
matched
one-to-one
on
performance
IQ,
chronological
age
and
gender,
so
that
of
the
initial
350
children
without
ASD,
61
were
selected.
Finally,
38
parents
and
11
teachers
of
these
61
children
participated
voluntarily
in
the
interview
with
the
school
psychologist.
Table
1
includes
the
children’s
demographic
information
for
the
ASD
and
Comparison
Groups.
There
were
36
boys
and
5
girls
in
the
ASD
Group
and
29
boys
and
9
girls
in
the
Comparison
Group.
Both
groups
had
a
mean
age
of
about
6
years
and
a
mean
performance
IQ
(measured
by
the
Raven
test)
of
about
97.
No
statistically
significant
differences
were
found
between
the
two
groups
of
children
on
gender
(
x
2
=
1.79;
p
=
.181;
h
2
=
.150),
chronological
age
(F
(1,77)
=
3.47;
p
=
.066;
h
p2
=
.043)
or
performance
IQ
(F
(1,77)
=
.007;
p
=
.936;
h
p2
=
.000).
Table
2
includes
family
demographic
information
for
the
ASD
and
Comparison
Groups.
In
the
two
groups,
most
of
the
participants
were
mothers
(around
80%),
and
the
mean
age
of
the
parents
was
about
39
(range:
25–50).
No
statistically
significant
differences
were
found
between
the
two
groups
of
parents
on
gender
(
x
2
=
.56;
p
=
.455;
h
2
=
.084)
or
age
(F
(1,77)
=
.12;
p
=
.729;
h
p2
=
.002).
Regarding
the
educational
level,
in
the
two
groups
about
31%
of
the
parents
reported
having
elementary
education
and
about
68%
reported
having
intermediate
or
higher
education.
Although
the
educational
level
of
the
parents
of
the
two
groups
was
similar,
in
the
case
of
their
occupation,
most
of
the
parents
in
the
Comparison
Group
(63.2%)
had
a
paid
job,
while
this
circumstance
occurred
in
less
than
half
of
the
parents
in
the
ASD
Group
(43.9%).
In
both
groups,
most
of
the
parents
were
married
or
living
together
(between
73%
and
80%)
and
they
reported
having
low
or
middle
income,
about
14%
reported
having
no
income,
and
the
mean
number
of
children
in
the
family
was
about
1.80.
Table
3
includes
teachers’
demographic
information
for
the
ASD
and
Comparison
Groups.
A
total
of
29
teachers
participated,
of
whom
11
were
the
regular
classroom
teachers
who
completed
the
questionnaires
about
the
children
in
the
Comparison
Group,
and
18
were
the
teachers
in
the
TEACCH
classrooms
(Therapeutic
Education
Teachers
or
Hearing
and
Language
Teachers)
who
completed
the
questionnaires
about
the
children
in
the
ASD
Group.
In
the
two
groups,
almost
100%
of
the
participating
teachers
were
female.
No
statistically
significant
differences
were
found
between
the
two
groups
of
teachers
on
gender
(
x
2
=
.63;
p
=
.426;
h
2
=
.148).
Regarding
the
age
of
the
teachers,
the
range
was
from
26
to
60.
Statistically
significant
differences
were
found
for
age
(F
(1,27)
=
6.60;
p
=
.016;
h
p2
=
.196),
as
it
was
higher
in
the
teachers
of
the
Comparison
Group
(M
=
43.09)
than
in
the
teachers
of
the
ASD
Group
(M
=
34.56).
Regarding
educational
level,
most
of
the
Table
1
Children’s
demographic
information
for
ASD
and
Comparison
Groups.
ASD
Group
(n
=
41)
Comparison
Group
(n
=
38)
Gender
Male
36
(87.8%)
29
(76.3%)
Female
5
(12.2%)
9
(23.7%)
Mean
age
in
years
(SD)
6.09
(1.06)
6.56
(1.19)
Mean
IQ
performance
(SD)
97.88
(20.47)
97.53
(17.90)
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
204

teachers
in
the
ASD
Group
had
more
academic
training
than
the
teachers
in
the
Comparison
Group,
with
this
difference
being
statistically
significant
(
x
2
=
6.58;
p
=
.037;
h
2
=
.476).
Thus,
in
both
groups,
all
the
teachers
had
a
three-year
university
degree,
but
in
the
case
of
the
teachers
in
the
ASD
Group,
10
of
them
(56%)
had
a
five-year
university
degree
or
a
masters
degree,
while
only
1
teacher
in
the
Comparison
Group
(9%)
had
one
of
these
higher
levels
of
academic
preparation.
All
the
teachers
had
between
5
and
36
academic
years
of
teaching
experience,
with
the
mean
of
the
teachers
in
the
Comparison
Group
(14.64)
being
higher
than
that
of
the
teachers
in
the
ASD
Group
(9),
although
this
difference
was
not
statistically
significant
(F
(1,27)
=
3.02;
p
=
.093;
h
p2
=
.101).
Regarding
the
number
of
academic
years
of
contact
with
students,
in
the
ASD
Group
teachers
had
between
1
and
5
academic
years
(M
=
2.33)
of
contact
with
the
children,
while
in
the
Comparison
Group
teachers
had
between
1
and
2
academic
years
(M
=
1.36)
of
contact
with
the
children,
with
this
difference
being
statistically
significant
(F
(1,27)
=
7.69;
p
=
.010;
h
p2
=
.222).
2.2.
Ethics
statement
This
study
is
part
of
a
broader
investigation
that
was
approved
and
funded
by
the
University
of
Valencia
and
had
the
official
and
written
authorization
of
the
General
Direction
and
Management
Schools
(Valencian
Education,
Training
and
Employment
Department).
All
of
the
Valencian
state
schools
with
TEACCH
integrated
classrooms
were
invited,
via
an
informative
meeting,
to
participate
in
the
research.
From
the
schools
that
voluntarily
agreed
to
participate,
some
classrooms
of
5–8-year-old
children
were
selected.
The
parents
of
the
children
gave
written
informed
consent
to
participate
in
the
research.
2.3.
Procedures
Each
child’s
performance
IQ
was
individually
evaluated
by
the
school
psychologist
in
a
noise
and
distraction
free
office.
Parents
and
teachers
of
all
the
selected
children
were
asked
to
participate
in
an
interview
with
the
school
psychologist
in
Table
2
Family
demographic
information
for
ASD
and
Comparison
Groups.
ASD
Group
(n
=
41)
Comparison
Group
(n
=
38)
Parents’
response
Father
6
(14.6%)
8
(21.1%)
Mother
35
(85.4%)
30
(78.9%)
Parents’
mean
age
(SD)
38.95
(4.39)
39.34
(5.58)
Parents’
educational
level
Elementary
education
13
(31.7%)
12
(31.6%)
Intermediate
or
higher
education
28
(68.3%)
26
(68.4%)
Occupation
Do
not
have
a
paid
job
23
(56.1%)
14
(36.8%)
Have
a
paid
job
18
(43.9%)
24
(63.2%)
Parents’
marital
status
Married
–
living
together
33
(80.5%)
28
(73.7%)
Single
–
divorced
–
separated
8
(19.5%)
10
(26.3%)
Parents’
income
No
income
6
(14.6%)
5
(13.2%)
Low–medium
income
17
(41.5%)
14
(36.8%)
Medium
income
18
(43.9%)
19
(50%)
Mean
number
of
children
(SD)
1.76
(0.66)
1.90
(0.56)
Table
3
Teachers’
demographic
information
for
ASD
and
Comparison
Groups.
ASD
Group
(n
=
18)
Comparison
Group
(n
=
11)
Teachers’
gender
Male
1
(5.6%)
–
Female
17
(94.4%)
11
(100%)
Teachers’
mean
age
(SD)
34.56
(6.79)
43.09
(11.18)
Teachers’
educational
level
Have
a
three-year
university
degree
8
(44.4%)
10
(90.9%)
Have
a
five-year
university
degree
5
(27.8%)
1
(9.1%)
Have
a
masters
degree
5
(27.8%)
–
Years
academic
of
teaching
experience
mean
(SD)
9
(7.00)
14.64
(10.50)
Years
academic
of
contact
with
student
mean
(SD)
2.33
(1.09)
1.36
(0.51)
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
205

order
to
provide
demographic
information
(see
Tables
2
and
3)
and
fill
out
the
questionnaires.
Specifically,
parents
and
teachers
of
the
children
in
the
sample
were
asked
to
complete
the
SPM
–
Home
Form
and
the
SPM
–
Main
Classroom
Form
questionnaires,
respectively.
Additionally,
information
about
autism
severity
was
obtained
from
the
GARS-2,
by
means
of
an
interview
with
the
parents
of
the
ASD
Group.
2.4.
Measures
2.4.1.
Raven’s
Colored
Progressive
Matrices
(CPM)
(Raven,
1996)
This
scale
provides
an
estimation
of
the
deductive
capacity
and
the
‘‘g’’
factor
of
general
intelligence.
This
non-verbal
test
contains
36
elements
where
the
child
must
choose
missing
pieces
from
a
series
of
between
6
and
8
proposals.
It
is
administered
to
children
between
4
and
9
years
old.
We
used
the
performance
IQ
score
provided
by
the
test.
2.4.2.
Gilliam
Autism
Rating
Scale,
Second
Edition
(GARS-2),
(Gilliam,
2006)
The
GARS-2
is
a
standardized,
professional
and
parent-report
instrument
to
evaluate
autism
symptoms
in
people
between
3
and
22
years
old.
Based
on
the
definition
of
autism
and
the
DSM-IV-TR
diagnostic
criteria
(APA,
2000),
the
scale
consists
of
42
items,
responded
to
on
a
Likert-type
scale,
which
measure
three
domains
associated
with
the
disorder:
Stereotyped
Behavior,
Communication,
and
Social
Interaction.
The
combined
scores
on
these
subscales
yield
an
autism
index
(AI)
score
(M
=
100
and
SD
=
15),
with
higher
scores
indicating
a
greater
degree
of
autism.
Gilliam
(31)
reported
AI
scores
85
for
90%
of
a
normative
sample
of
1107
people
diagnosed
with
autism.
Therefore,
the
higher
the
value
obtained
on
the
global
index
(AI
score),
the
greater
the
probability
of
autism,
so
that
three
categories
are
established:
Improbable
Autism
(AI
score
lower
than
70),
Possible
Autism
(AI
score
from
70
to
84),
or
Probable
Autism
(AI
score
equal
to
or
greater
than
85).
The
GARS-2
is
a
widely
used
tool
to
assess
ASD
symptoms,
and
it
has
been
adapted
and
validated
in
different
countries,
with
results
showing
good
psychometric
characteristics.
For
the
Spanish
version,
the
scale’s
internal
consistency
was
high
(Cronbach’s
alpha
=
.94
for
the
AI),
and
the
scale’s
criterion
validity
with
the
Autism
Behavior
Checklist
was
also
high
(.94).
2.4.3.
The
Sensory
Processing
Measure
(SPM),
(Parham
et
al.,
2007)
Based
on
Sensory
Integration
Theory
(Ayres
et
al.,
1979),
SPM
is
an
integrated
system
of
rating
scales
that
assess
sensory
processing
issues,
praxis,
and
social
participation
in
elementary
school-aged
children
(ages
5–12).
In
our
research,
we
used
a
Spanish
translated
version
(unpublished)
of
the
original
SPM
(Parham
et
al.,
2007).
Translations
and
back
translations
were
carried
out,
and
the
equivalence
of
the
translation
was
first
reviewed
by
8
expert
panel
members
(including
4
occupational
therapists,
3
psychologists
and
1
speech
therapist).
The
original
SPM
consists
of
three
forms
that
evaluate
the
child’s
functioning
in
different
environments.
In
this
study,
we
specifically
used
the
aforementioned
translation
of
the
original
SPM
–
Home
Form
and
SPM
–
Main
Classroom
Form
to
evaluate
the
child’s
functioning
in
the
home
environment
and
in
the
classroom
environment,
respectively.
The
test
items
cover
a
wide
range
of
behaviors
and
characteristics
related
to
sensory
processing
and
functional
performance
(social
participation
and
praxis).
Each
item
is
rated
in
terms
of
the
frequency
of
the
behavior
on
a
4-point
Likert-type
scale.
The
response
options
are
Never,
Occasionally,
Frequently
and
Always.
The
SPM
Home
Form
consists
of
75
items
and
is
completed
by
the
child’s
parent
or
home-based
care
provider.
The
SPM
Main
Classroom
Form
consists
of
62
items
and
is
completed
by
the
child’s
primary
classroom
teacher.
Both
forms
yield
several
norm-referenced
standard
scores
corresponding
to
the
different
scales
of
the
instrument:
Social
Participation
(SOC),
Planning
and
Ideas
(PLA),
Vision
(VIS),
Hearing
(HEA),
Touch
(TOU),
Body
Awareness
(BOD),
and
Balance
and
Motion
(BAL).
The
latter
five
subscales
make
it
possible
to
assess
possible
problems
or
alterations
in
the
functioning
of
each
of
these
different
sensory
systems
(visual,
auditory,
tactile,
propioceptive
and
vestibular,
respectively),
and
the
item
responses
are
sensitive
to
processing
vulnerabilities
within
each
sensory
system,
including
under-
and
over-responsiveness,
sensory
seeking
behavior
and
perceptual
problems.
From
the
scores
obtained
on
these
five
sensory
system
subscales
–
and
additional
items
representing
taste
and
smell
processing
–
a
total
score
called
Total
Sensory
Systems
(TOT)
can
be
obtained
that
represents
general
dysfunction
in
sensory
processing.
On
the
other
hand,
the
SOC
and
PLA
scales
represent
higher
level
integrative
functions
that
are
influenced
by
sensory
inputs
while
encompassing
other
cognitive
and
contextual
factors.
The
SOC
subscale
measures
the
child’s
participation
in
social
activities
in
the
home
and
community,
as
well
as
his/her
ability
to
get
along
with
peers
and
participate
appropriately
in
classroom
activities.
The
PLA
subscale
measures
praxis,
the
ability
to
conceptualize,
plan
and
organize
movements
in
order
to
complete
unfamiliar
motor
tasks.
Praxis
has
two
aspects:
ideation
(the
ability
to
create
a
conceptual
or
mental
image
of
a
novel
task)
and
motor
planning
(the
ability
to
organize
and
plan
novel
actions).
The
standard
score
for
each
subscale
makes
it
possible
to
classify
the
child’s
functioning
into
one
of
three
interpretive
ranges:
Typical
range
(T-score
range
40–59),
which
indicates
that
the
child’s
behavioral
and
sensory
functioning
is
similar
to
that
of
typical
children;
Some
Problems
range
(T-score
range
60–69),
which
indicates
mild-to-moderate
difficulties
in
behavioral
or
sensory
functioning;
and
Definite
Dysfunction
range
(T-score
range:
70–80),
which
indicates
a
significant
sensory
processing
problem
that
may
have
a
noticeable
effect
on
the
child’s
daily
functioning.
Both
forms
(Home
and
Main
Classroom)
from
the
original
version
share
many
structural
and
interpretative
similarities,
and
so
it
is
possible
to
assess
the
child’s
sensory
functioning
across
these
two
different
environments
in
order
to
compare
them.
The
original
versions
of
both
questionnaires
present
good
psychometric
characteristics.
The
different
subscales
in
both
forms
present
high
internal
consistency
(Cronbach’s
alphas
range
from
.75
to
.95).
Regarding
validity,
the
different
SPM
subscales
of
the
home
version
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
206

present
correlation
indexes
of
around
.5
with
the
subscales
of
the
Sensory
Profile
and
the
Short
Sensory
Profile
(Dunn,
1999)
that
evaluate
similar
aspects.
For
the
different
subscales
of
the
SPM
–
Main
Classroom
Form,
these
correlation
indexes
are
lower
(around
.2)
because
the
analyses
were
performed
with
the
application
scales
in
the
home
environment
of
the
Sensory
Profile
and
Short
Sensory
Profile,
as
described
in
the
SPM
handbook
(Parham
et
al.,
2007).
2.4.4.
Questionnaires
developed
by
the
authors
We
used
a
socio-demographic
questionnaire
to
ask
parents
about
their
gender,
age,
educational
level,
occupation,
marital
status,
income
level
and
number
of
children
(see
Table
2),
and
a
socio-demographic
questionnaire
to
ask
teachers
about
their
gender,
age,
educational
level,
number
of
academic
years
of
teaching
experience,
and
number
of
academic
years
of
contact
with
the
students
(see
Table
3).
2.5.
Data
analysis
Analyses
were
performed
with
the
SPSS
statistical
package,
version
19
for
Windows.
First,
multivariate
analyses
of
variance
(MANOVA)
were
carried
out
to
compare
the
characteristics
of
sensory
processing,
social
participation
and
praxis
in
the
ASD
Group
and
the
Comparison
Group:
a
MANOVA
to
compare
the
two
groups
in
the
home
environment
(parent
report)
and
another
MANOVA
to
compare
the
two
groups
in
the
classroom
environment
(teacher
report).
Second,
to
compare
the
parent
report
with
what
was
reported
by
teachers,
multivariate
analyses
of
variance
(MANOVA)
for
repeated
measures
were
performed:
one
for
the
Comparison
Group
and
another
for
the
ASD
Group.
3.
Results
3.1.
Group
differences
in
sensory
processing,
social
participation
and
praxis
in
the
home
environment
The
MANOVA
performed
with
the
scores
obtained
on
the
SPM
–
Home
Form
revealed
statistically
significant
differences
between
the
ASD
Group
and
the
Comparison
Group
on
all
the
subscales
evaluated
(Wilk’s
Lambda
(
l
)
=
.491;
F
(8,70)
=
9.06;
p
=
.000;
h
p2
=
.509).
As
shown
in
Table
4,
in
all
cases,
the
parents
of
the
children
in
the
ASD
Group
evaluated
their
children’s
characteristics
of
sensory
processing,
social
participation
and
praxis
as
significantly
more
dysfunctional
than
the
parents
of
the
children
in
the
Comparison
Group.
The
greatest
differences
were
obtained
on
the
subscales
of
Social
Participation,
Hearing,
Planning
and
Ideas,
and
Total
Sensory
Systems
(in
all
of
them,
h
p2
exceeded
the
value
of
0.3).
When
we
analyzed
the
percentage
of
scores
obtained
by
the
two
groups
in
each
of
the
three
SPM
interpretative
ranges
(Typical,
Some
Problems
and
Definite
Dysfunction)
in
the
home
environment
(see
Fig.
1),
we
noted
first
that
80–90%
of
the
Comparison
Group
obtained
scores
within
the
Typical
range,
while
a
small
percentage
(e.g.
15.8%
in
Total
Sensory
Systems,
18.4%
in
Social
Participation,
and
15.8%
in
Planning
and
Ideas)
obtained
scores
within
the
Some
Problems
and
Definite
Dysfunction
ranges,
indicating
some
difficulty.
However,
the
ASD
Group
obtained
a
percentage
of
scores
within
the
Typical
range
that
varies
depending
on
the
subscale
assessed,
from
26.8%
on
the
Social
Participation
subscale
to
56.1%
on
the
Touch
subscale.
In
addition,
a
high
percentage
of
the
ASD
Group
obtained
scores
within
the
Some
Problems
and
Definite
Dysfunction
ranges
(e.g.
65.9%
in
Total
Sensory
Systems,
73.2%
in
Social
Participation,
and
63.4%
in
Planning
and
Ideas).
Of
the
different
sensory
systems,
the
highest
percentage
of
dysfunction
in
the
ASD
Group
was
found
for
Hearing
(in
63.4%
of
the
cases),
according
to
the
information
provided
by
the
parents
of
these
children.
3.2.
Group
differences
in
sensory
processing,
social
participation
and
praxis
in
the
classroom
at
school
environment
The
MANOVA
performed
with
the
scores
obtained
on
the
SPM
–
Main
Classroom
Form
revealed
statistically
significant
differences
between
the
ASD
Group
and
the
Comparison
Group
on
all
the
subscales
evaluated
(Wilk’s
Lambda
(
l
)
=
.347;
Table
4
T-score
means,
standard
deviations
and
F-values
for
SPM–home
form
subscales
for
ASD
and
Comparison
Groups.
ASD
Group
Comparison
Group
F
(1,77)
p
h
p2
M
SD
M
SD
Vision
(VIS)
62.63
8.34
52.95
8.59
25.85
**
.000
.251
Hearing
(HEA)
63.12
8.64
50.66
8.72
40.67
**
.000
.346
Touch
(TOU)
59.76
9.20
51.79
7.46
17.69
**
.000
.187
Body
awareness
(BOD)
60.29
6.90
53.34
7.60
18.16
**
.000
.191
Balance
and
motion
(BAL)
58.59
9.55
49.03
6.99
25.44
**
.000
.248
Total
sensory
systems
(TOT)
62.59
7.88
52.66
6.66
36.27
**
.000
.320
Social
participation
(SOC)
65.37
10.10
52.34
7.68
40.83
**
.000
.347
Planning
and
ideas
(PLA)
62.61
9.80
50.05
7.93
38.80
**
.000
.335
**
p
<
.01.
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
207

F
(8,70)
=
16.45;
p
=
.000;
h
p2
=
.653).
As
shown
in
Table
5,
in
all
cases,
the
teachers
of
the
children
in
the
ASD
Group
evaluated
their
pupils’
characteristics
of
sensory
processing,
social
participation
and
praxis
as
significantly
more
dysfunctional
than
the
teachers
of
the
children
in
the
Comparison
Group.
The
greatest
differences
were
obtained
on
the
subscales
of
Social
Participation,
Touch,
Total
Sensory
Systems,
Planning
and
Ideas,
and
Hearing
(on
all
of
them,
h
p2
exceeded
the
value
of
0.4).
When
we
analyzed
the
percentage
of
scores
obtained
by
each
group
in
each
of
the
three
SPM
interpretative
ranges
(Typical,
Some
Problems
and
Definite
Dysfunction)
in
the
classroom
environment
(see
Fig.
2),
we
noted
first
that
70–90%
of
the
Comparison
Group
obtained
scores
within
the
Typical
range,
while
a
small
percentage
obtained
scores
within
the
Some
Problems
and
Definite
Dysfunction
ranges
(e.g.
15.8%
in
Total
Sensory
Systems,
23.7%
in
Social
Participation,
and
28.9%
in
Planning
and
Ideas).
However,
the
ASD
Group
obtained
a
percentage
of
scores
within
the
Typical
range
that
varies
greatly
depending
on
the
subscale
assessed,
with
Social
Participation
showing
the
lowest
percentage
(7.3%)
and
body
awareness
the
highest
percentage
(63.4%)
of
cases
within
the
Typical
range.
Regarding
the
scores
obtained
within
the
Some
Problems
and
Definite
Dysfunction
ranges,
a
high
percentage
of
the
ASD
Group
obtained
these
scores
(e.g.
68.3%
in
Total
Sensory
Systems,
92.7%
in
Social
Participation,
and
85.4%
in
Planning
and
Ideas).
Of
the
different
sensory
systems,
the
highest
percentage
of
dysfunction
in
the
ASD
Group
was
found
for
Touch
(in
78%
of
cases),
according
to
the
information
reported
by
the
teachers
of
these
children.
3.3.
Intra-group
differences
in
sensory
processing,
social
participation
and
praxis
The
MANOVA
performed
to
compare
the
parent
report
with
the
teacher
report
in
the
Comparison
Group
did
not
reveal
statistically
significant
differences
between
the
two
informants
(Wilk’s
Lambda
(
l
)
=
.686;
F
(8,30)
=
1.72;
p
=
.136;
h
2
=
.314)
whilst
the
MANOVA
performed
to
compare
the
parent
report
with
the
teacher
report
in
the
ASD
Group
did
reveal
statistically
significant
differences
between
the
two
informants
(Wilk’s
Lambda
(
l
)
=
.496;
F
(8,33)
=
4.20;
p
=
.001;
h
2
=
.504).
As
shown
in
Table
6,
these
differences
were
found
in
the
Social
Participation,
Touch,
and
Planning
and
Ideas
subscales,
with
the
teachers
reporting
higher
dysfunctions
than
the
parents
in
all
three
cases.
Fig.
1.
Percentages
of
scores
obtained
in
the
home
environment.
Comparison
Group
=
1
and
ASD
Group
=
2.
Table
5
T-score
means,
standard
deviations
and
F-values
for
SPM–main
classroom
form
subscales
for
ASD
and
Comparison
Groups.
ASD
Group
Comparison
Group
F
(1,77)
p
h
p2
M
SD
M
SD
Vision
(VIS)
62.51
7.53
53.92
9.21
20.74
**
.000
.212
Hearing
(HEA)
62.75
9.21
48.68
8.01
52.15
**
.000
.404
Touch
(TOU)
64.90
7.79
49.71
7.94
73.64
**
.000
.489
Body
awareness
(BOD)
58.87
8.67
49.47
7.04
27.77
**
.000
.265
Balance
and
motion
(BAL)
57.71
8.80
47.58
8.09
28.24
**
.000
.268
Total
sensory
systems
(TOT)
63.32
6.84
49.97
7.61
67.39
**
.000
.467
Social
participation
(SOC)
71.22
7.70
51.84
8.63
111.32
**
.000
.591
Planning
and
ideas
(PLA)
66.34
7.12
52.34
9.27
57.15
**
.000
.426
**
p
<
.01.
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
208

4.
Discussion
In
line
with
previous
studies
(Ben-Sasson
et
al.,
2009),
the
comparison
of
the
sensory
processing,
social
participation
and
praxis
characteristics
of
the
group
of
children
with
ASD
and
the
group
of
children
with
typical
development
revealed
a
greater
dysfunction
in
the
ASD
Group
on
all
the
subscales
of
the
SPM,
both
in
the
home
and
in
the
classroom
environments.
In
both
settings,
the
greatest
differences
were
obtained
on
the
Social
Participation
and
Planning
and
Ideas
subscales.
Moreover,
the
ASD
group
had
higher
percentages
of
cases
within
the
Some
problems
and
Definite
dysfunction
ranges
on
these
two
subscales.
This
result
was
expected,
since
the
two
diagnostic
criteria
for
ASD
(according
to
DSM-5)
are
‘‘persistent
deficits
in
social
communication
and
social
interaction
across
multiple
contexts’’
and
‘‘the
presence
of
restricted,
repetitive
patterns
of
behavior,
interests,
or
activities’’
(APA,
2013).
In
the
case
of
praxis,
‘‘poor
motor
planning
abilities
limit
the
ability
to
expand
play
repertoires
or
engage
with
others,
and
they
should
be
taken
into
consideration
when
attempting
to
understand
the
functional
deficits
of
ASD’’
(Mailloux,
2001).
The
high
impairment
obtained
on
these
high-level
integrative
functions
in
the
ASD
group
would
reinforce
the
idea
that
people
with
autism
have
major
cognitive
functioning
limitations
at
high
levels
of
information
processing
(De
Clercq,
1999;
Peeters,
1997).
According
to
the
Sensory
Integration
Theory,
these
impairments
in
social
participation
and
praxis
can
be
caused
or
exacerbated
by
a
specific
deficit
in
sensory
system
processing.
In
our
study,
in
both
settings,
the
sensory
processing
analysis
revealed
large
differences
between
the
ASD
Group
and
the
Comparison
Group
on
the
overall
measure
(Total
Sensory
Systems
score)
and
the
specific
sensory
processing
measures,
as
well
as
high
percentages
of
cases
within
the
Some
problems
and
Definite
dysfunction
ranges
in
the
ASD
Group.
Moreover,
in
this
group
the
analysis
of
different
sensory
modalities
revealed
that
the
most
affected
modalities
were
hearing
and
touch,
which
is
consistent
with
previous
research
(Ashburner
et
al.,
2008;
Kientz
&
Dunn,
1997;
Rogers
et
al.,
2003;
Tomchek
&
Dunn,
2007;
Wiggins
et
al.,
2009).
Fig.
2.
Percentages
of
scores
obtained
in
the
classroom
environment.
Comparison
Group
=
1
and
ASD
Group
=
2.
Table
6
T-score
means,
standard
deviations
and
F-values
for
ASD
group
on
SPM–home
and
main
classroom
forms.
SPM
–
home
SPM
–
main
classroom
F
(1,40)
p
h
p2
M
SD
M
SD
Vision
(VIS)
62.63
8.34
62.51
7.53
.01
.941
.000
Hearing
(HEA)
63.12
8.64
62.76
9.21
.07
.794
.002
Touch
(TOU)
59.76
9.20
64.90
7.79
10.11
**
.003
.202
Body
awareness
(BOD)
60.29
6.90
58.88
8.67
.91
.345
.022
Balance
and
motion
(BAL)
58.59
9.55
57.71
8.80
.31
.580
.008
Total
sensory
systems
(TOT)
62.59
7.88
63.32
6.80
.37
.548
.009
Social
participation
(SOC)
65.37
10.15
71.22
7.70
20.18
**
.000
.335
Planning
and
ideas
(PLA)
62.61
9.80
66.34
7.12
7.41
*
.010
.156
*
p
<
.05.
**
p
<
.01.
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
209

On
the
one
hand,
hearing
was
the
most
affected
sensory
modality
in
the
home
environment
and
one
of
the
most
affected
in
the
classroom
environment.
Hearing
is
characterized
by
low
sensory
adaptability,
so
that
an
auditory
stimulus
(a
sound),
even
if
repeated
or
predictable,
is
not
easy
to
get
used
to.
In
the
case
of
the
classroom
environment,
excessive
and
unpredictable
noise
is
common
in
modern
classrooms.
‘‘Academic
material
is
usually
presented
through
verbal
instruction,
which
is
by
nature
rapid
and
transient
and
thought
to
be
difficult
for
children
with
ASD
to
process’’
(Quill,
1997),
especially
in
the
presence
of
competing
background
noise
(Alcantara,
Weisblatt,
Moore,
&
Bolton,
2004).
On
the
other
hand,
in
the
case
of
touch,
our
study
showed
different
results
depending
on
the
context
in
the
ASD
group.
Touch
was
the
least
affected
sensory
modality
in
the
home
environment,
but
the
most
affected
one
in
the
classroom
environment.
Touch
is
characterized
by
high
sensory
adaptability.
Thus,
a
moderate
intensity
tactile
stimulus
presented
repeatedly
and
predictably
is
easy
to
get
used
to,
which
is
possibly
more
customary
in
the
home
environment.
However,
in
the
classroom,
children
are
often
seated
in
groups,
and
they
are
frequently
exposed
to
unpredictable
tactile
input,
which
may
even
be
invasive
for
them
(Dunn,
Myles,
et
al.,
2002;
Dunn,
Saiter,
et
al.,
2002).
Moreover,
a
child’s
confidence
and
spontaneity
is
usually
greater
at
home
than
at
school,
which
also
means
that
physical
proximity
to
people
in
the
family
environment
is
usually
greater
than
in
the
school
environment.
The
information
reported
by
parents
and
teachers
revealed
no
differences
in
the
Comparison
Group,
but
differences
were
found
in
the
ASD
Group.
In
line
with
our
hypothesis,
in
this
group
teachers
reported
greater
dysfunction
than
parents
did
on
the
Social
Participation,
Touch,
and
Planning
and
Ideas
subscales.
This
could
be
related
to
greater
demands
of
school
assignments,
teachers’
opportunities
to
compare
children’s
functioning
among
their
peers,
and
the
presence
of
certain
environmental
factors
in
the
classroom,
such
as
stimulation
overload
produced
by
excessive
noise
or
unpredictable
physical
contact
when
working
cooperatively
(Ashburner
et
al.,
2008).
Specifically,
although
in
both
settings
it
was
the
subscale
that
showed
the
greatest
dysfunction
in
the
ASD
group,
Social
Participation
dysfunction
was
higher
in
the
classroom
environment.
This
is
probably
due
to
the
fact
that
the
school
environment
is
a
highly
social
environment
where
there
are
different
people
who
are
less
known
and
trusted
people
by
the
child,
more
cues
and
implicit
social
rules
that
are
not
always
familiar
to
the
child,
and
generally
greater
unpredictability,
than
in
the
family
environment,
where
routines
are
usually
more
adapted
to
the
child’s
preferences
(Dunn,
Myles,
et
al.,
2002;
Dunn,
Saiter,
et
al.,
2002).
At
home,
greater
confidence
and
spontaneity
usually
mean
greater
proximity,
not
only
physical
but
also
social
and
emotional,
to
family
members.
This
closeness
would
also
justify
the
differences
in
touch
between
the
two
settings,
which
have
been
discussed
above.
In
the
case
of
Planning
and
Ideas,
although
it
is
highly
affected
in
both
settings,
in
the
school
environment
the
impairment
is
more
pronounced,
probably
because
in
this
context
the
child
has
to
deal
with
a
greater
number
of
situations
in
which
he
or
she
has
to
devise,
plan
and
execute
new
movements
(i.e.
in
yard
games,
in
physical
education
.
.
.).
However,
in
the
family
context,
the
activities
that
involve
movement
are
likely
to
be
more
automated
by
the
child
because
they
can
form
part
of
his
or
her
daily
routines.
In
short,
in
the
family
environment
children
usually
feel
more
comfortable
than
in
school,
and
they
are
more
spontaneous,
less
inhibited,
and
have
more
generative
capacity.
Therefore,
they
are
better
able
to
effectively
plan,
develop
and
engage
socially
with
others.
There
is
a
possibility
that
the
characteristics
of
the
TEACCH
classrooms
could
influence
the
ASD
Group
results.
However,
we
do
not
think
this
is
the
case
because
children
with
ASD
not
only
attend
these
specific
units,
but
they
also
spend
as
much
time
as
possible
in
their
regular
reference
classrooms.
TEACCH
classrooms
are
located
in
regular
schools
in
order
to
promote
children’s
inclusion,
which
means
that
the
classroom
characteristics
are
similar
in
both
groups,
as
they
are
exposed
to
a
large
amount
and
variety
of
sensory
stimuli,
and
they
are
required
to
participate
fully
in
each
activity.
In
summary,
on
the
one
hand,
the
children
with
ASD
in
this
study
showed
a
more
dysfunctional
sensory
processing
profile
than
the
Comparison
Group,
regardless
of
the
contextual
factors;
on
the
other
hand,
the
sensory
profile
differences
obtained
between
the
different
developmental
contexts
in
the
ASD
group
also
showed
unique
sensory
circumstances
in
each
environment.
The
context,
therefore,
is
an
important
factor
in
analyzing
the
sensory
profile
and
higher
integrative
functions
such
as
social
participation
and
praxis.
According
to
Brown
and
Dunn
(2010),
‘‘sensory
processing
patterns
have
both
universal
and
context-specific
qualities’’
in
children
with
autism.
Therefore,
it
seems
important
to
receive
information
from
both
parents
and
teachers
during
the
sensory
profile
assessment
process,
and
use
context-specific
assessments.
4.1.
Study
limitations
Our
study
presents
some
limitations.
First,
children
with
ASD
with
serious
behavioral
problems
(i.e.
aggressiveness)
or
very
low
cognitive
functioning
were
not
part
of
this
sample,
so
that
the
autism
spectrum
was
not
fully
represented.
Second,
there
is
a
lack
of
information
about
whether
children
in
the
ASD
Group
had
received
or
were
receiving
some
kind
of
intervention,
such
as
sensory
integration
therapy,
at
the
time
of
the
evaluation.
Third,
some
of
the
evaluation
instruments
we
used
(SPM
and
GARS-2)
were
reported
measures.
Although
these
instruments
have
good
psychometric
properties,
they
are
subjective
measures
that
can
lead
to
possible
biases.
Fourth,
in
most
cases
the
SPM
–
Home
Form
was
filled
out
by
mothers,
and
only
a
small
percentage
were
answered
by
fathers.
Likewise,
regarding
teachers,
the
SPM
–
Main
Classroom
Form
was
filled
out
by
females
in
nearly
all
cases.
This
could
limit
the
reach
of
the
results
because
it
did
not
allow
us
to
analyze
possible
differences
between
mothers’
and
fathers’
reports
or
between
male
and
female
teachers’
reports.
Fifth,
this
research
used
cross-sectional
data
and
did
not
study
the
variables
over
time.
Sixth,
this
study
did
not
include
a
comparison
group
with
a
different
psychological
disorder,
so
that
we
cannot
definitively
conclude
that
the
group
differences
were
specific
to
autism.
M.I.
Ferna
´ndez-Andre
´s
et
al.
/
Research
in
Developmental
Disabilities
38
(2015)
202–212
210

4.2.
Conclusion,
practical
implications
and
general
recommendations
for
future
research
This
study
provides
an
overview
of
alterations
in
sensory
processing
and
higher
integrative
functions
shown
by
children
with
ASD,
providing
evidence
that
sensory
processing
patterns
have
both
universal
and
context-specific
qualities.
However,
it
would
be
advisable
to
assess
each
particular
case
in
order
to
conduct
an
individualized
and
tailored
intervention
according
to
the
needs
of
each
child.
Thus,
interviews
with
parents
and
teachers
should
be
complemented
with
clinical
observations
in
natural
settings.
Alterations
in
sensory
processing,
therefore,
require
specific
interventions
tailored
to
the
particularities
of
each
context
and
programmed
by
qualified
occupational
therapists.
Bogdashina
(2003)
makes
some
recommendations
for
the
implementation
of
this
type
of
intervention,
aimed
at
effectively
managing
sensory
stimulation
and
improving
communication
skills
(Bogdashina,
2005).
Sensory
difficulties,
especially
in
the
auditory
and
tactile
processing
of
children
with
ASD,
are
often
associated
with
attention
and
learning
difficulties
in
the
classroom.
They
may
be
reduced
by
using
visual
strategies
to
lessen
overreliance
on
verbal
instructions,
improving
classroom
acoustics,
enhancing
the
salience
of
instructions
while
minimizing
competing
input,
increasing
the
predictability
of
activities,
presenting
information
at
a
reduced
pace,
introducing
interventions
that
reduce
unpredictable
tactile
input
and,
in
general,
simplifying
classroom
sensory
environments
(Ashburner
et
al.,
2008).
Future
research
on
sensory
processing
in
children
with
ASD
should
also
consider
certain
variables
that
can
influence
the
perceptions
of
parents
and
teachers,
such
as
parental
stress,
personality
characteristics
or
the
educational
styles
used.
The
instrument
used
(SPM)
makes
it
possible
to
compare
sensory
processing
performance
in
different
contexts,
in
addition
to
obtaining
the
degree
of
dysfunction
on
each
subscale
and
assess
higher
processes.
However,
if
a
detailed
item-by-item
analysis
is
not
performed,
the
SPM
does
not
provide
an
overall
score
that
includes
the
type
of
sensory
dysfunction,
that
is,
whether
the
child
shows
hyper-
or
hypo-sensitivity
or
sensation
seeking.
Conversely,
the
sensory
profile
(Dunn,
1999),
provides
information
about
both
the
degree
and
type
of
dysfunction,
but
it
does
not
provide
social
participation
and
planning
or
praxis
measures.
Furthermore,
differences
in
the
structures
and
scoring
systems
of
the
questionnaires
make
it
difficult
to
compare
performance
in
different
developmental
settings.
Therefore,
in
future
research,
and
especially
in
clinical
practice,
it
may
be
useful
to
use
both
instruments
to
assess
the
type
and
degree
of
sensory
alterations
in
different
settings.
Conflict
of
interest
statement
The
authors
state
no
conflict
of
interest
in
the
current
study.
Acknowledgements
The
authors
thank
the
families
and
the
teachers
for
their
participation
in
this
research
and
the
Generalitat
Valenciana
Government
(Spain)
for
providing
the
required
financial
resources
[grant
number
GV/2014/066].
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