Cardiovascular Arousal in
Individuals With Autism
Matthew S. Goodwin, June Groden, Wayne F. Velicer,
Lewis P. Lipsitt, M. Grace Baron, Stefan G. Hofmann,
and Gerald Groden
Despite the hypothesized link between arousal and behavior in
persons with autism, there is a lack of idiographic research that
directly assesses arousal responses to novel stimuli or social situations in this population. The current study used heart rate as
a measure of sympathetic activity to compare arousal responses
to the presentation of potentially stressful situations in five persons with autism and five age- and sex-matched typically developing individuals. Findings revealed that the group with autism
showed significant responses to stressors only 22% of the time
compared to the typically developing group, which showed significant responses 60% of the time. Interpretation of these results and methodological considerations for future research on
arousal in persons with autism are discussed.
A
ccording to the Diagnostic and Statistical Manual of
Mental Disorders–Fourth Edition (DSM-IV; American
Psychiatric Association, 1994), autism is characterized by qualitative impairments in socialization, communication, and circumscribed interests, including stereotypical
behavior patterns and behavioral rigidity to changes in routines. Although these symptomatic features are well established, it is unclear whether their origin lies simply in the
absence of appropriate social skills and behavioral flexibility or
arises from a qualitative difference in physiological arousal associated with these abilities.
There is currently little research addressing the role of
physiological arousal in autism despite earlier suggestions that
neurophysiological factors implicated in the disorder can cause
or contribute to significant problems in modulating arousal to
social and sensory stimuli that are novel or unpredictable
(Dawson, 1991; Dawson & Lewy, 1989; Kinsbourne, 1987;
Ornitz, 1989; Ornitz & Ritvo, 1968), resulting in behavioral
and physiological response patterns of either overarousal (Hutt,
Hutt, Lee, & Ounsted, 1964) or underarousal (DesLauriers
& Carlson, 1969). According to these arousal modulation
theories of autism, both anxious and agitated responses characteristic of overarousal and passivity and lethargy characteris-
tic of underarousal can interfere with this population’s ability
to attend to, process, and interact with the environment and
can result in the failure to learn normative behaviors and skills
from other people (Lord & McGee, 2001; Prizant, Wetherby,
Rubin, & Laurent, 2003; Siegel, 2003).
Despite the hypothesized link between arousal and behavior in persons with autism, there is a lack of idiographic research that directly assesses this population’s arousal responses
to novel stimuli or social situations. In an effort to systematically evaluate arousal responses in persons with autism, the present article reviews research on stress, stress-related anxiety,
and physiological arousal and experimentally compares arousal
responses to identified environmental stressors in five individuals with autism and five age- and sex-matched typically
developing children.
Stress, Anxiety, and Autism
A stressor is any stimulus or circumstance that compromises an
individual’s physical or psychological well-being (Lazarus &
Folkman, 1984) and that requires an individual to make an adjustment (Selye, 1956). The consequences of stressors within
an individual are collectively called the stress response. The stress
response typically relates to three periods of interaction between the stressor and the individual’s response: (a) before the
stressful event occurs, (b) during the stressor, and (c) after the
stressor, when the individual may experience some of the residual effects of the event.
Stress and Autism
Literature suggests that many of the behaviors associated with
autism are related to stress, as stressful events frequently
precipitate the maladaptive behavior problems seen in this
population, such as aggression, self-injury, tantrums, and destruction of property (Groden, Cautela, Prince, & Berryman,
FOCUS ON AUTISM AND OTHER DEVELOPMENTAL DISABILITIES
VOLUME 21, NUMBER 2, SUMMER 2006
PAGES 100–123
VOLUME 21, NUMBER 2, SUMMER 2006
101
1994; Prior & Ozonoff, 1998). Stereotypic behaviors including echolalia, twirling, rocking, flicking, and hand flapping are
also found to increase when this population is exposed to
events commonly defined as stressors in the typical population
(Howlin, 1998; Hutt & Hutt, 1968).
Characteristics of persons with autism, including communication (e.g., Lord & Paul, 1997) and socialization deficits
(e.g., Mundy & Stella, 2000), sensory problems (e.g., Baranek, 2002), and deficits in executive function (e.g., Rogers
& Bennetto, 2000), may also make this population exceedingly vulnerable to stressors and limit their ability to cope
(Groden, Cautela, Prince, & Berryman, 1994). Ineffective
coping to stressors can lead to anxiety, and research suggests
that anxiety is more prevalent in persons with autism, Asperger syndrome (AS), and Pervasive Developmental Disorder–
Not Otherwise Specified (PDD-NOS) than in individuals who
are typically developing, behaviorally disordered, or learning
impaired. For example, Muris and colleagues (1998) interviewed parents of 44 children with either autism or PDD-NOS
using the Anxiety Disorders section of the Diagnostic and Statistical Manual of Mental Disorders–Third Edition-Revised
(DSM-III-R; American Psychiatric Association, 1987) and found
that 84.1% met criteria for an anxiety disorder. In a similar
study, Kim et al. (2000) conducted standardized interviews
with parents of 59 children with either autism or AS and found
a greater rate of anxiety in this group compared to a normative sample of 1,751 typical children from the community.
Green et al. (2000) compared the psychological comorbidity
of 29 individuals with AS to age-matched adolescents with
a conduct disorder and found significantly higher levels of
anxiety in the AS group. Findings from this study also revealed
that 35% of the children with AS met the International
Statistical Classification of Diseases and Related Health
Problems–Tenth Revision (ICD-10; World Health Organization, 1992) criteria for generalized anxiety disorder and 10%
met criteria for a specific phobia. In another study, Gillot et al.
(2001) found that 15 children with high-functioning autism
scored higher on measures of anxiety than both age-matched
children with specific learning impairments and typically developing children. Lastly, Bellini (2004) examined anxiety in
41 adolescents with either high-functioning autism, AS, or
PDD-NOS and found that 49% of the sample met criteria for
social anxiety.
Evidence also suggests that children with developmental
disabilities, including those with autism, are more fearful than
typically developing children (Evans, Canavera, Kleinpeter,
Maccubbin, & Taga, 2005; Knapp, Barrett, Groden, & Groden, 1992; Matson & Love, 1990). Some of the most common fears identified for children with autism in these studies
were associated with noises, presence of other people, and the
dark. Individuals with autism have also been shown to exhibit
panic-like levels of discomfort in response to environmental
changes (Steingard, Zimnitzky, DeMaso, Bauman, & Bucci,
1997).
Physiological Arousal and Autism
The reviewed research suggests that stressful events are associated with behavioral challenges and anxiety in persons with
autism. However, given this population’s difficulties identifying and describing their feelings through self-report (Hill,
Berthoz, & Frith, 2004), traditional assessments of stress that
utilize verbal communication (e.g., interviews, paper/pencil
tests) have limited use in persons with autism. Contemporary
researchers have attempted to overcome these unreliable selfreports and measure stress in this population by focusing on
physiological reactivity during rest and performance on a task.
Physiological Stress Responses
Widespread changes in the cardiovascular system, the immune
system, the endocrine glands, and brain regions involved in
emotion and memory are activated when an organism is
aroused by a stressor (Sapolsky, 1998). These physiological actions are controlled primarily by the autonomic nervous system (ANS) and enable an organism to respond adaptively to a
stressor by preparing the body to fight or flee. The peripheral
part of the nervous system, the ANS controls smooth muscle,
cardiac muscle, and glands and includes both sympathetic and
parasympathetic branches. The sympathetic branch is dominant in emergency conditions and initiates widespread and
profound body changes, including acceleration in heart rate,
dilation of the bronchioles, discharge of adrenaline into the
bloodstream, inhibition of digestion, and elevation in blood
pressure. The parasympathetic branch contains chiefly cholinergic fibers that tend to induce secretion, increase the tone and
contractility of smooth muscles, and slow heart rate. In general, the sympathetic division is a catabolic system associated
with emergencies; the parasympathetic, an anabolic system
associated with vegetative processes. The sympathetic and
parasympathetic divisions of the ANS work in antagonistic
ways to maintain homeostasis: a dynamic equilibrium in which
continuous changes occur, yet relatively uniform conditions
prevail (Fox, 1996).
Autonomic defensive responding is thought to be an indicator of arousal characterized in part by accelerations in the
sympathetic nervous system, including heart rate (HR), respiration, and pupillary dilation, that fail to habituate to environmental stimuli of high intensity (Lacey, 1967). As such, it
is thought to be an adaptive strategy that enables an organism
to avoid or escape the potential dangers of threatening stimuli
(Stern, Ray, & Quigley, 2001). Autonomic defensiveness to
environmental stimulation has been observed previously in persons with autism. Cohen and Johnson (1977) measured cardiovascular reactivity during a variety of attention-demanding
tasks in 10 individuals with autism and age-matched typical
controls. Their tasks were designed to elicit either outward direction of attention (and intake of sensory input) or inward direction of attention (and relative rejection of external sensory
FOCUS ON AUTISM AND OTHER DEVELOPMENTAL DISABILITIES
102
input). Results indicated that the group with autism had a tendency to reject external sensory input and elicit higher mean
blood flow and lower peripheral vascular resistance. In a
follow-up study, Kootz and Cohen (1981) measured HR,
mean blood flow, and peripheral blood flow in 14 individuals
with autism and 16 typical boys while resting, during social interaction, and while engaged in a reaction-time task. Findings
revealed that the individuals with autism had elevated HR responses during the entire session and failed to show cardiovascular changes with sensory intake. Finally, Kootz, Marinelli,
and Cohen (1982) studied 16 individuals with autism by measuring blood pressure and HR during a reaction-time task,
social interaction, and at rest. In this observation, higher functioning individuals with autism displayed a normal pattern of
cardiovascular responses to sensory intake, whereas lower
functioning individuals showed increased cardiovascular reactivity and rejection of external sensory stimuli.
Additional investigations have found that individuals with
autism, compared to persons who are typically developing,
generally respond with increased sympathetic tone at baseline
(Ming, Julu, Brimacombe, Connor, & Daniels, 2005) and
when exposed to environmental stimulation (Angus, 1970;
Lake, Ziegler, & Murphy, 1977; Palkovitz & Wiesenfeld,
1980; Zahn, Rumsey, & van Kammen, 1987). Other studies,
however, have found little to no differences between groups
during experimental demands for socialization, attention, or
habituation (Althaus, Mulder, Mulder, Aarnoudse, & Minderaa, 1999; Graveling & Brooke, 1978; Hutt, Forrest, &
Richer, 1975; MacCulloch & Williams, 1971; Sigman, Dissanayake, Corona, & Espinosa, 2003; Stevens & Gruzelier,
1984; Toichi & Kamio, 2003; van Engeland, 1984). Only one
study has found lower than normal arousal levels in persons
with autism responding to social demands (DesLauriers &
Carlson, 1969).
Although these findings suggest some arousal differences
in persons with autism, it is difficult to interpret this body of
research due to methodological problems. For instance, most
of these studies were conducted prior to the publication of the
DSM-III-R criteria for autism, calling into question the validity of participant diagnoses. The physiological equipment used
in the majority of these investigations was antiquated, likely
contributing to participant discomfort, movement artifact,
and equipment failures that resulted in a loss of data. Few of
these studies incorporated a large sample of novel situations or
stimuli to elicit significant arousal responses, and many failed
to include a baseline measure from which to compare physiological reactivity. Finally, few studies reported on or controlled
for background factors that can affect arousal responses, including comorbid psychological disorders, the participant’s
use of pharmaceuticals, and general cardiovascular functioning.
To control for some of the methodological problems associated with previous ANS studies of arousal in persons with
autism, we conducted two feasibility studies for telemetrically
assessing cardiovascular arousal to environmental stressors in
individuals with autism. Groden et al. (2005) telemetrically
recorded HR in 10 individuals ranging in age from 13 to 37
years (M = 24 years) who were positively identified with either
autism or PDD-NOS. Cardiovascular responses were recorded
at baseline and then while the participants engaged in four potentially stressful situations adapted from the Stress Survey
Schedule for Persons with Autism and Developmental Disabilities (SSS; Groden et al., 2001). The SSS is a psychometrically
sound survey instrument for rating the severity of perceived
stress reactions to commonly identified stressors in the lives of
persons with autism and developmental disabilities. It contains
49 items/situations that relate to eight dimensions of stress,
including changes and threats, anticipation/uncertainty, unpleasant events, pleasant events, sensory/personal contact,
food-related activity, social/environment interactions, and
ritual-related stress. The potentially stressful situations adapted
from the SSS used in the study included losing at a game, eating a preferred food, having a change in staff, and having unstructured time. Using interrupted time series analysis, the
data for each participant were examined to see if mean HR responses were significantly different during each stressor phase
compared with mean HR during baseline. Results illustrated
good compliance with the HR monitor and arousal to all four
stressors in some of the participants.
In an effort to provide a wider sample of potential stressors that can elicit significant arousal responses in this population, Goodwin et al. (2004) repeated the experimental design
and analysis plan from Groden et al. (2005) in five individuals with autism ranging in age from 12 to 20 years (M = 15
years). Cardiovascular reactions were assessed while the participants engaged in three previously untested stressors from
the SSS, including exposure to a loud noise, engagement in a
difficult task, and attending to a remote control robot (an unpredictable stimulus). This study also used a more sophisticated, wireless HR monitor (LifeShirt, Vivometrics, Inc.) that
records concomitant motor movements. Results illustrated
that participants tolerated the new ambulatory monitor and
showed some significant arousal responses to all three added
stressors.
The present investigation sought to further replicate the
measurement protocol from Groden et al. (2005) and Goodwin et al. (2004) and control for some remaining methodological problems associated with previous ANS assessments
of arousal in persons with autism. Controlling for background
factors that can affect cardiovascular responses, including comorbid psychological disorders, use of pharmaceuticals, and
general cardiovascular functioning, the current study experimentally compared arousal responses to identified environmental stressors in five individuals with autism and five
age- and sex-matched typically developing children. A series
of 10 single-subject time series designs was used. The singlesubject designs consisted of 14 phases where resting tasks alternated with potentially stressful tasks. Sessions began with a
baseline phase. After the baseline phase the participants engaged in six potentially stressful situations. The potentially
VOLUME 21, NUMBER 2, SUMMER 2006
103
stressful situations alternated with rest phases. In addition, a
physical exertion phase was used to ensure that participants
could demonstrate an increase in HR significantly greater than
baseline. Given the reviewed literature on stress, stress-related
anxiety, and ANS arousal findings in persons with autism, it
was hypothesized that the group with autism would have significantly greater cardiovascular reactivity, as compared to
baseline, to a greater number of environmental stressors than
the group of typically developing peers.
Method
Participants
Two groups of children with parental consent participated in
this study. The first group consisted of five males with autism,
none of whom were included in the feasibility studies described earlier. They ranged in age from 8 to 18 years (M =
13.8, SD = 4.24) and were recruited from the Groden Center, a day program serving behavioral and academic needs of
children with developmental disabilities. Diagnoses were made
by a licensed psychologist familiar with autism using DSM-IV
guidelines, the Childhood Autism Rating Scale (CARS;
Schopler, Reichler, & Renner, 1986), and previous psychiatric
reports. Participant cognitive abilities as assessed either by
standardized intelligence measures (e.g., Stanford-Binet Intelligence Scale–Fourth Edition [Thorndike, Hagen, & Sattler,
1986]; Leiter International Performance Scale–Revised [Roid
& Miller, 1997]) or scales of cognitive development (e.g.,
Bayley Scales of Infant Development–Second Edition [Bayley,
1993]) ranged from 24 to 38 (M = 31) and 5 months to 24
months, respectively. A familiar staff person also completed a
CARS for each participant with autism. Scores on the CARS
ranged from 31.5 to 43.5 (M = 39), placing the sample in the
moderately to severely autistic range. Four of the five participants with autism used spoken language as their primary
method of communication, and one participant used sign language. The second group was composed of five typically
developing, chronological age- and sex-matched individuals.
Typically developing participants were children of staff members at the Groden Center recruited from advertisements
posted at the center. None of the participants in either group
were prescribed any psychiatric medications and none had
documented comorbid disorders (e.g., attention-deficit/
hyperactivity disorder, obsessive-compulsive disorder, seizure
disorder) at the time of the study. Typically developing participants and participants with autism were also assessed for high
blood pressure using diastolic and systolic measures and found
to be normotensive (< 90 mmHg diastolic blood pressure).
Characteristics of the 10 participants are presented in Table 1.
Setting
Participants were seated in a comfortable chair in a soundattenuated room with low-level incandescent lighting. A oneway mirror provided discrete viewing capabilities from an
adjacent observation room. A familiar person accompanied the
participants to increase comfort with the setting and experimental phases.
Instruments
Cardiovascular responses were recorded using the LifeShirt
(Vivometrics, Inc.), a noninvasive telemetric recording device
that continuously (i.e., beat-to-beat) stores electrocardiograph
(ECG) data on a portable battery-powered electronic recorder
TABLE 1
Participant Characteristics
Age
(years)
Sex
Diagnosis
Primary method
of communication
Diastolic
pressure
Systolic
pressure
Cognitive
development/IQ
CARS
Total score
Autism
M.L.
J.L.
S.E.
M.C.
A.F.
8
10
16
17
18
Male
Male
Male
Male
Male
Autism
Autism
Autism
Autism
Autism
Verbal
Verbal
Verbal
Verbal
Sign language
58
64
84
70
66
102
110
136
128
124
32b
5 mo.a
38b
18–24 mo.a
24c
36
43.5
31.5
39
42.5
Typically developing
B.A.
C.N.
D.P.
D.V.
S.M.
8
10
16
17
18
Male
Male
Male
Male
Male
—————-
—————-
68
62
74
66
72
96
106
106
98
118
Participant
Note. CARS = Childhood Autism Rating Scale (Schopler, Reichler, & Renner, 1986).
a
Bayley Scales of Infant Development-Second Edition (Bayley, 1993). bStanford-Binet Intelligence Scale-Fourth Edition (Thorndike, Hagen, & Sattler, 1986). c Leiter
International Performance Scale-Revised (Roid & Miller, 1997).
FOCUS ON AUTISM AND OTHER DEVELOPMENTAL DISABILITIES
104
worn on the body (for description see Wilhelm, Roth, & Sackner, 2003). The LifeShirt also collected motor movements and
changes in posture positions using a dual-axis accelerometer
positioned on the anterior surface of the rib cage. Movement
data were obtained for the present study to control for HR responses attributable to physical demands. All of the information stored in the electronic recorder was downloaded to a PC
computer as an ASCII file and exported to Excel in preparation for statistical analyses.
Procedure
Preobservation Procedure. To increase comfort and
compliance with the stress assessment, each participant was introduced to the laboratory setting and heart monitor prior to
the experimental session. For the participants with autism, laboratory visits occurred once a day for a week prior to being
observed. For the typically developing participants, a minimum of 30 minutes prior to the assessment period was provided to try on the HR monitor, ask questions about the
device, and sit in the laboratory. Both groups of participants
were given a rationale for measuring HR appropriate to their
developmental level (e.g., “We are interested in seeing how
fast your heart beats when you are doing activities”). To accommodate for difficulties with changes in daily routines, par-
ticipants with autism had visits to the laboratory included on
their weekly classroom schedules. Finally, all participants chose
from a reward menu (food, game, or activity) at the end of
their preobservation visits to increase future participation.
Design. The observational design for each participant
consisted of 14 phases (see Table 2). Each session began with
a 5-minute baseline phase (sitting quietly with a familiar person). After the baseline phase the participants engaged in six
potentially stressful situations (see Stress Phases). These potentially stressful situations alternated with 2-minute rest phases
(sitting quietly with a familiar person). A physical exertion task
(riding a stationary bicycle for 2 minutes) was included to ensure that participants could demonstrate an increase in HR significantly greater than baseline. The order of presentation of
the stress phases was intentionally not counterbalanced to permit direct comparisons both between and within the typically
developing and autism groups.
Stress Phases. A wide sample of potential stressors was
selected to enable adequate opportunities for the participants
to elicit a cardiovascular stress response. The following stress
phases and accompanying stress dimensions identified in the
SSS (Groden et al., 2001) were included in the study because
they (a) included events that naturally occur in the environ-
TABLE 2
Observational Design and Stress Task Descriptions
Phase
Task
Task length
Task description
1
Baseline
5 min
With a familiar person, seated in a comfortable chair
2
Loud noise
2 min
With a familiar person, seated in a comfortable chair while a
vacuum cleaner runs outside the room
3
Rest
2 min
With a familiar person, seated in a comfortable chair
4
Remote robot
2 min
With a familiar person, seated in a comfortable chair while
a remote control robot navigates around the room
5
Rest
2 min
With a familiar person, seated in a comfortable chair
6
Unstructured time
2 min
Sitting in the room alone, given no other instructions than
“We will be back in 2 minutes”
7
Rest
2 min
With a familiar person, seated in a comfortable chair
8
Eating preferred food
2 min
With a familiar person, given preferred food to eat
9
Rest
2 min
With a familiar person, seated in a comfortable chair
10
Difficult task
2 min
With a familiar person, seated in a comfortable chair and
asked to mimic how the familiar person folds a towel
11
Rest
2 min
With a familiar person, seated in a comfortable chair
12
Change in staff
2 min
Familiar person leaves and person unfamiliar to the
participant sits in the room
13
Rest
2 min
With a familiar person, seated in a comfortable chair
14
Physical exertion
2 min
With a familiar person, riding a stationary bicycle
Transition
Time between tasks
Stress survey domain
Sensory/personal contact
Anticipation/uncertainty
Anticipation/uncertainty
Pleasant event
Changes/threats
Unpleasant event
VOLUME 21, NUMBER 2, SUMMER 2006
105
ment; (b) could be replicated in an experimental setting;
(c) consist of physical, social, and cognitive stimuli that overlap considerably with the problems of socialization, communication, and behavioral rigidity characteristic of persons with
autism; and (d) were shown to elicit increased heart activity
in the two feasibility studies (Goodwin et al., 2004; Groden
et al., 2005). The stress phases included were as follows:
1. Loud noise (sensory/personal contact): with a familiar
person, seated in a comfortable chair while a vacuum
cleaner runs outside the room.
2. Remote robot (anticipation/uncertainty): with a familiar
person, seated in a comfortable chair while a remotecontrol robot navigates around the room.
3. Unstructured time (anticipation /uncertainty): sitting in
the room alone, given no other instructions than “We
will be back in 2 minutes.”
4. Eating a preferred food (pleasant event): with a familiar
person, seated in a comfortable chair and given preferred
food to eat.
5. Difficult task (changes/threats): with a familiar person,
seated in a comfortable chair and asked to fold a towel
the same way the familiar person folds it. The familiar
person is instructed prior to the session to fold the towel
at a pace difficult for the participant to imitate. When the
participant folds the towel incorrectly, the familiar person
says, “Try it this way.”
6. Change in staff (unpleasant event): seated in a comfortable chair, familiar person leaves the room and a person
unfamiliar to the participant sits in the room.
7. Transition: an artifact of the study design consisting of
time between stressors and rest phases when the participant waited for the investigator to set up and begin the
subsequent phase.
Analysis
The data analyses consisted of 10 separate univariate time series analyses (Crosbie, 1993; Glass, Willson, & Gottman,
1975; Velicer & Colby, 1997; Velicer & Fava, 2003) performed on each participant for the dependent variable HR.
Time series analysis (TSA) requires repeated measurement at
equally spaced intervals over a large number of observations
and as such is a powerful longitudinal method for modeling
change over time. In TSA, sample size reflects the number of
observations over time rather than the number of subjects.
The telemetric HR monitor provided beat-to-beat HR values
generating approximately 3,500 data points per participant.
TSA was used to analyze these data given that repeated measurements over time on a single subject creates serial dependency that violates the statistical assumption that errors in the
data are independent across observations. TSA can calculate
an autocorrelation between adjacent observations and thus
transform serially dependent data to be independent. Once the
data has been transformed to be independent, TSA can em-
ploy traditional tests of statistical significance using the general
linear model.
Three waves of analyses were conducted for each participant using SAS Proc ARIMA (SAS Institute, 1988). The first
wave involved a graphical display of the data. The second wave
involved a model identification procedure to determine the
best-fitting ARIMA (p, d, q) model. For all 10 participants,
the general transformation approach of Velicer and McDonald
(1991) was used. This approach is the equivalent to assuming
a higher order (5+) autoregressive model and has been shown
to perform accurately in previous simulation studies (Harrop
& Velicer, 1985, 1990; Velicer & Colby, 2005). The third
analysis wave employed a within-subject, interrupted TSA to
determine whether mean HR during each potential stressor
phase was significantly different from mean HR during baseline. The data points used to calculate baseline were the last 3
minutes of the first 5 minutes of observation for each participant. The first 2 minutes of the baseline phase were excluded
a priori from the analysis for each participant to allow habituation to the telemetric apparatus and laboratory setting.
Results
Movement Data
Table 3 lists the mean motor movement results for the participants with autism and the typically developing group. The
motion component ranges from 0 for no movement to 50 for
running very fast. With the exception of the physical exertion
task, where motor movements were expected to increase, there
was very little movement detected across phases for either
group. In addition, for each participant motor movement was
included in the time series analysis as a time-varying covariate
to account for any explained variance in the HR data. The findings suggest that the subsequent reported HR results are virtually free from detected movement artifacts.
Heart Rate Data
Within Individual Differences: Autism Group. M.L.
(see Appendix A) showed statistically significant HR increases
from baseline (M = 106, SD = 7) to eating a preferred food
(M = 112, SD = 8), t(629) = 2.65, p < .01; difficult task
(M = 110, SD = 10), t(629) = 2.14 p < .05; and physical exertion (M = 122, SD = 11), t(629) = 6.58, p < .0001. J.L. (see
Appendix B) showed statistically significant HR increases from
baseline (M = 84, SD = 7) to remote robot (M = 92, SD = 19),
t(540) = 2.40, p < .05; unstructured time (M = 95, SD = 1),
t(540) = 2.11, p < .05; and physical exertion (M = 93, SD =
15), t(540) = 2.32, p < .05. S.E. (see Appendix C) only
showed statistically significant HR changes from baseline
(M = 113, SD = 3) to physical exertion (M = 125, SD = 10),
t(700) = 2.22, p < .05. M.C. (see Appendix D) only showed
statistically significant HR changes from baseline (M = 87,
FOCUS ON AUTISM AND OTHER DEVELOPMENTAL DISABILITIES
106
TABLE 3
Mean Movement Results for Autism and Typically Developing Participants
Baseline
Loud
noise
Remote
robot
Unstructured
time
Eating
food
Difficult
task
Change
in staff
Transition
Physical
exertion
0.41
0.19
0.12
0.29
0.41
0.33
0.13
0.19
0.61
0.25
0.30
0.34
0.41
0.14
1.48
0.33
0.54
0.38
0.28
0.21
2.14
0.40
0.68
0.34
0.42
0.27
0.50
0.38
0.38
0.77
0.86
0.72
0.59
0.56
0.70
0.90
0.55
0.25
0.65
0.35
0.54
0.72
0.53
0.35
0.64
0.74
0.60
1.45
1.44
1.09
1.49
1.13
1.32
1.09
0.14
0.09
0.10
0.12
0.27
0.34
0.23
0.05
0.19
0.22
0.12
0.48
0.22
0.03
0.14
0.20
0.46
0.39
0.21
0.18
0.21
0.29
0.27
0.38
0.18
0.23
0.27
0.27
1.24
0.71
0.89
0.84
0.72
0.88
0.22
0.41
0.22
0.04
0.25
0.23
0.63
0.80
0.20
0.23
0.35
0.44
2.22
2.60
0.94
1.17
1.09
1.60
M
SD
Autism
M.L.
J.L.
S.E.
M.C.
A.F.
Group
0.41
0.19
0.31
0.23
0.46
0.32
Typically developing
B.A.
C.N.
D.P.
D.V.
S.M.
Group
0.55
0.21
0.26
0.28
0.31
0.32
Participant
Note. Motion component ranges from 0 for no movement to 50 for running very fast.
SD = 5) to physical exertion (M = 110, SD = 10), t(563) =
10.37, p < .0001. A.F. (see Appendix E) showed statistically
significant HR changes from baseline (M = 90, SD = 8) to eating a preferred food (M = 103, SD = 11), t(601) = 5.63, p <
.0001; difficult task (M = 106, SD = 13), t(601) = 6.17, p <
.0001; change in staff (M = 97, SD = 13), t(601) = 3.22,
p < .001; transition (M = 101, SD = 12), t(601) = 5.18, p <
.0001; and physical exertion (M = 108, SD = 12), t(601) =
7.35, p < .0001.
Within Individual Differences: Typically Developing
Group. B.A. (see Appendix F) showed statistically significant
HR changes from baseline (M = 98, SD = 10) to remote robot
(M = 110, SD = 9), t(673) = 2.81, p < .01; unstructured time
(M = 119, SD = 7), t(673) = 4.13, p < .0001; eating a preferred food (M = 116, SD = 3), t(673) = 4.44, p < .0001; difficult task (M = 114, SD = 5), t(673) = 3.18, p < .01; change
in staff (M = 105, SD = 5), t(673) = 4.62, p < .0001; transition (M = 112, SD = 13), t(673) = 4.88, p < .0001; and physical exertion (M = 141, SD = 9), t(673) = 5.28, p < .0001.
C.N. (see Appendix G) showed statistically significant HR
changes from baseline (M = 89, SD = 6) to transition (M = 93,
SD = 9), t(571) = 2.18, p < .05, and physical exertion (M =
105, SD = 18), t(571) = 5.37, p < .0001. D.P. (see Appendix
H) showed statistically significant HR changes from baseline
(M = 57, SD = 5) to unstructured time (M = 60, SD = 6),
t(478) = 1.99, p < .05; eating a preferred food (M = 68,
SD = 5), t(478) = 4.57, p < .0001; difficult task (M = 70,
SD = 7), t(478) = 5.42, p < .0001; change in staff (M =
62, SD = 7), t(478) = 2.64, p < .001; transition (M = 65,
SD = 8), t(478) = 4.44, p < .0001; and physical exertion (M =
73, SD = 9), t(478) = 5.52, p < .0001. D.V. (see Appendix I)
showed statistically significant HR changes from baseline (M =
74, SD = 6) to eating a preferred food (M = 90, SD = 5),
t(484) = 5.32, p < .0001; difficult task (M = 89, SD = 5),
t(484) = 3.62, p < .0001; transition (M = 81, SD = 8), t(484) =
3.66, p < .0001; and physical exertion (M = 94, SD = 7),
t(484) = 6.87, p < .0001. S.M. (see Appendix J) showed statistically significant HR changes from baseline (M = 50, SD =
5) to unstructured time (M = 58, SD = 8), t(497) = 3.12, p <
.01; eating a preferred food (M = 67, SD = 7), t(497) = 3.68,
p < .001; difficult task (M = 64, SD = 8), t(497) = 3.20, p <
.01; change in staff (M = 56, SD = 7), t(497) = 2.06, p < .05;
transition (M = 62, SD = 13), t(497) = 3.63, p < .001; and
physical exertion (M = 78, SD = 11), t(497) = 6.25, p < .0001.
Within-Group Differences: Autism Group. Two of the
participants (S.E., M.C.) showed no significant HR changes
to any of the potentially stressful situations. Two other participants (M.L., J.L.) showed significant HR changes to only two
of the stressors. The remaining participant (A.F.) showed significant HR changes to four of the stressors. In all participants,
the physical exertion phase elicited significant mean HR responses greater than baseline.
Within-Group Differences: Typically Developing Group.
One participant (C.N.) showed significant HR changes to only
one stressor. One participant (D.V.) showed significant HR
changes to three stressors. One participant (S.M.) showed
significant HR changes to five of the stressors. Two participants (B.A., D.P.) showed significant HR changes to six of
the stressors. Again, in all participants, the physical exertion
phase elicited significant mean HR responses greater than
baseline.
VOLUME 21, NUMBER 2, SUMMER 2006
107
Between-Group Differences. Figures 1 and 2 illustrate
for each phase the mean HR results for each participant with
autism and each typically developing participant, respectively.
The mean HR for baseline in the autism group ranged from
84 bpm to 113 bpm with an overall group mean of 96 bpm
(SD = 12). The mean HR for baseline in the typically developing group ranged from 50 bpm to 98 bpm with an overall
group mean of 74 bpm (SD = 20). The mean HR for loud
noise in the autism group ranged from 87 bpm to 113 bpm
with an overall group mean of 97 bpm (SD = 11). The mean
HR for loud noise in the typically developing group ranged
from 52 bpm to 94 bpm with an overall group mean of 75
bpm (SD = 18). The mean HR for remote robot in the autism
group ranged from 86 bpm to 112 bpm with an overall group
mean of 96 bpm (SD = 11). The mean HR for remote robot
in the typically developing group ranged from 49 bpm to 110
bpm with an overall group mean of 75 bpm (SD = 26). The
mean HR for unstructured time in the autism group ranged
from 90 bpm to 113 bpm with an overall group mean of 100
bpm (SD = 10). The mean HR for unstructured time in the
typically developing group ranged from 58 bpm to 119 bpm
with an overall group mean of 80 bpm (SD = 25). The mean
HR for eating a preferred food in the autism group ranged
from 85 bpm to 113 bpm with an overall group mean of 100
bpm (SD = 13). The mean HR for eating a preferred food in
the typically developing group ranged from 67 bpm to 116
bpm with an overall group mean of 87 bpm (SD = 20). The
mean HR for difficult task in the autism group ranged from
87 bpm to 115 bpm with an overall group mean of 101 bpm
(SD = 13). The mean HR for difficult task in the typically developing group ranged from 64 bpm to 114 bpm with an overall group mean of 85 bpm (SD = 19). The mean HR for
change in staff in the autism group ranged from 85 bpm to
102 bpm with an overall group mean of 97 bpm (SD = 11).
The mean HR for change in staff in the typically developing
group ranged from 56 bpm to 105 bpm with an overall group
mean of 78 bpm (SD = 20). The mean HR for transition in
the autism group ranged from 87 bpm to 115 bpm with an
overall group mean of 100 bpm (SD = 12). The mean HR for
transition in the typically developing group ranged from 62
bpm to 112 bpm with an overall group mean of 83 bpm (SD
= 21). The mean HR for physical exertion in the autism group
ranged from 92 bpm to 125 bpm with an overall group mean
of 112 bpm (SD = 14). The mean HR for physical exertion in
the typically developing group ranged from 73 bpm to 141
bpm with an overall group mean of 98 bpm (SD = 27).
Discussion
The present study compared the cardiac responses of five relatively low-functioning persons with autism to five age- and
sex-matched typically developing individuals under repeated
conditions of environmental stressors. Based on arousal mod-
M.L.
J.L.
S.E.
M.C.
A.F.
Baseline Loud noise Remote Unstructured Eating Difficult task Change in Transition
preferred
staff
time
robot
foods
PHASE
FIGURE 1. Mean heart rate level by phase for autism group.
Physical
exertion
FOCUS ON AUTISM AND OTHER DEVELOPMENTAL DISABILITIES
108
B.A.
C.N.
D.P.
D.V.
S.M.
Baseline Loud noise
Remote Unstructured Eating Difficult task Change in Transition
preferred
staff
time
robot
foods
Physical
exertion
FIGURE 2. Mean heart rate level by phase for typical group.
ulation theories of autism (Dawson, 1991; Dawson & Lewy,
1989; Kinsbourne, 1987; Ornitz, 1989; Ornitz & Ritvo,
1968), reports of stressful events being associated with behavioral challenges (Groden et al., 1994; Howlin, 1998; Hutt &
Hutt, 1968; Prior & Ozonoff, 1998), and documented comorbid anxiety disorders in persons with autism (Bellini,
2004; Gillot et al., 2001; Green et al., 2000; Kim et al., 2000;
Muris et al., 1998), it was hypothesized that the group with
autism would show significant cardiovascular responses to a
greater number of stressors than the typically developing control group. However, the findings revealed just the opposite:
Out of the 35 opportunities for each group to show a significant mean HR response to a stressor (i.e., seven potentially
stressful phases × five participants), the group with autism
showed significant responses only 22% of the time (8 out of
35), compared to the typically developing group, which
showed significant responses 60% of the time (21 out of 35).
At first glance, these results suggest that the group of individuals with autism is less aroused by environmental stressors than the typically developing control group. However, the
diminished cardiovascular reactivity to potential stressors in
the group with autism may be related to their high basal HR
and reduced variance in responsivity (see Figure 3). On average, the participants with autism showed mean HR responses
approximately 20 bpm higher during baseline and nearly every
potentially stressful situation. The group with autism also
showed approximately half the amount of variance in HR responsivity compared to the typically developing group. These
data appear to replicate the previous findings of Cohen and
colleagues (Cohen & Johnson, 1977; Kootz & Cohen, 1981;
Kootz, Marinelli, & Cohen, 1982) and suggest that persons
with autism who have high basal HR are unable to elicit
significantly greater increases in cardiovascular reactivity to environmental stimulation. The diminished cardiovascular reactivity to environmental stressors suggests that the group with
autism was either overly aroused by the testing situation on the
whole (which included the same characteristics and staff that
may be stressful on a daily basis) or in a general state of autonomic defensiveness.
If the hypothesis is tenable that some individuals with
autism are in a general state of high autonomic arousal, then
it is of interest to identify the underlying mechanisms contributing to such responsivity. Although no one theory has
gained overwhelming support, several putative mechanisms
have been suggested. Ornitz (1989) speculated that dysfunctions in the neuronal networks in the brainstem, including the
diencephalon, can cause disordered sensory processing that result in problems of arousal modulation. Hutt and Hutt (1970)
hypothesized dysfunctions in sympathetic inhibitory control
mediated by the limbic system. Others have postulated dysfunctions in the central control of HR modulation (Graveling
& Brooke, 1978; Hutt, Forrest, & Richer, 1975; MacCulloch
VOLUME 21, NUMBER 2, SUMMER 2006
109
Autism
Typical
Baseline Loud noise Remote Unstructured Eating Difficult task Change in Transition Physical
preferred
staff
time
exertion
robot
foods
FIGURE 3. Average mean heart rate level by phase for autism and typical groups.
& Williams, 1971), including the vagus nerve (Althaus, Mulder, Mulder, Aarnoudse, & Minderaa, 1999). More recently,
the amygdala, which plays a central role in moderating fear and
anxiety (Davis & Whalen, 2001), is thought to be abnormal
in autism (Baron-Cohen et al., 2000; Schultz, Romanski, &
Tsatsanis, 2000; Sweeten, Posey, Shekhar, & McDougle,
2002), contributing to improper arousal regulation in this
population (Amaral, Bauman, & Mills Schumann, 2003).
Although biological preconditions leading to and behavioral observations indicative of overarousal are implicated in
autism, one must still reconcile the fact that physiological overarousal does not always replicate in this population. Some tentative reasons for this discrepancy have been offered by Zahn
(1986) in an early review of ANS arousal findings in autism:
(a) that most individuals with autism have chronically high levels of autonomic activity, but that a subgroup within the disorder may respond at normal levels; (b) that persons with
autism may exhibit heightened ANS activity only some of the
time; and (c) that physiological studies requiring interaction
with people or that create confusion about what the participant is being asked to do can cause study participants to exhibit high arousal. Clearly, all of these potential conditions can
vary depending on the experimental research design used, the
procedure for gaining compliance, and the sample studied.
Dawson and Lewy (1989) have also suggested that levels of
stimulation can vary across individuals with autism as a function of developmental level, degree of familiarity with the test-
ing situation, and biologically based individual differences, including severity of the disorder.
In light of these cautions, there are methodological
strengths and weaknesses associated with the present study’s
findings. First, several steps were taken to control for arousal
induced by the testing environment: (a) The preobservation
protocol enabled the participants with autism to sample the
laboratory setting and heart monitor repeatedly prior to the
observation; (b) a relatively noninvasive, wireless HR monitor
that can be worn underneath a garment was used; (c) observations were undertaken in a minimally stimulating (e.g.,
incandescent lighting, pattern-free walls and carpet), soundproof laboratory; and (d) a familiar person accompanied the
participants throughout the observational sessions. Second,
several steps were taken to control for arousal artifacts unrelated to the independent variables: (a) With the exception of
riding the stationary bicycle, participants were seated in a comfortable chair for the duration of the observation to minimize
HR increases associated with physical activity; (b) the HR
monitor recorded postural changes and motor movements and
inclusion of this data as a covariate in the statistical analyses
controlled for HR increases due to recorded physical activity;
and (c) participants in this study had normal blood pressure
measurements and were free of medications, ruling out the
possibility that their arousal responses were affected by abnormal cardiovascular systems or pharmacological agents. Finally,
a wide sample of potential stressors was used to provide mul-
FOCUS ON AUTISM AND OTHER DEVELOPMENTAL DISABILITIES
110
tiple opportunities for participants to elicit a stress response.
Sampling just one potentially stressful situation may or may
not have elicited significant physiological reactions across all
participants, enabling potentially erroneous conclusions about
arousal responses in this sample.
While these experimental controls attempt to minimize extraneous variables that can affect measurement of arousal responses in persons with autism, there are a few potential
confounds and limitations associated with the current study
that merit future research. For example, there were instances
across both the autism and control groups where significant
cardiovascular reactivity occurred during rest phases. A review
of the data suggests that these responses might be related to
(a) a carry-over effect from a previous stress condition, (b) cumulative arousal mediated by a participant’s relevant cognitions or emotions, or (c) participant reactivity to being
observed in an artificial setting.
In the present study, a carry-over effect seems evident in
the autism group for M.L., who showed significant HR responses during rest only after a significant response to a preceding stressor. While representing a potential threat to the
internal validity of the experimental stressors, this carry-over
effect suggests that arousal associated with a stressor can extend over time even when the stressful stimuli or situation is
removed. This phenomenon, if replicated in future studies,
may be of clinical interest as it demonstrates that some individuals with autism cannot self-regulate their arousal response
to a stressor in a timely manner.
Cumulative stress responses evidenced by increased cardiovascular reactivity in every previous and subsequent condition, typically toward the end of the observation, occurred for
A.F. in the autism group and B.A., D.P., D.V., and S.M. in the
control group. This pattern of responding may be related to
unobservable thoughts or feelings (e.g., memory of a previous
stimulating occasion, boredom, anticipation) that are themselves arousal producing. Although only speculative, this
hypothesis has some face validity given that this pattern of responding occurred primarily in the more cognitively able, typically developing group. It is also possible that these arousal
responses are not related to the environmental stressors per se,
but to the simple act of being monitored in a laboratory setting. For instance, three participants with autism (M.L., S.E.,
A.F.) and one typically developing individual (B.A.) had basal
HR, prior to any presentation of an experimental stressor,
equal to or greater than 90 bpm. A nurse on staff at the Groden Center reviewed the medical records of all the participants
to verify that no one had documented problems with cardiovascular functioning before entry into the study. Therefore, it
is unclear whether these basal rates are accurate estimates of
resting HR or whether they are artificially high in response to
being observed in an artificial setting. Future studies that deploy wireless HR monitors in the natural environment might
gather data from individuals with autism and indicate whether
the high basal HR and stress response patterns observed in the
current study are attributable to characteristics of the partici-
pants or environmental stressors, or simply to the act of being
observed in a simulated environment.
The individual differences found within the autism and
typically developing groups also demonstrate the advantages
and complexity inherent in interpreting single-subject data.
Nomothetic approaches that classify large, random groups of
people based on an average response statistic to find interindividual variation prevail in psychology. However, this approach often yields superficial understanding of any one
person because limited data are typically collected. In contrast,
idiographic methods (see Molenaar, 2004) that gather singlesubject data, such as those used in the present study, investigate a small sample of individuals in detail and focus on a
person’s uniqueness. Quantitative analysis of idiographic data
highlights intraindividual variation over time to gain a thorough and more subtle understanding of a few people to lead
to more general understanding of others. In this framework,
systematic replication (Barlow & Hersen, 1984) becomes the
basis for generalizability. Because the current study only included five individuals with autism, it is questionable whether
the observed HR results and accompanying interpretation of
the data would generalize to a large sample. Therefore, larger
sample sizes are needed in future studies to assure more accurate representation of response types in a notoriously heterogeneous population. Continuing research might also recruit
participants who have a greater range of functioning abilities
and might employ standardized, adaptive behavioral measures
that better identify individual differences by differentiating between high- and low-functioning individuals with autism, a
variable that Kootz and colleagues (1982) and Dawson and
Lewy (1989) suggest can mediate arousal responses.
Future studies might also make attempts to record and
correlate overt behavioral responding with underlying physiological functioning to determine if there is synchrony or dysynchrony across levels of measurement. Despite the general
finding of high HR in the participants with autism, anecdotal
observation of overt behavior in this study indicated only
minor signs of arousal. This is a potentially interesting happening that deserves more systematic study given that communication deficits characteristic of this population require
educators to make inferences about internal states from overt
behavioral responses. It may well be that some individuals with
autism look relatively calm overtly, but are experiencing significant physiological arousal covertly.
Finally, while HR is a robust measure of general physiological arousal, it is influenced by both sympathetic and
parasympathetic nervous system activities. Heart rate variability, on the other hand, allows more fine-grained analyses of
stress on cardiovascular arousal, including the assessment of
vasovagal tone. Physiological research supports the notion that
HR patterns are predominantly mediated via the vagus nerve
(Levy, 1984). Measures of vagal reactivity to sensory, visceral,
or cognitive challenges indicate the adaptive functioning of the
nervous system. Therefore, measures of cardiac vagal tone can
provide an important window into the central control of au-
VOLUME 21, NUMBER 2, SUMMER 2006
111
tonomic processes and by inference the central processes necessary for organized behavior. Future studies that employ such
data may determine if restricted autonomic flexibility (Porges,
1985) contributes to the cardiovascular overarousal found in
this study.
In sum, this study further explores the role that stress,
stress-related anxiety, and physiological arousal play in the behavior of individuals with autism. Continuing research that focuses on these constructs and addresses the methodological
considerations raised when using HR as a direct measure of
stress will be required to determine if qualitative differences in
arousal prevent this population from attending to, processing,
and interacting with their environment and learning normative behaviors and skills from other people. However, if replicated, the findings from this study have important assessment
and treatment implications for psychologists, educators, family members, and individuals with autism. For instance, heightened arousal might constrain the ability of persons with autism
to benefit from behavioral and social interventions that fail to
address this physiologic reactivity. If an individual with autism
is identified as being overaroused, stress reduction techniques
such as relaxation training (Cautela & Groden, 1978) and cognitive picture rehearsal (Groden, LeVasseur, Diller, & Cautela,
2002) might be used as preparatory steps to any further behavioral or academic instruction. This study also highlights the
promise of developing noninvasive, wireless technologies that
persons with autism can wear to monitor physiological stress
in real time, thus facilitating more effective ways for these individuals to communicate their arousal states and for educators and family members to respond appropriately.
ABOUT THE AUTHORS
Matthew S. Goodwin, MA, is the research coordinator at the Groden
Center, a day and residential treatment and education program serving children and youth who have developmental and behavioral difficulties. He is also a PhD candidate in behavioral science at the
University of Rhode Island. His research and clinical experience with
children with autism spectrum disorders focuses primarily on the assessment of behavioral and physiological responses using telemetric monitors
and digital video/editing systems. June Groden, PhD, is the director of
the Groden Center and is on appointment at Brown University and
the University of Rhode Island. Wayne F. Velicer is the co-director
of the Cancer Prevention Research Center and professor of psychology at
the University of Rhode Island. In behavioral statistics, his work has focused on factor analysis and component analysis, the application of time
series analysis to the behavioral sciences, and methods for measurement
development. Lewis P. Lipsitt, PhD, is professor emeritus of psychology,
medical science, and human development at Brown University. His
career-long interests have been in child behavior and development, sensory and learning processes of infants, risk-taking behavior in children
and adolescents, and crib death (SIDS). M. Grace Baron is professor of
psychology at Wheaton College in Norton, Massachusetts, and a consulting behavioral psychologist at the Groden Center. She is also a member of the Groden Center Research Team, studying biobehavioral aspects
of stress in autism. Stefan G. Hofmann, PhD, is an associate professor
of psychology at Boston University and editor of Cognitive and Behav-
ioral Practice. His current interests include the psychophysiology and
treatment of emotion and anxiety disorders. Gerald Groden, PhD, is
the cofounder of the Groden Center and is currently on appointment at
Brown University and the University of Rhode Island. Address: Matthew S. Goodwin, The Groden Center, Inc., 86 Mt. Hope Ave., Providence, RI 02906; e-mail: msgoodwin@earthlink.net
NOTES
1. Small amounts of food were used so that the entire portion of food
could be consumed in the time provided.
2. In the analyses, HR data was reduced to 5-second averages to facilitate graphical representation and statistical testing.
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APPENDIX A
Mean Heart Rate Level by Phase for M.L.
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APPENDIX B
Mean Heart Rate Level by Phase for J.L.
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APPENDIX C
Mean Heart Rate Level by Phase for S.E.
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APPENDIX D
Mean Heart Rate Level by Phase for M.C.
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APPENDIX E
Mean Heart Rate Level by Phase for A.F.
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APPENDIX F
Mean Heart Rate Level by Phase for B.A.
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APPENDIX G
Mean Heart Rate Level by Phase for C.N.
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APPENDIX H
Mean Heart Rate Level by Phase for D.P.
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APPENDIX I
Mean Heart Rate Level by Phase for D.V.
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APPENDIX J
Mean Heart Rate Level by Phase for S.M.