Neurodiversity literature review and correlational research study.

COGNITIVE, EMOTIONAL, AND LIFE EXPERIENCES OF AUTISTIC ADULTS 1
Cognitive, Emotional, and Life Experiences of Autistic Adults
by
Christine R. Glass
Dr. Ilie Vasilescu – Academic Advisor
Integrative Project Submitted to the Graduate School
In Partial Fulfillment of the Requirements for the Degree of
Master of Arts in General Psychology
Union College, Kentucky
December 2021

Abstract
Recent studies have highlighted the experiential differences of autistic people compared to
neurotypical people, as well as differences in phenotypic presentation between autistic males and
autistic females. A questionnaire regarding cognitive, emotional, and life experiences was given
to 291 adult participants, of which 57 identified as autistic. Our results confirm past findings
regarding experiential differences between autistic and non-autistic adults, including higher rates
of unemployment and increased risk of various forms of abuse experienced in the autistic
population. Our results did not indicate any significant differences between the cognitive,
emotional, or social communication experiences of autistic males and autistic females.
However, our data did reveal that autistic females are significantly more likely to experience
sensory difficulties than autistic males.
Keywords: neurodiversity, theory of mind (ToM), double empathy problem, systemizing,
masking in autism

Table of Contents
Review of Literature ....................................................................................................................... 6
Etiology....................................................................................................................................... 6
Theoretical Perspectives ............................................................................................................. 8
Intense World Theory ............................................................................................................. 9
Autism as a Disorder of High Intelligence ............................................................................. 9
“Pattern” Model .................................................................................................................... 10
Evolutionary Theories of Autism.............................................................................................. 10
Adaptive Model .................................................................................................................... 11
Byproduct Model .................................................................................................................. 11
Diametrical Model ................................................................................................................ 11
Life History Perspective Model............................................................................................ 12
Theory of Mind......................................................................................................................... 12
Sex Differences in Autism........................................................................................................ 13
ASD Employment..................................................................................................................... 15
Victimization Experiences........................................................................................................ 16
Hypotheses................................................................................................................................ 17
Method.......................................................................................................................................... 17
Participants................................................................................................................................ 17
Ethical Considerations .............................................................................................................. 18
Design ....................................................................................................................................... 18
Data Analysis............................................................................................................................ 19
Results........................................................................................................................................... 19

Hypothesis 1.............................................................................................................................. 22
Hypothesis 2.............................................................................................................................. 24
Hypothesis 3.............................................................................................................................. 27
Hypothesis 4.............................................................................................................................. 28
Discussion..................................................................................................................................... 29
Hypothesis 1.............................................................................................................................. 29
Hypothesis 2.............................................................................................................................. 31
Hypothesis 3.............................................................................................................................. 33
Hypothesis 4.............................................................................................................................. 33
Limitations................................................................................................................................ 34
Conclusion and Future Directions ............................................................................................ 35
References..................................................................................................................................... 36
Appendix A................................................................................................................................... 44
Appendix B................................................................................................................................... 50

Cognitive, Emotional, and Life Experiences of Autistic Adults
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by
impairments in social interactions and communication and restricted or repetitive behaviors or
interests (American Psychiatric Association, 2013). ASD is a heterogeneous condition with
patients showing widely variable combinations of symptoms, which is further compounded by a
broad range of cognitive abilities (Del Giudice, 2018). The Fifth Edition of the Diagnostic and
Statistical Manual of Mental Disorders (DSM-5) created the concept of the “spectrum” to
diagnose ASD, combining the DSM-IV’s previous disorders of pervasive developmental
disorder (PDD), autistic disorder, Asperger’s disorder, childhood disintegrative disorder, and
pervasive developmental disorder not otherwise specified (PDD-NOS) under the umbrella of
ASD. Severity is coded on three levels, and specifiers for the presence of intellectual disability
and language impairment are included. Concerns have been raised that the changes in diagnostic
criteria may prevent some autistic people (particularly older children, adolescents, adults, and
those with a former diagnosis of Asperger’s disorder) from receiving an accurate diagnosis
(Hodges et al., 2020).
The distinctive social behaviors observed in ASD include an avoidance of eye contact,
problems with emotional control or understanding the emotions of others, and restricted range of
interests or activities (Park et al., 2016). Atypical use of gestures, facial expressions, body
orientation, or speech intonation are common as are difficulties coordinating nonverbal
communication with speech (American Psychiatric Association, 2013). Executive functioning
difficulties are common among autistic people; however, researchers have found little evidence
that deficits in executive functioning are common in autistic children under the age of four which

suggests that executive functioning deficits may not necessarily be primary to the disorder, but
instead arise later as a result of social learning difficulties (Reser, 2011).
Review of Literature
Etiology
Several neuroanatomical abnormalities are associated with ASD. According to Dr.
Lorenza Culotta from Northwestern University (2020), the brain hemispheres of autistic people
have slightly more asymmetry than those of a non-autistic brain (Rossi, 2020). Brain overgrowth
in terms of both cortical size and extra-axial fluid have been indicated in autistic children
(Hodges et al., 2020). An underdeveloped cerebral cortex is believed to cause the connectivity
issues that occur in autistic brains. According to Dr. Jeffrey Anderson, professor of radiology at
the University of Utah, the brain of an autistic person has a tendency toward short-range over
connectivity and long-range under connectivity which explains why autistic people struggle with
tasks that require the assimilation of different parts of the brain, like social functioning. It also
explains why autistic people often excel at tasks that require focus of a specific brain region, like
paying attention to specific details and systemizing (Rossi, 2020).
A study conducted at King’s College in London reported changes in cerebellar volume in
autistic people. Impairments in social interaction and emotion recognition in autistic people
were linked to increased amygdala volume, relative to total brain volume. Abnormal cortical
growth patterns, abnormalities in cortical thickness, and disorganization of neurons across
cortical layers in autistic people were reported (Donovan & Basson, 2017). ASD patients tend to
have larger prefrontal lobes with thicker cortical areas and reduced gray matter in the anterior
cingulate cortex (ACC), medical prefrontal cortex (MPFC), and temporal regions (Del Giudice,
2018). Recent theoretical models suggest the need to consider ASD as a disorder of several

large-scale neurocognitive networks. White matter deficits are interpreted as a key factor of
“atypical connectivity” in autistic individuals leading to dis-connectivity in some regions and
over-connectivity in others. It is suggested that frontal lobe connections that are typically formed
during development are disrupted in ASD brains (Ecker, 2012). Autism is associated with a
smaller corpus collosum, accounting for the diminished connectivity between right and left-brain
hemispheres (Del Giudice, 2018).
Several neurochemical pathways have been implicated in ASD but studies to date have
not been successful in concluding the specific neurochemical interactions that cause the onset of
ASD symptoms. A 2020 study published in Brain Sciences indicated neurochemical
dysfunctions related to gamma aminobutyric acid (GABA), serotonin, dopamine, N-acetyl
aspartate, oxytocin, melatonin, Vitamin D, orexin, endogenous opioids, and acetylcholine
(Marotta et al., 2020). Evidence for patterns of upregulated glutamate and downregulated
GABA show consistency with the idea that autism is associated with an increased ratio of
excitation to inhibition in the modulation of cortical activity (Del Giudice, 2018).
ASD is understood to be caused by a complex interaction between genetics and the
environment and current heritability rates are estimated from 40 to 90 percent. To date,
hundreds of genes have been identified that contribute to the symptoms experienced by autistic
individuals but no specific autism gene has been specified. Large effect variants identified
involve genes that regulate brain connectivity and neural plasticity (Del Giudice, 2018).
Epigenetic alterations are likely to play a role in the expression of ASD as are genetic modifiers
such as single nucleotide polymorphisms and copy number variations (Rylaarsdam & Guemez-
Gamboa, 2019). Involvement of epigenetic mechanisms such as DNA methylation, histone
modification, and noncoding RNA have been indicated. In addition to epigenetic mechanisms,

the role of environmental agents that cause disease or developmental aberrations have been
investigated as potential contributors to ASD (Eshraghi et al., 2018). Although autism-linked
genes are typically expressed throughout the brain during prenatal development, there is
evidence that some genes in this cluster may be expressed at later stages in the amygdala,
hippocampus, and stratium (Del Giudice, 2018).
There are currently no clear biomarkers related to ASD and diagnosis is typically made
upon the fulfillment of descriptive criteria. Blood serotonin levels, urine melatonin levels, head
circumference, and digit ratio tests have been studied as potential future biomarkers but further
research is required to form conclusions (Bridgemohan et al., 2019).
ASD has an increased rate of several co-occurring genetic disorders compared to the
average population, including fragile X, tuberous sclerosis, Down syndrome, and Rhett
syndrome. Common co-occurring medical conditions include gastrointestinal disorders, dietary
restrictions, sleep disorders, obesity, and seizures. Common psychiatric co-occurring conditions
include anxiety, attention deficit/hyperactivity disorder (ADHD), post-traumatic stress disorder
(PTSD), obsessive compulsive disorder (OCD), and mood disorders (Hodges et al., 2020).
Large scale sequencing studies have revealed extensive genetic overlap between ASD and
schizophrenia, bipolar disorder, ADHD, OCD, and major depressive disorder (MDD)
(Rylaarsdam & Guemez-Gamboa, 2019).
Theoretical Perspectives
Several theoretical models have attempted to explain autism. In 1972, Tinbergen and
Tinbergen proposed that autism could be understood as a withdrawal reaction to intense fear and
stress caused by traumatic infantile experiences (Silverman, 2010). Advancements in the field of
autism have highlighted the weaknesses of these early theories; however, subsequent research

does suggest that children with autism and their parents are at high risk for developing insecure
attachment patterns. Additionally, research shows that the establishment of secure attachments
with autistic children by parents is a predictor of improved outcomes in autistic children
(McKenzie & Dallos, 2017).
Intense World Theory
The “Intense World Theory” proposes a view that autism is a result of amplified synaptic
plasticity that leads to enhanced learning and memory processing in some people. Proponents of
the Intense World Theory suggest that enhanced brain functioning lies at the heart of autism.
The theory is based upon the concept that hyper-functioning of local neural microcircuits which
are characterized by hyper-reactivity and hyper-plasticity cause autistic people to experience
hyper-perception, hyper-attention, hyper-memory, and hyper-emotionality. In contrast to
previous research regarding autism and empathy that emphasizes empathy deficits, Intense
World Theory proponents claim that the overly active amygdala that is common in autism causes
the autistic individual to feel emotions strongly and have the ability to experience intense
empathy, but may avoid doing so because it is too overwhelming (Markram & Markram, 2010).
Autism as a Disorder of High Intelligence
Recent studies report a positive genetic correlation between autism and mental ability.
Despite the fact that autism has been characterized, overall, by low IQ in the past, recent findings
indicate that alleles for autism overlap with alleles for high intelligence. Proponents of the
“autism as a disorder of high intelligence” hypothesis claim that autism etiology involves
enhanced, but imbalanced, components of intelligence. Convergent evidence supporting this
hypothesis include large brain size; fast brain growth; increased sensory and visual-spatial
ability; enhanced synaptic functioning; increased attentional focus; more deliberative decision-

making; and professional interests in science and engineering. Proponents of the theory suggest
that autism risk is mediated in part by high, but imbalanced, intelligence (Crespi, 2016).
“Pattern” Model
Crespi (2021) has also proposed the umbrella of “pattern” as a way to frame and unify the
autistic brain experiences. The “pattern” model highlights the autistic brain’s tendency to
maintain, generate, and process patterns as a unifying trait to define autism. In this context,
pattern is described as “spatially or temporally repeated configuration, with recurring, ordered, or
other predictable characteristics, and discernable interrelationships of components” (Crespi,
2021). This model is in line with previous autism research proposing that autism is a disorder of
high, but imbalanced, intelligence. Baron-Cohen (2020) postulates that autistic people are
typically “hyper-systemizers” who are adept at spotting novel “if and then” patterns but can
struggle with “tunnel vision”. He theorizes that the autistic person’s IQ influences whether the
target of the systemizing is concrete or abstract (Baron-Cohen, 2020). Crespi (2021)
hypothesizes that the pattern tendency of the autistic brain is related to sensory overload,
specifically identifying increased focused attention on particular patterned stimuli as a way for
the autistic brain to manage sensory overload. Repetitive behaviors may be another means of
managing sensory overload. Crespi provides an argument for replacing “systemizing” with
“pattern” in autism literature (Crespi, 2021).
Evolutionary Theories of Autism
Evolutionary theories for autism can be divided into four categories: adaptive models;
byproduct models; diametrical models; and life history perspective models (Del Giudice, 2018).

Adaptive Model
Baron-Cohen (2004) postulated that perceptual, visuospatial, and mechanistic abilities
associated with autism may have been selected in the male-typical activities of hunting and tool-
making. Hyper-focus and systemization could have been useful in a variety of skills that were
critical to our ancestors, including tracking prey and manufacturing weapons and tools (Baron-
Cohen, 2004). Reser (2011) proposed that the solitary lifestyles employed by many autistic
people may have enabled a “solitary forager” strategy in ancestral humans, particularly under
conditions of food scarcity (Reser, 2011). Baron-Cohen and Reser agree that, although autistic
traits in the nonclinical range can be adaptive, most clinically diagnosed cases are maladaptive
instances of trait overexpression (Del Giudice, 2018).
Byproduct Model
The byproduct model proposes that autistic traits do not necessarily have an adaptive
function of their own, but instead represent undesirable side effects of other adaptive traits such
as intelligence or brain size. According to the byproduct theory, genetic variants that increase
autism correlate with increased intelligence. The byproduct model suggests that the interaction
of a combination of specific, unusual alleles increase intelligence but also disrupt brain
development and lead to the development of autism. Autism can be summed up by this model as
a cognitive profile of “high but imbalanced” intelligence (Ploeger & Galis, 2020).
Diametrical Model
The diametric model of autism and psychosis presented by Crespi and Badcock (2008)
proposed that the confirmed pattern of enhanced mechanistic and reduced mentalistic cognition
in ASD provides a broader context for byproduct models that link autism to specific cognitive
profiles caused by a tradeoff between mechanistic and mentalistic cognition. Epigenetic studies

suggest that maternally expressed and paternally expressed imprinted genes play opposite roles
in the etiology of autism and psychosis (maternally expressed imprinted genes resulting in
psychosis spectrum disorders and paternally expressed imprinted genes resulting in ASD). This
theory posits that intra-genomic conflict increases the risk of both outcomes by amplifying the
expression of extreme trait values, despite the associated fitness costs (Crespi & Badcock, 2008).
Life History Perspective Model
The life history perspective model of autism is based upon the idea that autism is a
“male” variant associated with prolonged cognitive and behavioral development. Typical
autistic traits such as restricted socio-sexuality, and increased investment in long-term partners
promote parental investment over mating effort, a pattern referred to as the “slow life strategy”
by evolutionary psychologists (Del Giudice, 2018).
Theory of Mind
Difficulty understanding the minds of others is cited as a core cognitive feature of ASD.
The term “theory of mind” (ToM) has been used to describe the ability to infer the full range of
mental states that cause an action, including beliefs, desires, intentions, imaginations, and
emotions (Baron-Cohen, 2001). Autistic people have consistently scored lower on tasks
designed to measure ToM than non-autistic people across several experiments (Mathersul et al.,
2013). Baron-Cohen (2014) suggests that it is the implicit nature of ToM that causes problems
for autistic people. Explicit systems rely on sequential processing, which is a heightened ability
in many autistic people, whereas implicit systems require parallel processing (the ability to
process multiple items simultaneously), which is deficient in many autistic people (Baron-
Cohen, 2014) (Schneider et al., 2017).

A vast body of research concludes that autistic and non-autistic people tend to have dis-
similar ToM; however, recent research challenges the claim that this phenomenon should be
posed as an impairment of the autistic brain. Proponents of the neurodiversity movement claim
that the autistic ToM is simply a different perspective than that of a non-autistic person.
Researchers at the University of Michigan and the University of Wisconsin challenge the
concept altogether, citing a lack of empirical research that autistic people lack ToM, and failure
to replicate studies on the topic (Gernsbacher & Yergeau, 2019).
An experimental study conducted by researchers from the University of Nottingham, UK
hypothesized that the ToM issue may be a problem for both the autistic and non-autistic
population depending on the context. The results of the study concluded that non-autistic people
have more difficulty interpreting the mental states of people with ASD than they have with other
non-autistic people. Likewise, autistic people have more difficulty interpreting the mental states
of non-autistic people than they have with other autistic people, suggesting that ToM difficulties
are universal (Sheppard et al., 2015). This phenomenon has been termed the “double empathy
problem” and its proponents believe that the communication breakdowns that are common
between autistic and non-autistic people are a two-way issue. The “double empathy problem”
further supports the claims of the neurodiversity movement that autistic people have a way of
thinking that is merely different, not necessarily deficient or impaired (Mitchell et al., 2021).
Sex Differences in Autism
ASD has a striking male bias in prevalence. Approximately four males are affected for
every one female overall. That number varies across the spectrum, falling as low as 2:1 where
autism is accompanied by severe intellectual disability, and rising to approximately 10:1 among
people with superior intellectual ability (Milner et al., 2019). It is unclear whether this gap is

reflective of the actual occurrence rates or if it is due to diagnostic error. Several sex-differential
genetic and hormonal factors that contribute to the prevalence discrepancy have been identified.
Recent studies also indicate differences in phenotypic presentation, specifically that females
report fewer restricted and repetitive behaviors and fewer externalizing behavioral problems
(Werling & Geschwind, 2013). The DSM-5 has included sensory issues as a key ASD symptom.
A number of recent studies have suggested that autistic females may experience more sensory
issues than autistic males (Lai et al., 2011). Genetic studies suggest that females are protected
from ASD genetically, a phenomenon that has been termed the “female protective effect” (FPE).
The FPE model posits that females require a greater etiologic load in order to express autism.
The FPE model predicts that, due to the greater familial etiologic load, family members of
autistic females should have higher autistic trait scores than the family members of autistic males
with the same degree of impairment (Robinson et al., 2013). Studies have shown that girls
diagnosed with ASD tend to have more autistic traits than boys, suggesting that girls may require
more severe autistic difficulties in order to receive a diagnosis (Whitlock et al., 2020).
A study conducted by the Autism Research Center in Cambridge, UK used cognitive and
behavioral measures to examine differences between high-functioning autistic males and
females. The study showed no significant neurobiological differences between the sexes.
However, high-functioning autistic females showed more lifetime sensory problems, fewer social
communication difficulties, and more self-reported autistic traits than high-functioning autistic
males. The study found no differences in empathizing-systemizing profiles, a result that
confirms the “extreme male brain theory” (Baron-Cohen et al., 2014). Lai et al. (2018) refers to
the differences in social communication skills as “superficial”, as the evidence suggests that
autistic females may be more motivated to appear “socially typical” and develop camouflaging

strategies as a compensation (Lai et al., 2018). A review conducted at the University College
London suggests that the camouflaging tendency that is prevalent in autistic females may explain
some of the gender discrepancy in diagnosis (Hull et al., 2020).
ASD Employment
An increasing number of neurodiversity advocates propose a shift in the cultural
perspective of ASD. Several major employers have instituted “neurodiversity initiatives” in an
attempt to highlight the benefits of neurodiverse employees. SAP, Microsoft, JP Morgan,
VMWare, and Salesforce are among the growing number of U.S. companies who have joined the
“Autism at Work” initiative. Despite their efforts, Autism at Work and other major autism
initiatives combined employ fewer than 1500 workers total. Forbes contributor Michael Bernick
predicts that autism workforce intermediaries (Integrate, Next for Autism, Neurodiversity
Pathways, Autism Speaks) are the most promising vehicles for increasing employment rates in
the autistic population. He adds that universities, nonprofits, and foundations have been absent
from these initiatives thus far and could have a strong positive impact should they join (Bernick,
2021).
The current unemployment rate for high functioning autistic adults is approximately four
times that of the general population (Cockayne, 2017). Autistic employees cite autistic burnout
as a significant factor in the unemployment rates. Autistic employees who participated in a study
conducted by researchers from the Academic Autism Spectrum Partnership in Research and
Education identified sensory related stressors, barriers to support, and an inability to obtain relief
from the cumulative load as causes of autistic burnout at work. Participants of the study
identified lack of empathy from non-autistic co-workers or managers as an additional stressor
(Raymaker et al., 2020).

Birbeck University of London psychologist Nancy Doyle suggests the alternative
perspective that autistic employees can offer “specialist thinking skills”. Doyle suggests that the
aim of occupational accommodations for autistic employees is to access the “spikey” profile that
is found in autistic people, while reducing struggles (Doyle, 2020). Bernick (2021) states that an
“autism friendly workplace” goes beyond lighting or sound modifications to consider a culture of
greater patience and flexibility that also addresses common comorbidities like OCD, anxiety
disorder, and major depressive disorder (Bernick, 2021).
Victimization Experiences
Despite the increased awareness of autism in recent years, victimization among this
population is a pervasive problem. A study at York University found that autistic participants
were approximately four times more likely than non-ASD participants to experience bullying,
four times more likely to experience maltreatment, seven times more likely to experience sexual
abuse, and 27 times more likely to be teased by peers (Fardella, 2018). Autistic “masking” and
“camouflaging” are strategies that are commonly employed by autistic people to avoid bullying
and other external stressors. Masking comes at a significant cost, however, causing stress,
burnout, and suicidality in some autistic people (Pond, 2021). Autistic people who do not
receive a timely diagnosis may be at an increased risk of bullying and social isolation, as well as
feelings of being misunderstood and “not fitting in” (Whitlock et al., 2020). Autistic people are
especially vulnerable to “mate crimes” a term used to describe a form of hate crime that occurs
when someone uses their relationship with an individual to exploit and abuse them, or
“cuckooing” a British term used to describe a practice in which a criminal befriends a vulnerable
person in order to exploit his or her home for criminal use (typically drug dealing) (Autism
Spectrum Conditions, 2019). The abuse and trauma that mars the lives of many autistic people

often leads to suicidal ideation. A survey of 400 autistic adults conducted at the Autism
Research Center at the University of Cambridge found that two thirds of the autistic participants
reported feeling suicidal and one third of the autistic participants had attempted suicide (Baron-
Cohen, 2020).
Hypotheses
We predict that our data will replicate previous findings regarding the challenges and
strengths associated with ASD; the heightened risk of adverse experiences for autistic
individuals; the phenotypic similarities and differences among males and females with ASD; and
the increased unemployment rates for autistic individuals. Accordingly, the following four
hypotheses are proposed:
Hypothesis 1 - Autistic people report more sensory disturbances and difficulties with social
communication and emotion perception compared to non-autistic people and a stronger tendency
to systemize information.
Hypothesis 2 - Autistic males and females have similar cognitive and emotional profiles but
autistic females have more sensory disturbances than autistic males and fewer social
communication difficulties.
Hypothesis 3- Autistic people are at greater risk of abuse, bullying, and PTSD than non-autistic
people.
Hypothesis 4- Autistic people report lower rates of employment than non-autistic people.
Method
Participants
Participants for the study were obtained in the following ways: 1) The “Contribute Panel”
from online survey tool, Survey Monkey (www.surveymonkey.com) recruited survey

participants in exchange for a 50-cent donation to a charity of their choice. 2) Participants of
online social networking sites for the autistic population received an email link which directed
them to the online survey hosted at Survey Monkey. 3) Acquaintances of the researcher received
an email link which directed them to the online survey hosted at Survey Monkey. In total, 311
people started the survey. Of this total sample, 19 were disqualified for not completing the
survey fully and one was disqualified for being under the age of 18, leaving 291 participants for
the study.
Ethical Considerations
Permission to administer the questionnaire was granted by the Union College, KY
Institutional Review Board (IRB). An online consent form indicating that participation was
voluntary and that all data was anonymous preceded the survey.
Design
The 46-question survey (Appendix A) included five sections. The first section included
33 questions related to cognitive, emotional, sensory, and social experiences that were rated on a
five-point Likert scale (1= I do not identify with this statement at all; 2= This statement does not
describe me very well; 3= I am neutral as to whether or not this statement describes me; 4= This
statement describes me fairly well; 5= This statement describes me very well). The second
section included 5 yes or no questions related to past experiences of abuse and trauma. The third
section included one “check all that apply” question in a list of 11 physiological and
psychological conditions. The fourth section included six demographic questions, including the
participants’ ASD diagnosis status. The final question was a direct open-ended question related
to hobbies and interests.

For the purpose of the analysis, the data was organized into five domains: A) Cognitive/
Emotional experiences, B) Sensory experiences, C) Social experiences, D) Adverse experiences,
and E) Demographic data. Each survey question pertained to the domains. The questions were
assigned to each of the four hypotheses based upon relevance. Certain questions were omitted
from the analysis because the pattern of responses indicated problems with the wording.
Seventeen questions from domains A, B, and C were analyzed for hypotheses 1 and 2. Six
questions from domain D were analyzed for hypothesis 3, and one demographic question from
Domain E was analyzed for hypothesis 4.
Data Analysis
Analyses were conducted in Jamovi (v1.2.27.0 for Mac). Descriptive statistics were used
to analyze demographic variables. Chi-Square Tests of Independence were used to determine
association among variables. An Independent Samples t Test was used to compare the mean age
of the ASD vs non-ASD groups and the mean age of the autistic male and autistic female groups.
A binomial test was used to compare the number of ASD participants in our sample to the
number of ASD participants in the general population.
Results
Of the 291 participants who completed the survey, 234 people indicated that they had
never been formally or self-diagnosed with ASD. Twenty-eight respondents indicated that they
had been formally diagnosed with ASD and 29 respondents indicated that they were self-
diagnosed with ASD. For the purpose of this study, “ASD participants” includes both formally
and self-diagnosed individuals. In total, 57 participants identified as autistic and 234 participants
identified as not autistic. Of the 57 autistic participants, 22 were recruited from targeted sources
and the other 35 were obtained from Survey Monkey’s “Contribute Panel”. A binomial test was

conducted to compare the number of self-selected autistic participants from the Contribute Panel
(n=35) to the average number of autistic people in the general population (2.21%) (CDC
Releases First Estimates of the Number of Adults Living with ASD, 2020). The test revealed that
our random sample has more autistic participants than is likely to be found in the general
population (p=.000026). This may be due to the fact that the stated purpose of the survey was
understanding autism so autistic people may have been more likely to complete the survey than
non-autistic people.
The average age of the total sample was 42 (M=42.0, SD=16.4). The average age of the
ASD group was approximately 35 (M=34.72, SD=8) compared to an average age of
approximately 44 (M=43.79, SD=7.5) in the non-ASD group. An Independent Sample t Test
indicated a significant difference between the mean ages of the two groups, t(289) = 3.83,
p<.001.
The total sample (N=291) consisted of 61.51% females. Both the ASD group (n=57) and
the non-ASD group (n=237) contained more females than males or non-binary participants.
Within the ASD group, 24 participants identified as “male”, 30 identified as “female” and 3
identified as “other”. Among the non-ASD participants, 80 identified as “male”, 149 identified
as “female”, one responded “other”, and four responded “prefer not to answer”. A Chi-Square
Test of Independence did not reveal a significant difference between the number of males and
females in the two groups, X2
(1, N=283) = 1.70, p = .192. A comparison of gender between the
groups is presented in Table 1.

Table 1
Gender Frequencies by ASD Diagnosis (N=291)
ASD Non-ASD Total Sample
Male 24 (42.11%) 80 (34.19%) 104 (35.74%)
Female 30 (52.63%) 149 (63.68%) 179 (61.51%)
Other 3 (5.26%) 1 (0.43%) 4 (1.37%)
Prefer not to answer 0 (0.00%) 4 (1.71%) 4 (1.37%)
Note. “Other” and “Prefer not to answer” responses were not included in the X2
test.
A Chi-Square Test of Independence revealed a significant difference in relationship
status between the groups, X2
(6, N=291) = 27.8, p<.001. A summary of the relationship status
of both groups is presented in Table 2 and Figure B1 (Appendix B).
Table 2
Relationship Status by ASD Diagnosis (N=291)
ASD Non-ASD
Currently married 12 (21.05%) 110 (47.01%)
Widowed 4 (7.02%) 8 (3.42%)
Divorced 7 (12.28%) 14 (5.98%)
Separated 7 (12.28%) 4 (1.71%)
Currently in a relationship and
living with partner
5 (8.77%) 26 (11.11%)
Currently in a relationship, not
living with partner
4 (7.02%) 23 (9.83%)
Currently not in a relationship 18 (31.58%) 49 (20.94%)

Although college education levels among the ASD and non-ASD groups were similar,
ASD participants were less likely to have graduated high school than non-ASD participants.
None of the ASD participants attended trade school, compared to 9% of the non-ASD group. A
Chi-Square Test of Independence indicated that there was a significant association between
education levels and ASD diagnosis. X2
(5, N=291) = 23.6, p<.001. Education levels of the two
groups are presented in Table 3. A histogram of the education levels of both groups is presented
in Figure B2 (Appendix B).
Table 3
Education Level by ASD Diagnosis (N=291)
ASD Non-ASD
Did not graduate high school 9 (15.79%) 5 (2.14%)
Graduated high school 15 (26.32%) 76 (32.48%)
Bachelor’s degree 21 (36.84%) 81 (34.62%)
Master’s degree 9 (15.79%) 40 (17.09%)
Ph.D. or higher 3 (5.26%) 11 (4.70%)
Trade School 0 (0.00%) 21 (8.97%)
Hypothesis 1
A Chi-Square Test of Independence measured differences in cognitive, emotional,
sensory, and social domains among ASD (n=57) and non-ASD (n=234) participants. The results
of the tests are presented in Table 4.

Table 4
Cognitive, Emotional, Sensory, and Social Experiences by ASD Diagnosis
X2
df N p
Cognitive/ Emotional Domain (A)
Inferring the thoughts or feelings of others is difficult for me. 21.3 4 291 <.001
It is difficult for me to detect lies. 19.8 4 291 <.001
I have difficulty identifying my feelings. 37.4 4 291 <.001
I have problems distinguishing my own thoughts and feelings from the
thoughts and feelings of others.
25.1 4 291 <.001
I experience difficulty communicating my thoughts or feelings to others. 24 4 291 <.001
It seems as if my thoughts and feelings are disconnected from one
another.
31.7 4 291 <.001
I focus on certain details and miss things that seem obvious to
others.
33.9 4 291 <.001
I find it difficult to stop thinking about things that I cannot understand. 16.8 4 291 =.002
I have trouble switching from one task to another. 36.8 4 291 <.001
I have difficulty spotting signals of danger that seem obvious to others. 42.1 4 291 <.001
Sensory Domain (B)
I am sensitive to bright lights or loud sounds. 41.7 4 291 <.001
I am sensitive to certain textures, tastes, or smells. 33.1 4 291 <.001
Social Domain (C)
I copy or imitate others to fit in socially. 21.0 4 291 <.001
I cannot tell when someone is flirting with me. 14.8 4 291 =.005

People describe me as naïve or gullible. 26.5 4 291 <.001
People tell me that my speech is formal or robotic. 52.3 4 291 <.001
I am overly cautious because I do not trust my ability to detect danger. 23.1 4 291 <.001
All of the questions in domains A, B, and C showed a statistically significant association
for cognitive, emotional, sensory, and social communication variables between ASD and non-
ASD participants, in support of Hypothesis 1. The results from domains A indicated that autistic
people have more emotional and cognitive communicative difficulties (difficulty inferring the
thoughts or feelings of others, difficulty detecting lies, difficulty identifying feelings, difficulty
distinguishing thoughts and feelings from others, difficulty communicating thoughts and
feelings, and experiencing thoughts and feelings as disconnected), as well as a stronger
systemizing profile (focusing on certain details, difficulty disengaging thoughts, difficulty
switching tasks). The results from domains B and C show that autistic people are significantly
more likely to experience sensory and social communication difficulties than non-autistic people.
Altogether, our data strongly supports Hypothesis 1.
Hypothesis 2
In order to test Hypothesis 2, we first examined the demographic differences between the
male and female autistic respondents (N=54). The average age of the groups was nearly
identical. The average age of males was 35 (M=35.4, SD=14.4) and the average age of females
was also 35 (M=35.4, SD=13.5). This similarity of ages between the groups was reflected in an
Independent Samples t Test, t(48)=.013, p=.990. The relationship status of the groups was also
similar with the greatest frequency of responses being “not currently in a relationship”. A Chi-
Square Test of Independence reflected this similarity of relationship status among the groups,
X2
(6, N=54) = 1.50, p=.959. The education levels of the autistic males and autistic females were

also similar. Members of both groups were most likely to have a Bachelor’s degree. A Chi-
Square Test of Independence revealed the similarity of education levels among the groups, X2
(4,
N=54) = .585, p=.965. Although more autistic males reported being employed full time (n=10)
than females (n=5) and more females (n=6) than males (n=2) were currently seeking
employment, a Chi-Square Test of Independence indicated no statistically significant difference
in the employment status of the groups, X2
(4, N=54) = 4.66, p=.324.
The same 17 survey questions used for analysis in Hypothesis 1 were used to measure the
differences in cognitive, emotional, sensory, and social experiences between autistic males
(n=24) and autistic females (n=30) using the Chi-Square Test of Independence. Results of the
tests are presented in Table 5.
Table 5
Autistic Cognitive, Emotional, Sensory, and Social Experiences by Gender
X2
df N p
Cognitive/Emotional (A)
Inferring the thoughts or feelings of others is difficult for me. 1.57 4 54 =.813
It is difficult for me to detect lies. 1.65 4 54 =.799
I have difficulty identifying my feelings. 4.64 4 54 =.326
I have problems distinguishing my own thoughts and feelings
from the thoughts and feelings of others.
12.1 4 54 =.017
I experience difficulty communicating my thoughts or feelings
to others.
4.01 4 54 =.404
It seems as if my thoughts and feelings are disconnected from
one another.
4.00 4 54 =.406

I focus on certain details and miss things that seem obvious to
others.
4.34 4 54 =.362
I find it difficult to stop thinking about things that I cannot understand. 2.97 4 54 =.564
I have trouble switching from one task to another. 1.33 4 54 =.856
I have difficulty spotting signals of danger that seem obvious
to others.
1.77 4 54 =.778
Sensory Domain (B)
I am sensitive to bright lights or loud sounds. 12.0 4 54 =.017
I am sensitive to certain textures, tastes, or smells. 9.48 4 54 =.050
Social Domain (C)
I copy or imitate others to fit in socially. 7.36 4 54 =.118
I cannot tell when someone is flirting with me. 7.17 4 54 =.127
People describe me as naïve or gullible. 2.28 4 54 =.685
People tell me that my speech is formal or robotic. 1.50 4 54 =.826
I am overly cautious because I do not trust my ability to
detect danger.
2.61 4 54 =.625
Hypothesis 2 predicted that we would find significant differences between the genders in
domain A and that we would not find significant differences between the genders in domains B
and C. The only item from domains A that was significantly different between genders was “I
have problems distinguishing my thoughts and feelings from the thoughts and feelings of
others.” This item did not show a statistically significant difference between genders in the non-
ASD group {X2 (12, N=234) =10.5, p=.569} suggesting that the observed difference may be

specific to autism and not influenced by gender in general, although the interaction itself was not
tested. With that exception, we found no significant differences between the genders in any of
the questions assigned to domain A. We also found significant differences between the genders
in both variables measured in domain B as we expected. However, we found no significant
relationships between the genders for the variables measured in Domain C. A Chi-Square Test
of Independence was used for the item “I copy or imitate others to fit in socially” (referred to as
“masking” in autism literature). Both the targeted autism group {X2
(8, N=22) = 14.3, p=.073}
and the self-selected Contribute Panel autism group {X2
(4, N=35) = 4.66, p=.324} were tested,
with no significance being found in either group.
Hypothesis 3
A Chi-Square test of independence was used on five survey questions from domain D to
examine the relationship between autism and adverse experiences. Results of the test are
presented in Table 7 and Figure B3 (Appendix B).
Table 7
Adverse Experiences by ASD Diagnosis
ASD Non-ASD X2
df N p
Physical abuse 33 (58.93%) 67 (28.76%) 17.4 1 291 <.001
Sexual abuse 26 (46.43%) 50 (21.37%) 15.9 1 291 <.001
Financial exploitation 23 (41.07%) 60 (25.64% 6.05 1 291 .014
Workplace bullying 28 (50.00%) 82 (35.34%) 3.62 1 291 .057
PTSD 21 (37.50%) 29 (12.39%) 21.8 1 291 <.001

The results indicated a significant relationship between autism and physical abuse, sexual
abuse, financial exploitation, and PTSD. Although we did not find a significant relationship
between autism and being bullied at work, our results may have been influenced by the low
levels of employment for the ASD group. The probability value for this variable was
approaching significance (p=.057). Future studies with larger sample sizes and employment
matched groups are needed to confirm the relationship between ASD diagnosis and bullying
experiences at work. Overall, our data supports Hypothesis 3.
Hypothesis 4
A Chi-Squared Test of Independence was used to determine the association between
autism and employment status. The variable of employment was significant, supporting our
hypothesis that autistic people have lower rates of employment than non-autistic people, X2
(1,
N=291) = 16.4, p = .002. A summary of employment status is presented in Table 8 and Figure
B4 (Appendix B).
Table 8
Employment Status by ASD Diagnosis (N=291)
ASD Non-ASD
Employed Full-time 15 (26.32%) 117 (50.00%)
Employed Part-time 18 (31.58%) 36 (15.38%)
Seeking Employment 8 (14.04%) 17 (7.26%)
Unemployed 11 (19.30%) 32 (13.68%)
Retired 5 (8.77%) 32 (13.68%)

Discussion
Hypothesis 1
The fact that our data strongly supported Hypothesis 1 is no surprise given the abundance
of evidence supporting the fact that autistic people perceive and experience the world differently
than non-autistic people. Although these findings have been replicated many times over, their
practical application is of key importance. Until these differences are acknowledged and
accepted, autistic people are unlikely to experience improved outcomes. One setting in which
real-world application of the current autism research could have a significant impact is the
mental health industry. Despite the extraordinarily high rate of mental health concerns within
the autistic population, the fundamental cognitive and emotional communication differences
between autistic people and their providers often leads to poor standard of care (similar to other
‘non-mainstream’ populations). Autistic people who have struggled to find acceptance in their
family, social, or work settings may risk further invalidation when attempting to receive mental
health support from an industry that is modeled by and for neurotypical people. Anecdotal
evidence suggests that many autistic adults have negative experiences within the mental health
industry. The current standard treatment for autism in the United States is applied behavioral
analysis (ABA), which is typically used with autistic children. Neurodiversity advocates claim
that ABA further invalidates autistic individuals by attempting to force autistic people into
conforming into neurotypical standards. A 2018 study of 460 autistic people and their caregivers
found that autistic people with ABA exposure were significantly more likely to develop PTSD,
concluding that childhood ABA exposure is a predictor of adult PTSD diagnosis in the autistic
population (Kupferstein, 2018). Furthermore, since ABA is most appropriate for people who
externalize behaviors, the approach may be unhelpful for autistic people who struggle with

internalizing issues such as anxiety or depression. Simon Baron Cohen (2020) posits that the
capacity to systemize (along with the curiosity that drives systemization) is the trait that sets
humans apart from other species. It is also the mechanism at work behind many of the great
inventions in history and is present in many autistic people (Baron Cohen, 2020). Neurodiversity
advocates claim that striving to make autistic minds more ‘typical’ is not only unethical, but also
not in the best interest of society at large.
Notwithstanding the arguments against current therapeutic techniques used with autistic
people, there is clearly a need for mental health interventions with this population in order to
address the symptoms that commonly accompany autism. Surprisingly, there are few standard
treatment interventions for autistic adults, in spite of the high rates of depression, anxiety, PTSD,
and other issues experienced by this population. There are several intriguing therapeutic
techniques for autism that require further research. Eye Movement Desensitization and
Reprocessing (EMDR) has shown promising results in preliminary trials that measured trauma-
related symptom reduction in ASD patients who also experience traumatic symptoms (Lobregt-
van Buuren et al., 2018). This therapy is an interesting option for autistic patients given that the
basis of EMDR is bilateral brain stimulation and we know that autistic brains experience
diminished connectivity in some regions, as well as a weakened corpus callosum. EMDR also
addresses the issue of trauma that is common among the autistic population. Future research to
further investigate the benefits of EMDR for ASD is needed. Other promising therapies for
autism may help improve sensory related difficulties, including somatic experiencing (SE), yoga
therapy, and sensorimotor therapy. Further investigation into the benefits of these therapies for
ASD is needed.

Regardless of the chosen intervention, the therapeutic relationship remains a core
predictor of psychotherapeutic success. The “double empathy problem” is particularly
problematic in the therapeutic relationship where empathy is critical. Educating mental health
professionals about neurodiversity is crucial for advancements in autism. The growing body of
research in the field of autism is only useful if it can be practically applied to help autistic
people. The neurodiversity movement is timely given the current emphasis on Diversity, Equity,
and Inclusion (DEI). The recent public apology issued by the APA regarding its historic role in
promoting racism is a positive sign that the American mental health industry may be evolving
into a more inclusive entity (Apology to People of Color for APA’s Role in Promoting,
Perpetuating, and Failing to Challenge Racism, Racial Discrimination, and Human Hierarchy in
U.S., 2021). A paradigm shift within the mental health industry to perceiving autism and other
neurological differences as ‘different’ rather than ‘disordered’ could be a pivotal step toward
discovering and implementing appropriate treatments to help manage symptoms experienced by
autistic people.
Hypothesis 2
We saw no significant differences between autistic males and autistic females in the
cognitive or emotional variables, in support of Hypothesis 2. We also found a significant
relationship between gender and both auditory/visual sensitivity and tactile sensitivity, in support
of our hypothesis. However, we did not find a significant relationship between gender and social
communication difficulties within the ASD group.
Surprisingly, we did not find a significant difference in the social compensation strategies
employed by autistic males and females. Recent studies have highlighted the role of “masking”
in autistic females and some researchers believe that masking may skew the gender discrepancy

within autism. It is possible that our sample size influenced this finding. Future studies with
larger autism samples are needed in order to draw accurate conclusions about gender and
masking in autism. It is also possible that the results of our study did not reflect a significant
relationship between gender and autistic masking because the relationship does not exist in the
population. Some autism researchers believe that the current 4:1 gender discrepancy is not
accurate and accordingly search for evidence, such as the autistic masking hypothesis, to support
their claim. Other researchers cite the abundance of genetic research supporting the gender
discrepancy. The “female protective effect” hypothesis continues to gain credibility as its claims
that females are protected genetically from autism are consistently supported. Since a greater
mutational load is required in females in order to express autism, we should expect to see that
discrepancy gap widen as IQ increases, which is in line with current research. If the gender
discrepancy is accurate, then there may be no difference in compensatory social strategies
between the genders.
Realistically, we know relatively little about the female autistic phenotype because the
majority of autism studies in past years have been limited to male participants. Since autistic
females may be at an even higher risk of abuse and exploitation than autistic males (Bargiela et
al., 2016), accurate understanding and diagnosis of this population is critical. A commonly cited
criticism of the neurodiversity movement is that viewing autism as “different” as opposed to
“disordered” may lead to fewer people receiving an ASD diagnosis. Anecdotal evidence
suggests that having a formal ASD diagnosis allows some people to have a better understanding
of their lives and take appropriate steps toward self-empowerment, including physical and
emotional safety. This issue seems to be especially important for autistic females whose lack of

diagnosis may cause decreased self-esteem and put them at an increased risk of adverse
experiences. Future autism studies which include females are critical.
Hypothesis 3
The fact that our data strongly supported Hypothesis 3 is also no surprise given the prior
findings on autism and various forms of abuse and exploitation. Autistic participants in our study
were significantly more likely to experience physical, sexual, and financial abuse and more
likely to receive a PTSD diagnosis. These high rates of victimization found in the study are a
massive concern. Importantly, ASD participants were also significantly more likely to report
difficulties detecting lies and spotting danger, two commonly cited ToM deficits in the autistic
population. Understanding ToM difficulties as they relate to victimization in this population is
fundamental to implementing victimization prevention strategies for autistic people. Education
aimed at helping autistic people protect themselves from abuse and exploitation is an urgent
priority.
Hypothesis 4
Our study revealed results that are in line with current research on unemployment rates
for autistic people. In spite of the efforts of the neurodiversity movement, current unemployment
rates for high functioning autistic people are approximately four times higher than the general
population. Given what we know about the autistic brain’s ability to problem solve and/or detect
novel patterns, it is an oversight for employers to dismiss the potential of autistic employees.
Slight modifications to accommodate sensory or social issues could lead to new ideas,
inventions, problem solving, and precision in many industries. Birbeck University of London
psychologist Nancy Doyle refers to the autistic perspective in the workplace as “specialist
thinking skills” (Doyle, 2020). That these skills are not leveraged more often in the business

world is surprising. Training employers to identify the potential of autistic employees and to
make appropriate accommodations could not only positively impact the employment rates for the
autistic population, but it could also benefit various industries and businesses. To quote world
renowned autism spokesperson Temple Grandin, “The world needs different kinds of minds to
work together” (Grandin, 2010).
Limitations
There are several limitations of the present study. First, this was a subjective, self-report
survey making it subject to cognitive bias and dependent upon the (unknown) introspective
abilities of the respondents. Second, several of the autistic participants came from the same
source (an online autism forum) which may have influenced the results. Third, the autistic group
included people who do not have a formal ASD diagnosis but are self-diagnosed with ASD.
Approximately half of the autistic participants were self-diagnosed. This was done in order to
achieve a larger sample size. Although there is a benefit to including this group in studies, future
studies should use the Autism Quotient (AQ) or some similar test to assess autistic criteria prior
to defining groups. Fourth, some of the original survey questions were omitted from analysis
because the pattern of responses indicated clear problems with the wording of the questions.
Future questionnaires that control for bias or vagueness are needed for a more comprehensive
understanding of the measured domains. Fifth, a binomial test revealed that we had significantly
more autistic participants in our sample than would normally be found in the population. Future
tests with samples that are reflective of the general population are needed in order to draw
accurate conclusions. Finally, the results of non-binary participants were not included in the
gender analysis. Three autistic participants identified as “other” for gender and their results were
included in the autistic/non-autistic analysis but not in the autism gender analysis. Given that

autistic people are significantly more likely than non-autistic people to identify as non-binary,
studies that involve a much larger sample size for this population are needed.
Conclusion and Future Directions
The results of our study replicate former studies which confirm that autistic people
perceive and experience the world differently than neurotypical people. Our study also found a
significant relationship between gender and sensory difficulties but not cognitive, emotional, or
social communicative difficulties within the ASD group. Our results are in line with current
statistics regarding autism and abuse which confirm that autistic people are at a significantly
increased risk of abuse compared to non-autistic people. Finally, our results match current
employment statistics which conclude that autistic people have much higher rates of
unemployment than the general population.
Based on the results of our study, along with the reviewed literature, four questions for
future research have been identified.
1. What can we do to work toward solving the double empathy problem in the mental health
setting and what interventions are most appropriate for autistic people?
2. What (if any) are the differences in social communication experiences between autistic
males and autistic females?
3. What practical steps can be taken to help autistic people identify danger and protect
themselves from it?
4. How can we train employers to identify the benefits of autistic employees and make
appropriate accommodations for them?

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APPENDIX A
Union College Informed Consent for
Cognitive, Emotional, and Life Experiences Survey
You are invited to participate in a research study of the experiences of autistic people.
Participation in this study is voluntary. We ask that you read this form and ask any questions you
may have before agreeing to be in the study.
The study is being conducted by Christine R. Glass, graduate psychology student at Union
College, as part of a graduation integrative project. Dr. Ilie P. Vasilescu is the faculty
coordinator.
The purpose of this study is to better understand the characteristics of autistic people.
Number of People Taking Part in the Study: A number of 200 subjects will be participating in
this research.
Procedures for the Study: If you agree to be in the study, you will be asked to complete a
questionnaire that is estimated to take 20 minutes or less to complete.
Risks of Taking Part in the Study: The risks of this study are minimal. You will be asked
questions regarding experiences of bullying and abuse which could lead to discomfort.
Benefits of Taking Part in the Study: If you choose to take part in this study, you will be
helping to better understand the characteristics of autistic people.
Alternatives to Taking Part in the Study: The alternative to participating in this study is to not
participate in this study.
Confidentiality: This study is completely anonymous. Do not include your name on the
questionnaire.
For Questions or Problems, Contact:

Dr. Ilie P. Vasilescu
Ramsey Health Center, room 150 B
Campus PO Box: D16; Telephone: (606) 546-1523
Preferred form of communication: ivasilescu@unionky.edu
Taking part in this study is voluntary. You may choose not to take part, or may discontinue
the survey at any time.
Section 1
Please answer the following questions as to how well you identify with the statement.
1= I do not identify with this statement at all.
2= This statement does not describe me very well.
3= I am neutral as to whether or not this statement describes me.
4= This statement describes me fairly well.
5= This statement describes me very well.
Inferring the thoughts or feelings of others is difficult for me.
It is difficult for me to detect lies.
I have difficulty identifying my feelings.
I have problems distinguishing my own feelings or thoughts from those of others.
I experience difficulty communicating my feelings or thoughts to others.
I experience physical pain when someone else is in pain.
I faint or become light headed when someone else is injured or hurting.
It seems as if my thoughts and feelings are disconnected from one another.
I sometimes think or dream about things before they happen.
I have a strong sense of connection to nature and animals.

I copy or imitate others to fit in socially.
I have interests that my peers find unusual.
I focus on certain details and miss things that seem obvious to others.
I cannot tell when someone is flirting with me.
People describe me as naïve or gullible.
People tell me that my speech is formal or robotic.
I am sensitive to bright lights or loud sounds.
I am sensitive to certain textures, tastes, or smells.
I have an unusually high or low pain tolerance.
I have insomnia.
I usually notice details that other people miss.
I am interested in how the parts of an idea or thing connect to one another.
I come up with lots of questions about my topics of interest.
People describe me as a “deep thinker”.
I find it difficult to stop thinking about things that I cannot understand.
I become exhausted after being around a lot of people.
I have trouble switching from one task to another.
I have difficulty spotting signals of danger that seem obvious to others.
I am overly cautious because I do not trust my ability to detect danger.
I have a strong concern for social justice.
When conversing with others, I mostly focus on myself.
When conversing with others, I mostly focus on the other person.
When conversing with others, it is easy to focus on myself and others at the same time.

Section 2
Please answer yes or no to the following questions:
Have you ever been the victim of physical abuse?
Have you ever been the victim of sexual abuse?
Have you ever been financially exploited?
Have you ever been bullied at work?
Have you ever been diagnosed with post-traumatic stress disorder (PTSD)?
Section 3
Do you currently experience any of the following? (Check all that apply.)
Gastrointestinal issues
Allergies
Sleep issues
Skin conditions
Seizures
Asthma
Diabetes
Neurological problems
Depression
Anxiety
A mood or mental disorder other than depression or anxiety
Section 4
What is your gender?
Male

Female
Other
Prefer not to say
What is your age?
What is your education level?
Did not graduate high school
Graduated high school
Bachelor’s degree
Master’s degree
Ph.D. or higher
Trade school
What is your current relationship status?
Currently married
Widowed
Divorced
Separated
Currently in a relationship and living with partner
Currently in a relationship, not living with partner
Currently not in a relationship
Which of the following best applies to you?
I have been diagnosed with autism spectrum disorder (ASD).
I have self-diagnosed myself with autism spectrum disorder (ASD).
I have never been formally or self-diagnosed with autism spectrum disorder (ASD).

What is your current employment status?
Employed full time
Employed part time
Seeking employment
Unemployed
Retired
Section 5
Please list no more than 3 of your favorite hobbies or interests.

APPENDIX B
Figure B1
Relationship Status by ASD Diagnosis
0
5
10
15
20
25
30
35
40
45
50
Married Widowed Divorced Separated In a
relationship
and living with
partner
In a
relationship,
not living with
partner
Not in a
relationship
ASD % Non-ASD %

Figure B2
Education Levels by ASD Diagnosis
Figure B3
Adverse Experiences by ASD Diagnosis
0
5
10
15
20
25
30
35
40
Did not graduate
high school
Graduated high
school
Bachelor's degree Master's degree Ph.D. or higher Trade school
ASD % Non-ASD %
0
10
20
30
40
50
60
70
Physical abuse Sexual abuse Financial exploitaton Bullied at work Diganosed with PTSD
ASD/Non-ASD Adverse Experiences Comparison
ASD % Yes Non-ASD % Yes

Figure B4
Employment Status by ASD Diagnosis
0
10
20
30
40
50
60
Employed Full-time Employed Part-time Seeking Employment Unemployed Retired
ASD % Non-ASD %

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