Risk markers for suicidality in autistic adults

Abstract

Background
Research has shown high rates of suicidality in autism spectrum conditions (ASC), but there is lack of research into why this is the case. Many common experiences of autistic adults, such as depression or unemployment, overlap with known risk markers for suicide in the general population. However, it is unknown whether there are risk markers unique to ASC that require new tailored suicide prevention strategies.

Methods
Through consultation with a steering group of autistic adults, a survey was developed aiming to identify unique risk markers for suicidality in this group. The survey measured suicidality (SBQ-R), non-suicidal self-injury (NSSI-AT), mental health problems, unmet support needs, employment, satisfaction with living arrangements, self-reported autistic traits (AQ), delay in ASC diagnosis, and ‘camouflaging’ ASC. One hundred sixty-four autistic adults (65 male, 99 female) and 169 general population adults (54 males, 115 females) completed the survey online.

Results
A majority of autistic adults (72%) scored above the recommended psychiatric cut-off for suicide risk on the SBQ-R; significantly higher than general population (GP) adults (33%). After statistically controlling for a range of demographics and diagnoses, ASC diagnosis and self-reported autistic traits in the general population significantly predicted suicidality. In autistic adults, non-suicidal self-injury, camouflaging, and number of unmet support needs significantly predicted suicidality.

Conclusions
Results confirm previously reported high rates of suicidality in ASC, and demonstrate that ASC diagnosis, and self-reported autistic traits in the general population are independent risk markers for suicidality. This suggests there are unique factors associated with autism and autistic traits that increase risk of suicidality. Camouflaging and unmet support needs appear to be risk markers for suicidality unique to ASC. Non-suicidal self-injury, employment, and mental health problems appear to be risk markers shared with the general population that are significantly more prevalent in the autistic community. Implications for understanding and prevention of suicide in ASC are discussed.

Full text

R E S E A R C H Open Access
Risk markers for suicidality in autistic adults
Sarah Cassidy
1,2,3*
, Louise Bradley
2
, Rebecca Shaw
2,4
and Simon Baron-Cohen
3,5
Abstract
Background: Research has shown high rates of suicidality in autism spectrum conditions (ASC), but there is lack of
research into why this is the case. Many common experiences of autistic adults, such as depression or unemployment,
overlap with known risk markers for suicide in the general population. However, it is unknown whether there are risk
markers unique to ASC that require new tailored suicide prevention strategies.
Methods: Through consultation with a steering group of autistic adults, a survey was developed aiming to identify
unique risk markers for suicidality in this group. The survey measured suicidality (SBQ-R), non-suicidal self-injury (NSSI-AT),
mental health problems, unmet support needs, employment, satisfaction with living arrangements, self-reported autistic
traits (AQ), delay in ASC diagnosis, and ‘camouflaging’ASC. One hundred sixty-four autistic adults (65 male, 99 female)
and 169 general population adults (54 males, 115 females) completed the survey online.
Results: A majority of autistic adults (72%) scored above the recommended psychiatric cut-off for suicide risk on the
SBQ-R; significantly higher than general population (GP) adults (33%). After statistically controlling for a range of
demographics and diagnoses, ASC diagnosis and self-reported autistic traits in the general population significantly
predicted suicidality. In autistic adults, non-suicidal self-injury, camouflaging, and number of unmet support needs
significantly predicted suicidality.
Conclusions: Results confirm previously reported high rates of suicidality in ASC, and demonstrate that ASC diagnosis,
and self-reported autistic traits in the general population are independent risk markers for suicidality. This suggests there are
unique factors associated with autism and autistic traits that increase risk of suicidality. Camouflaging and unmet support
needs appear to be risk markers for suicidality unique to ASC. Non-suicidal self-injury, employment, and mental health
problems appear to be risk markers shared with the general population that are significantly more prevalent in the autistic
community. Implications for understanding and prevention of suicide in ASC are discussed.
Keywords: Autism spectrum condition, Autistic traits, Suicidality, Non-suicidal self-injury, NSSI, SBQ-R, NSSI-AT, Risk markers,
Mental health, Depression, Anxiety
Background
There are elevated rates of suicidality in adults diag-
nosed with autism spectrum conditions (ASC) [1–5].
However, suicidality in ASC is poorly understood, and
there is a paucity of research exploring why adults with
ASC (henceforth, autistic adults) may be at increased
risk [6]. Although a number of studies have explored
suicidality in autistic adults, no study has yet utilised a
suicidality assessment tool with evidence of validity [4,7,
8]. Non-suicidal self-injury (NSSI) is a risk factor for
suicide attempts in the general population [9]. However,
to our knowledge, only one study has ever explored
NSSI in a small sample of autistic adults using a vali-
dated instrument but did not explore associations with
suicidality [10]. Clearly, it is crucial to better understand
suicidality in autistic adults, and associated risk markers,
using instruments with evidence of validity (albeit not
yet in autistic adults). Given the paucity of literature in
the area of suicide in ASC research, it is important to en-
gage with the autistic community in the refinement of re-
search priorities to speed up progress and benefit the end
users of research [11]. This is the aim of the current study.
Suicidal thoughts and behaviours are significantly
increased in autistic adults compared to the general
population and other clinical groups. In a large sample
of 374 adults newly diagnosed with Asperger syndrome
* Correspondence: Sarah.Cassidy@Nottingham.ac.uk
1
School of Psychology, University of Nottingham, University Park,
Nottingham NG7 2RD, UK
2
Centre for Innovative Research across the Life Course, Coventry University,
Coventry, UK
Full list of author information is available at the end of the article
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Cassidy et al. Molecular Autism (2018) 9:42
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(AS; autism without language delay or intellectual disability),
66% had contemplated suicide, significantly higher than the
general population (17%) and patients with psychosis (59%);
35% had planned or attempted suicide [2], higher than
previous estimates of attempted suicide in general and
university populations (2.5–10%) [12–14]. Only one study
has ever explored whether autistic people are more at risk
of dying by suicide than the general population; this popu-
lation study in Sweden showed that autistic people were
significantly more likely to die by suicide (0.31%) com-
pared to the general population (0.04%) [15].
Traits characteristic of autism are also significantly as-
sociated with suicidality in those with [2], and without
ASC diagnosis [16–18]. ASC diagnosis has also recently
been found to be an independent risk marker for suicide
attempts independent of demographic characteristics
and co-occurring diagnoses [19]. These findings suggest
that ASC explains additional variance in suicidality, not
accounted for by other well-known risk markers in the
general population which are more prevalent in ASC,
such as depression [20–22] or social isolation [23,24],
which have been associated with increased risk of suicidality
in ASC [2,15,17,25,26]. Hence, there may be as yet
unknown unique risk markers for suicidality in ASC that
are not shared with the general population or other clinical
groups, requiring adapted suicide prevention strategies [6].
Studies exploring the characteristics of suicidality in
ASC could provide important clues for possible unique
risk markers in this group. For example, the highest
rates of suicidal ideation (66%) were reported in adults
newly diagnosed with AS, who had struggled without
support [2]. Age of diagnosis and adequate access to
post-diagnostic support could therefore be particularly
important in preventing suicidality in ASC [2]. However,
many children and adults diagnosed with ASC not only
struggle to obtain their diagnosis, but also struggle to
obtain post-diagnostic support [27–29]. Lack of tangible
social support has been associated with increased risk of
suicidality, indirectly through depression [25].
In the general population, the global male to female
ratio of deaths by suicide is estimated to be 1.7 [30],
indicating that males are more likely to die by suicide than
females. However, in the one available study exploring
death by suicide in the autistic community, autistic
females without intellectual disability (ID) were more at
risk of dying by suicide (0.32%) compared to autistic
males (0.3%); opposite to the general population where
males (0.05%) were more likely to die by suicide than
females (0.03%) [15]. Autistic females have been under-
researched, and it has been recognised that this group
may also be under-diagnosed [29,31,32]. Autistic people
report attempting to camouflage their ASC in order to try
and fit in in social situations, which may delay obtaining a
timely ASC diagnosis and negatively affect their mental
health [31–33]. However, no study has quantitatively
measured associations between ‘camouflaging’and risk
of mental health difficulties or suicidality in both autistic
males and females.
In addition to lack of research into possible autism
specific risk markers for suicidality, some potentially
common risk factors for suicidality in those with and
without ASC diagnosis have very different conceptuali-
sations that have resulted in them being overlooked by
researchers and clinicians. For example, self-injurious
behaviour in ASC [34] is conceptualised rather differently
than NSSI in the general population, as primarily a restricted
and repetitive behaviour characteristic of ASC [35]. By con-
trast NSSI in the general population is considered a possible
risk marker for later suicide attempts [9]. Only one study
has explored NSSI in autistic adults without co-occurring
ID using a tool validated for online research in non-clinical
populations [10] (non-suicidal self-injury assessment tool
(NSSI-AT)) [36]. The rate of NSSI in ASC was elevated
(50%)comparedtocollegestudents(17%)andadultcom-
munity samples (23%), but the phenomenology of NSSI was
broadly similar between those with and without ASC [10].
Importantly, this suggests that NSSI could be more preva-
lent in ASC than that in the general population, and could
potentiallybeapreviouslyunexploredcommonriskfactor
for suicidality in ASC and the general population.
Previous research has taken a piecemeal approach to
furthering our understanding of suicidality in ASC.
Important limitations include the fact that no suicidality
studies in ASC have used a suicidality assessment tool
with evidence of validity in this group [7,8], and very few
studies have included a comparison group [3]. Studies
have also failed to disentangle common shared and unique
risk markers for suicidality in autistic and general pop-
ulations, which is key to understanding and preventing
suicide in ASC [6].
The current study thus aimed to address these pitfalls
in previous suicidality in ASC research. First, we used
both a review of the available literature, and consultation
with a steering group of autistic adults who have experi-
enced suicidality, to ensure that we identified a range of
high priority risk markers for suicidality in autism, some
of which may be unique to this group. Second, we are
the first to utilise a well-validated suicidality assessment
tool (the Suicide Behaviours Questionnaire-Revised
(SBQ-R)) [37] in autistic adults (confirmed in a systematic
review) [7], and NSSI assessment tool previously utilised
in autistic adults (NSSI-AT) [10]. We also include a
general population comparison group. Hence, we are able
to explore whether autistic adults are at increased risk of
suicidality compared to the general population, while
controlling for known common risk factors for suicidality
(e.g. age, sex, mental health problems, employment, living
situation). We also explore for the first time a potentially
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unique risk marker for suicidality and NSSI in ASC males
and ASC females—camouflaging ASC in order to cope in
social situations—as well as age of ASC diagnosis, and
unmet support needs. We also explore whether NSSI is an
independent risk marker for suicidality in those with and
without ASC, and whether autistic traits are an independ-
ent risk marker for suicidality in the general population
without ASC diagnosis.
Method
Participants
The ASC group comprised 164 adults (65 males; 99 females)
who self-reported a diagnosis of ASC from a trained clin-
ician, and a majority (81.1%) confirmed the clinic where this
diagnosis was obtained. The general population group com-
prised 169 adults (54 males; 115 females). Participants were
aged between 20 and 60 years old (Table 1). There were no
significant differences in age (t(331) = .657, p= .511) or sex
ratio (χ
2
(1) = 2.14, p= .14) between the ASC and general
population group. The ASC group scored significantly
higher on the Autism-Spectrum Quotient (AQ) (36.42)
than the general population group (19.87) (t(331) = .657,
p<.001).SeeTable 1for group demographics.
Participants were recruited from research volunteers
databases located in the Autism Research Centre at the
University of Cambridge. Autistic adults and their family
members across the UK and internationally register in
the Cambridge Autism Research Database (CARD)
(https://www.autismresearchcentre.net/). General popu-
lation adults without an autism diagnosis or autistic
family members register at a separate website (https://
www.cambridgepsychology.com/login). Volunteers regis-
ter in these databases to receive information about a
variety of psychology research projects and not mental
health specifically. Additionally, participants were recruited
from online adverts.
Measures
Survey development
An online questionnaire exploring mental health, self-injury,
and thoughts of ending life was developed for the current
study in partnership with a steering group of eight adults
diagnosed with ASC (6 females, 2 males) through a series of
6 focus groups. Given the topic of the survey, all steering
group members were recruited by advertising for autistic
adults who would like to share their experience to influence
research and improve support for mental health problems,
self-injury, and suicidality. The first three focus groups
developed the topics to be captured in the questionnaire.
First, the researchers proposed a number of topics thought
to be important contributors to mental health and suicidality
in autism, and the focus group fed back on the relevance
and importance of these proposed topics, and whether any
important topics were missing. This ensured that a large
array of possible risk markers was prioritised for the
study. Subsequent focus groups discussed participants’
experiences of the topics. The researchers then devel-
oped a survey to capture these topics and experiences.
The steering group provided feedback on three drafts
of the survey to ensure that the questions were com-
prehensive, relevant, and clear.
Demographics
Participants who completed the online survey provided
information on age, biological birth sex, education,
employment, living situation, diagnosed developmental
and mental health conditions, current medication, whether
they were currently receiving any treatment for mental
health problems, suicidal thoughts, self-injury or other
reason. Participants also reported whether they need or
currently receive support, and if yes, were asked (a) in
which areas they would ideally like support in (in the
home, with employment, health care, mental health care,
finance, social activities, in the community, organisation,
mentoring, education, other); and (b) in which of these
areas they actually receive support. Unmet support needs
were thus calculated as the mismatch between the number
of areas participants actually received support, compared
to the number of areas participants would ideally like
support (unmet support needs = nareas support ideally
liked—nareas support actually received) (Table 1).
Camouflaging
A brief set of four questions were designed to quantify
tendency to camouflage in the current study. Autistic
adults were asked “Have you ever tried to camouflage or
mask your characteristics of ASC to cope with social
situations? For example, have you ever tried to copy or
mimic other people’s behaviour to try and fit in (e.g.
copying another person’s accent or mannerisms), or tried
to mask or hide your symptoms of ASC from other
people?”If participants responded yes, they subsequently
(a) specified the areas in which they camouflage (work,
educational settings, social gatherings, when visiting
the doctors, when visiting a health professional, at
home, with friends, other); (b) the overall frequency
they camouflage on a scale from 1 (never) to 6 (always
(over 90% of social situations)); and (c) overall amount
of the day they spend camouflaging on a scale from 1
(noneofmywakingtime)to6(allofmywakingtime
(over 90% of social situations)). Scores were calculated
as the sum of number of areas (maximum 8), overall
frequency (maximum 6), and overall amount (maximum 6),
with a maximum score of 20 overall. Internal consistency
for the whole scale was acceptable in the ASC group
(α= .75).
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Table 1 Participant characteristics
Variables Group
GP male (n= 54) GP female (n= 115) ASC male (n= 65) ASC female (n= 99)
Mean (SD)/n(%)
Age 39.11 (10.09) 41.48 (11.18) 41.52 (11.73) 38.89 (10.47)
AQ total score 22.96 (8.56) 18.43 (7.12) 35.38 (7.5) 37.1(8.33)
Age diagnosed with ASC –– 34.55 (14.75) 35.06 (11.83)
% Lifetime ‘camouflage’––58 (89.2) 90 (90.9)
Camouflage total score –– 12.9 (4.06) 14.7 (3.61)
% Non-suicidal self-injury 18 (33.3) 32 (28.1) 35 (53.8) 71 (74)
Suicidality
SBQ-R total score 7.48 (3.7) 6.36 (3.08) 10.14 (3.99) 10.56 (3.98)
%≥general population cut off 27 (50) 49 (42.6) 52 (80) 79 (79.8)
%≥psychiatric population cut-off 22 (40.7) 35 (30.4) 45 (69.2) 73 (73.7)
% Lifetime suicide attempt 7 (13) 7 (6.1) 21 (32.3) 42 (42.4)
ASC subtype
HFA/AS –– 51 (78.5) 85 (85.9)
Autism/classic autism –– 0 0) 2 (2)
ASC –– 7 (10.8) 7 (6.9)
PDD/PDD-NOS –– 1 (1.5) 1 (1)
Other –– 6 (9.2) 4 (4)
Education type
Mainstream 53 (98.1) 113 (98.3) 59 (98.1) 88 (88.9)
Home 1 (1.9) 2 (1.7) 1 (1.5) 2 (2)
Special 0 (0) 0 (0) 3 (4.6) 4 (4)
Private/boarding 0 (0) 0 (0) 2 (3.1) 5 (5.1)
Support
Need/receive support 16 (29.6) 36 (31.3) 51 (78.5) 75 (76.5)
Unmet support needs* 2.12 (1.78) 1.3 (1.47) 3.1 (2.44) 3.43 (2.25)
Treatment
Current treatment (total) 28 (51.9) 60 (53.1) 51 (78.5) 77 (77.8)
For mental health 27 (93.1) 51 (76.1) 44 (77.2) 71 (76.3)
For suicidal thoughts 9 (31) 8 (11.9) 14 (24.6) 25 (26.9)
For self-injury 3 (10.3) 2 (3) 4 (7) 9 (9.7)
Other 2 (6.9) 6 (9) 8 (14) 14 (14)
Living arrangements
Living independently 15 (27.8) 26 (22.6) 18 (27.7) 30 (30.3)
Living with parents 5 (9.3) 5 (4.3) 15 (23.1) 15 (15.2)
Living with flatmate(s) 4 (7.4) 8 (7) 2 (3.1) 3 (3)
Live with friend(s) 0 (0) 3 (2.6) 1 (1.5) 0 (0)
Living with a partner and/or dependent(s) 29 (53.7) 71 (61.7) 21 (32.3) 44 (44.4)
Living in supported accommodation 0 (0) 0 (0) 2 (3.1) 1 (1)
Living with a carer 0 (0) 0 (0) 1 (1.5) 1 (1)
Other 1 (1.9) 2 (1.7) 5 (7.7) 5 (5.1)
Occupational status
Employed 41 (75.9) 94 (81.7) 30 (46.2) 51 (51.5)
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Autism-Spectrum Quotient (AQ)
The Autism-Spectrum Quotient (AQ) is a 50-item
questionnaire assessing the number of self-reported
autistic traits [38]. The AQ has been shown to reliably
distinguishing those with and without a diagnosis of
ASC [38,39], with scores ≥26 indicating potential diag-
nosis of ASC [40].
Non-suicidal self-injury (NSSI)
The non-suicidal self-injury assessment tool (NSSI-AT)
[36] was used to screen for presence of any form of life-
time NSSI in the current sample. Participants were first
asked the screening question “Have you ever hurt your
body (e.g. cut, carve, burn, scratch really hard, punch)
on purpose but without wanting to end your life?”If yes,
participants then completed sections A–B of the NSSI-
AT to confirm that suicidality was not the primary reason
for their self-harm. Subsequently, responses were classified
as endorsing lifetime NSSI, or no lifetime NSSI.
The NSSI-AT was developed as a research tool to assess
NSSI online in non-clinical populations and has previ-
ously been shown to have adequate measurement proper-
ties in college students; test-retest reliability for any form
of NSSI was 0.74, with moderate correlations with related
behavioural problems [36]. One study has previously used
the NSSI-AT in an ASC adult sample and found evidence
in support of similar phenomenology of NSSI in those
with and without ASC [10].
Table 1 Participant characteristics (Continued)
Variables Group
GP male (n= 54) GP female (n= 115) ASC male (n= 65) ASC female (n= 99)
Mean (SD)/n(%)
Volunteering 2 (3.7) 6 (5.2) 3 (4.6) 9 (9.1)
Student 5 (9.3) 6 (5.2) 6 (9.2) 15 (15.2)
Unemployed/unable to work 4 (7.4) 9 (7.8) 25 (38.5) 22 (22.2)
Retired 2 (33.3) 0 (0) 1 (1.5) 2 (2)
Mental health or other condition
≥1 mental health or other condition 29 (53.7) 66 (57.4) 51 (78.5) 92 (92.9)
Current medication for mental health condition 10 (34.5) 26 (39.4) 26 (51) 56 (60.9)
Depression 25 (46.3) 51 (44.3) 47 (72.3) 84 (84.8)
Anxiety 19 (35.2) 42 (36.5) 40 (61.5) 77 (77.8)
Obsessive compulsive disorder 0 (0) 3 (2.6) 7 (10.8) 17 (17.2)
Bipolar disorder 1 (1.9) 2 (1.7) 2 (1.7) 6 (3.7)
Personality disorder 1 (1.9) 4 (3.5) 5 (7.7) 18 (18.2)
Schizophrenia 0 (0) 0 (0) 2 (3.1) 4 (4)
Anorexia nervosa 0 (0) 4 (3.5) 1 (1.5) 8 (8.1)
Bulimia 0 (0) 1 (0.9) 0 (0) 2 (2)
Myalgic encephalopathy 0 (0) 3 (2.6) 3 (4.6) 10 (10.1)
Tourettes 0 (0) 0 (0) 2 (3.1) 2 (2)
Epilepsy 1 (1.9) 4 (3.5) 1 (1.5) 4 (4)
Other 4 (7.4) 4 (3.5) 10 (15.4) 21 (21.2)
Developmental condition
≥1 developmental condition 2 (3.7) 1 (0.9) 15 (23.1) 22 (22.2)
Dyspraxia 1 (1.9) 1 (0.9) 7 (3.9) 11 (11.1)
Learning disability 1 (0) 0 (0) 1 (1.5) 0 (0)
Learning difficulty 0 (0) 0 (0) 0 (0) 2 (2)
Dyscalculia 0 (0) 0 (0) 2 (31) 1 (1)
Dyslexia 2 (3.7) 0 (0) 5 (7.7) 8 (8.1)
Attention deficit hyperactivity disorder 0 (0) 0 (0) 2 (3.1) 9 (9.1)
Developmental delay 0 (0) 0 (0) 0 (0) 1 (1)
Other 0 (0) 1 (0.9) 2 (3.1) 4 (4)
*NB, unmet support needs calculated by (total nareas support ideally liked—total nareas support actually received)
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Suicidality
Participants completed the Suicide Behaviours
Questionnaire-Revised (SBQ-R) [37], a 4-item self-report
questionnaire that assesses lifetime suicidal behaviour,
suicide ideation over the past 12 months, threat of
suicide attempt, and likelihood of suicidal behaviour in
the future. The SBQ-R has been validated for use in
general population and clinical samples to reliably dis-
tinguish suicide attempters from non-attempters [37],
and is widely used in research, with moderate-strong
evidence in support of internal consistency, structural
validity, hypothesis testing, and criterion validity in clinical
and non-clinical samples [7]. Internal consistency for the
whole scale was acceptable in both autistic adults (α=.76)
and general population adults (α=.768).
Ethical approval
The current study received ethical approval from Coventry
University Psychology Ethics Committee and was approved
by the autism steering group who fed back on the ques-
tionnaire, and the scientific advisory group at the Autism
Research Centre, University of Cambridge, prior to
recruiting participants registered in the Cambridge Autism
Research Database (CARD).
Procedure
Participants with and without ASC diagnosis were invited
to complete an online survey about understanding and
preventing mental health problems, self-injury, and suicid-
ality. Participants could take part regardless of prior experi-
ence of mental health difficulties, self-injury or suicidality.
Participants read the participant information and indicated
informed consent to participate via an online form. Partici-
pants were fully briefed about the nature of the research,
that they could skip sections and/or questions that made
them feel uncomfortable, and were provided information
about relevant support services before and after taking
part in the study. Participants subsequently completed
questions on demographics, diagnoses (mental health,
developmental conditions, and ASC), NSSI-AT, camoufla-
ging, AQ, SBQ-R, current treatment (for mental health,
self-injury, or suicidality), and support (areas in which
support was actually received and ideally liked but not yet
received).
Analysis approach
Data were analysed using SPSS 24. Chi-square analysis
was used to explore group differences in frequency of
lifetime NSSI, lifetime experience of camouflaging, and
demographics, with odds ratios (with 95% confidence in-
tervals) calculated as a measure of effect size. Independent
samples ttests were used to compare total scores on the
SBQ-R, AQ, and camouflaging questionnaires between
groups, with Cohen’sdas a measure of effect size (where
0.2 = small, 0.5 = medium, and 0.8 = large effect) [41]. One
sample ttests compared SBQ-R total scores to established
cut-offs in general and psychiatric populations. Spearman’s
correlations were used to explore inter-correlations between
all variables in each group (where 0.1 = small, 0.3 = medium,
and 0.5 = large effect). Multiple hierarchical regressions
subsequently explored whether significant associations
between demographics and diagnoses with suicidality
remained when controlling for significant covariates.
The SBQ-R was non-normally distributed. Analyses were
therefore undertaken using bootstrapping techniques, a
robust analysis technique which is reliable even when as-
sumptions of a symmetric distribution are not met [42].
Utilising this robust analysis technique did not alter the
pattern of results, with similar direction and magnitude
of effects and statistical significance found using boot-
strapping or normal analytic approach; therefore, untrans-
formed results are reported for ease of interpretation.
Results
Group comparisons
Suicidality
There was no significant difference in total SBQ-R scores
between autistic males and autistic females (t(162) = .671,
p= .503), so results were pooled. A one sample ttest
showed that autistic adults SBQ-R total scores were
significantly higher than the recommended cut-off for
the general population (7) (t(163) = 10.92, p< .001), and
psychiatric populations (8) (t(163) = 7.71, p< .001) [33].
Amajority(72%)ofautisticadultsscoredatorabove
the cut-off for psychiatric populations (8) (Table 1).
There was a significant difference in total SBQ-R
scores between general population (GP) males and females
(t(167) = 2.06, p= .041), so data from males and females
were analysed separately. One sample ttests showed
that GP males SBQ-R scores were not significantly
different from the recommended cut-off for the gen-
eral (t(53) = .956, p= .343) or psychiatric population
(t(162) = .671, p= .503). GP females scored significantly
lower than the recommended cut off for the general
(t(114) = 2.211, p= .029) and psychiatric population
(t(114) = 5.694, p< .001) (Table 1).
Autistic adults scored significantly higher on the SBQ-R
than GP adults (t(331) = 9.131, p< .001, d=1)andweresig-
nificantly more likely to score above the psychiatric cut-off
for suicide risk (72%) than GP adults (33.7%) (χ
2
(1) = 48.77,
p< .001, OR 5.04, 95% CI 3.16–8.04) (Table 1).
NSSI
Significantly more autistic females (74%) reported NSSI
than autistic males (53.8%) (χ
2
(1) = 6.97, p< .01, OR 2.43,
95% CI 1.25–4.74). There was no significant sex difference
in NSSI in the GP group (χ
2
(1) = .486, p=.486). Autistic
Cassidy et al. Molecular Autism (2018) 9:42 Page 6 of 14
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adults were significantly more likely to report lifetime
NSSI (65%) than GP adults (29.8%) (χ
2
(1) = 42.91, p<.001,
OR 4.55, 95% CI 2.86–7.23) (Table 1).
Demographics
Compared to the general population, autistic adults reported
significantly lower satisfaction with their living arrangements
(t(146) = 2.82, p= .005; d= .4) were significantly more likely
to be unemployed (χ
2
(1) = 33.95, p< .001, OR 4.07, 95% CI
2.5–6.61), be diagnosed with at least one co-occurring devel-
opmental condition (χ
2
(1) = 34.02, p< .001, OR 16.12, 95%
CI 4.86–53.47), at least one mental health or other condition
(χ
2
(1) = 39.18, p< .001, OR 5.3, 95% CI 3.06–9.19), depres-
sion (χ
2
(1) = 43.1, p< .001, OR 4.86, 95% CI 2.98–7.91),
anxiety (χ
2
(1) = 41.56, p< .001, OR 4.41, 95% CI 2.78–6.99),
and report higher unmet support needs (t(176) = 4.91,
p< .001; d= .87) (Table 1).
Camouflaging
There was no significant difference between autistic
males (89.2%) and autistic females (90.9%) in terms of
whether they attempted to camouflage their ASC in
order to fit in in social situations (χ
2
(1) = .126, p= .723).
However, autistic females scored significantly higher on
the camouflaging questionnaire overall (14.7, SD 3.61)
than autistic males (12.9, SD 4.06) (t(146) = 2.82, p=.005;
d=.47)(Table1).
Predictors of suicidality in ASC
Table 2shows the results of all inter correlations between
variables in the ASC group. Lifetime NSSI, camouflaging,
ADHD, depression, anxiety, unmet support needs, and
satisfaction with living arrangements all significantly
correlated with suicidality (total SBQ-R scores). How-
ever, age of diagnosis was not significantly correlated
with any other variables.
Hierarchical regression models were performed with
total SBQ-R scores as the outcome variable. To statisti-
cally control for these variables, age at testing and gender
were entered into the first step, and employment, satisfac-
tion with living arrangements, developmental conditions,
depression, and anxiety entered into the second step. The
third step explored additional variance accounted for
by the predictor variable. Separate models explored the
additional predictive contribution of ASC diagnosis (in
the combined ASC and GP groups), lifetime experience
of NSSI, camouflaging questionnaire total scores, and
unmet support needs (in the ASC sub-group), to the
model. Age of ASC diagnosis was not explored further as
a unique predictor given that this did not significantly
correlate with any other variables (Table 2).
ASC diagnosis
In step one, the regression model containing sex and
age significantly predicted SBQ-R scores (F(2,330) = 6.99,
p< .001), accounting for 4.1% of the variance. In step two,
employment, satisfaction with living arrangements, pres-
ence of at least one developmental condition, depression,
and anxiety accounted for significantly more of the vari-
ance (33.4%) in SBQ-R scores (F(5,325) = 34.79, p<.001).
In step three, autism diagnosis accounted for significantly
more of the variance (4.5%) in SBQ-R scores (F(1,324) =
24.9, p< .001) (Table 3).
NSSI
In step one, the regression model containing sex and age
did not significantly predict SBQ-R scores (F(2,158) = 1.99,
p= .141), accounting for only 2.5% of the variance. In step
two, employment, satisfaction with living arrangements,
presence of at least one developmental condition, depres-
sion, and anxiety accounted for significantly more of
the variance (19.9%) in SBQ-R scores (F(5,153) = 7.84,
p< .001). In step three, NSSI accounted for significantly
more of the variance (4%) in SBQ-R scores (F(1,152) =
6.78, p= .005) (Table 4).
Camouflaging
In step one, the regression model containing sex and age
did not significantly predict SBQ-R scores (F(2,145) = .529,
p= .59), accounting for only 0.7% of the variance. In step
two, employment, satisfaction with living arrangements, at
least one developmental condition, depression, and anxiety
accounted for significantly more of the variance (20.7%)
in SBQ-R scores (F(5,140) = 7.39, p< .001). In step
three, camouflaging total scores accounted for signifi-
cantly more of the variance (3.5%) in SBQ-R scores
(F(1,139) = 6.56, p= .01) (Table 5).
Unmet support needs
In step one, the regression model containing sex and age
did not significantly predict SBQ-R scores (F(2,123) = .233,
p= .793), accounting for only 0.4% of the variance. In step
two, employment, satisfaction with living arrangements, at
least one developmental condition, depression, and anxiety
accounted for significantly more of the variance (13.5%) in
SBQ-R scores (F(5,118) = 3.7, p= .004). In step three,
unmet support needs accounted for significantly more
of the variance (3.1%) in SBQ-R scores (F(1,117) = 4.32,
p=.04)(Table 6).
Predictors of suicidality in the general population
Table 7shows the results of all inter correlations between
variables in the GP group. Self-reported autistic traits (AQ
total scores), lifetime NSSI, depression, anxiety, satisfaction
with living arrangements and employment all significantly
correlated with suicidality (total SBQ-R scores).
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Table 2 Means, standard deviations and inter-correlations for all variables in the ASC group
Variable AQ Age of ASC
diagnosis
SBQ-R NSSI Lifetime
camouflage
Camouflage
score
Unmet
support
needs
≥1 developmental
condition
ADHD ≥1 mental
health/other
condition
Depression Anxiety Satisfaction
with living
arrangements
Employed Sex Age at
testing
AQ –
Age of ASC
diagnosis
.147 –
SBQ-R .099 −.138 –
NSSI .126 −.125 .277* –
Lifetime
camouflage
.053 −.048 .245* .33* –
Camouflage
score
.058 .107 .164* .085 ––
Unmet support
needs
.101 −.087 .247* .109 .088 .085 –
≥1
developmental
condition
−.008 −.201* .064 .009 .068 .073 −.023 –
ADHD −.02 −.113 .182* .077 .088 .001 .058 .497* –
≥1 mental
health/other
condition
.259* −.035 .365* .188* .182* .112 .063 .032 .103 –
Depression .199* .128 .322* .088 .143 .076 −.035 −.093 −.048 .764* –
Anxiety .161* .012 .325* .286* .201* .119 .079 .084 .062 .605 .59* –
Satisfaction
with living
arrangements
−.072 .081 −.257* −.047 .003 .170* −.386* −.063 −.054 .034 .037 −.15 –
Employed −.174* .023 −.114 .078 .037 .044 −.096 .021 .076 −.205* −.143 −.102 .135 –
Sex .105 .105 .053 .208* .028 .228* .07 −.01 .118 .212* .153 .176* .212* .052 –
Age at testing .104 .91* −.137 −.152 −.073 .096 −.141 −.2* −.134 −.017 .131 .028 .076 .03 −.117 –
Mean/% 36.42 34.85 10.4 64.63 90.2 13.99 3.29 22.5 6.7 87.19 79.88 71.34 68.47 28.66 39.63 39.93
SD 8.03 13.03 3.98 –– 3.88 2.33 –––––26.67 ––11.03
Note: AQ, Autism-Spectrum Quotient (total score); SBQ-R, Suicidal Behaviours Questionnaire-Revised (total score); Lifetime camouflage , attempting to camouflage autism in order to fit in in social situations; Camouflage
score, total score on the camouflaging questionnaire; Mismatch,(n areas of support ideally liked –nareas actually received); ≥1 developmental condition, at least one co-occurring developmental condition; ≥1 mental
health/other condition, at least one co-occurring mental health or other condition; Sex, % autistic male; Age at testing, age in years at testing. *Significant correlations p< .05
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A hierarchical regression model was thus performed
with total SBQ-R scores as the outcome variable. To
statistically control for these variables, age at testing and
gender were entered into the first step. To statistically con-
trol for additional co-variates, employment, satisfaction
with living arrangements, developmental conditions, de-
pression, and anxiety were entered into the second step.
The third and final step explored much additional variance
in suicidality was explained by self-reported autistic traits.
Autistic traits
In step one, the regression model containing sex and
age significantly predicted SBQ-R scores (F(2,166) = 7.57,
p< .001), accounting for 8.4% of the variance. In step two,
employment, satisfaction with living arrangements, pres-
ence of at least one developmental condition, depression,
and anxiety accounted for significantly more of the vari-
ance (31.5%) in SBQ-R scores (F(5,161) = 16.85, p<.001).
In step three, self-reported autistic traits accounted for
Table 3 Hierarchical regression with diagnostic group (ASC vs.
general population) predicting SBQ-R
BSEBβ
Step 1
Constant 12.408 1.135
Sex −.635 .460 −.074
Age −.070 .020 −.188*
Step 2
Constant 13.591 1.382
Employed −.768 .395 −.090
Satisfaction with living arrangements −.045 .008 −.280*
≥1 developmental condition .827 .567 .066
Depression 2.856 .482 .339*
Anxiety .898 .474 .110
Step 3
Constant 8.918 1.630
Diagnostic group 2.038 .408 .249*
Note: R
2
= .041 fo r step 1, ΔR
2
= .334 for step 2, ΔR
2
= .045 for step 3 (p < .001).
*p < .001. N= 333
Table 4 Hierarchical regressions with NSSI predicting SBQ-R in
the ASC group
BSEBβ
Step 1
Constant 12.283 1.661
Sex .153 .642 .019
Age at testing −.055 .029 −.153
Step 2
Constant 12.822 1.896
Employed −.261 .578 −.033
Satisfaction with living arrangements −.037 .011 −.251*
≥1 developmental condition −.194 .707 −.020
Depression 2.716 .903 .276*
Anxiety .971 .809 .111
Step 3
Constant 12.131 1.869
NSSI 1.803 .631 .215*
Note: R
2
= .012 fo r step 1, ΔR
2
= .199 for step 2, ΔR
2
= .04 for step 3 (p = .005).
*p < .01.N=161
Table 5 Hierarchical regression with camouflaging total scores
predicting SBQ-R in the ASC group
BSEBβ
Step 1
Constant 11.139 1.730
Sex .335 .668 .042
Age at testing −.024 .030 −.068
Step 2
Constant 12.033 2.043
Employed −.291 .599 −.037
Satisfaction with living arrangements −.045 .012 −.307*
≥1 developmental condition .275 .736 .029
Depression 2.725 .971 .270*
Anxiety .803 .850 .090
Step 3
Constant 10.217 2.126
Camouflage score .200 .078 .198*
Note: R
2
= .006 fo r step 1, ΔR
2
= .207 for step 2, ΔR
2
= .035 for step 3 (p = .01).
*p < .01.N=148
Table 6 Hierarchical regression with unmet support needs
predicting SBQ-R in the ASC group
BSEBβ
Step 1
Constant 11.738 1.759
Sex .142 .718 .018
Age at testing −.020 .032 −.058
Step 2
Constant 11.296 2.148
Employed .060 .690 .008
Satisfaction with living arrangements −.028 .012 −.204*
≥1 developmental condition .032 .830 .003
Depression 2.771 1.089 .264*
Anxiety .826 .963 .090
Step 3
Constant 8.394 2.537
Unmet support needs .329 .158 .195*
Note: R
2
= .004 fo r step 1, ΔR
2
= .135 for step 2, ΔR
2
= .031 for step 3 (p = .04).
*p < .05. N= 126
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significantly more of the variance (3.2%) in SBQ-R scores
(F(1,160) = 9.08, p= .003) (Table 8).
Discussion
Previous research exploring suicidality in ASC has failed to
include adequately sized samples, matched comparison
groups, explore risk or protective factors [2,3,6], or include
validated suicidality assessment tools [7]. The current study
aimed to address these weaknesses of previous research, to
identify common and unique risk markers for suicidality in
ASC. Specifically, whether there are unique aspects of ASC
and autistic traits that increase risk of suicidality, after
statistically controlling for common risk factors such as age,
sex, employment, or mental health. We then explored
possible unique risk factors which could explain increased
risk of suicide in ASC, identified by our steering group of
autistic adults: camouflaging one’s ASC in an attempt to fit
in in social situations, age of ASC diagnosis, whether people
felt they received the support they required, and NSSI.
Previous studies have not systematically studied unique and
common risk markers for suicidality in ASC compared to
the general population, which has prevented development
of tailored suicide prevention strategies for this group [6].
Results are consistent with previous findings that autistic
adults are at significantly increased risk of suicidality com-
pared to the general population [2]. A majority (72%) of
autistic adults scored significantly above the recommended
cut-off for suicide risk in psychiatric populations, signifi-
cantly higher than general population adults (33%) with
similar age and gender composition. This significant
Table 7 Means, standard deviations and inter-correlations for all variables in the general population group
Variable AQ SBQ-R NSSI Unmet
support
needs
≥1
developmental
condition
≥1 mental
health/other
condition
Depression Anxiety Satisfaction
with living
arrangements
Employed Sex Age at
testing
AQ –
SBQ-R .329* –
NSSI .009 .233* –
Unmet support
needs
.277 .205 −.191 –
≥1
developmental
condition
.116 .097 .011 ––
≥1 mental health/
other condition
.168* .373* .132 .052 .028 –
Depression .232* .432* 193* .091 −.059 .798* –
Anxiety .206* .301* 194* −.136 .008 .663 .559* –
Satisfaction with
living
arrangements
.136 −.487* −.119 −.193 −.005 .212* −.181 −.173* –
Employed .149 .185* .029 .392 .044 .175* .169* −.115 .118 –
Sex −.269* −.157* −.054 −.238 .1 −.035 −.018 .013 .238* .068 –
Age at testing −.15 −.257* −.23* −.121 .087 .082 −.032 −.148 .312* .121 .102 –
Mean/% 19.86 6.72 29.8 1.56 2.9 56.2 44.97 19.24 78.44 7.69 31.95 42.72
SD 7.87 3.32 –1.6 ––––23.16 ––10.87
Note: AQ, Autism-Spectrum Quotient (total score); SBQ-R, Suicidal Behaviours Questionnaire-Revised (total score); Mismatch, (n areas of support ideally liked –nareas actually
received); ≥1 developmental condition; ≥1 mental health/other condition, at least one mental health or other condition; Sex, %male;Age at testing, age in years at testing.
*Significant correlations p<.05
Table 8 Hierarchical regressions with autistic traits predicting
SBQ-R in the general population group
Autistic traits BSEBβ
Step 1
Constant 11.335 1.244
Sex −.940 .530 −.132
Age −.074 .023 −.244*
Step 2
Constant 5.690 3.193
Employed −.561 .517 −.068
Satisfaction with living Arrangements −.051 .010 −.357*
≥1 developmental condition 3.410 1.554 .136*
Depression 2.321 .501 .349*
Anxiety .119 .517 .017
Step 3
Constant 2.597 3.281
Autistic traits .083 .027 .196*
Note: R
2
= .084 fo r step 1, ΔR
2
= .315 for step 2, ΔR
2
= .032 for step 3 (p=.003).
*p < .05.N=169
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association between ASC diagnosis and suicidality
remained when controlling for a number of demographics
and diagnoses, known to increase or decrease risk of suicid-
ality in the general population (employment, depression,
anxiety, and satisfaction withlivingarrangements).Add-
itionally, the significant association between self-reported
autistic traits in the general population and suicidality
remained after statistically controlling for these demograph-
ics and diagnoses. These results suggest that autism diagno-
sis and autistic traits explain significant additional variance
in suicidality beyond a range of known risk factors, and are
therefore independent risk markers for suicidality. This is
consistent with research showing that ASC diagnosis is an
independent risk marker for suicide attempts when control-
ling for a range of demographics and co-occurring diagno-
ses [19]. These findings suggest additional unique
contributors to suicidality in ASC, which must be ad-
dressed in addition to important well-known factors such
as mental health, employment, and living arrangements.
The current study explored a potentially unique risk
marker for suicidality in ASC, identified by our steering
group of autistic adults: tendency to camouflage one’s
ASC in order to cope in social situations. Previous
research [29,32] and discussions with our steering
groupidentifiedcamouflagingasanimportantpotential
barrier to timely ASC diagnosis, and having a negative
impact on mental health and risk of suicidality. Previous
research has also suggested that camouflaging is primarily
experienced by autistic females [31,33], which may at least
in part explain why this group has been under-diagnosed
[43]. Results from the current study however showed sub-
tle differences in camouflaging behaviour between autistic
males and females: there was no sex difference in reporting
whether one engages in camouflaging behaviour, but
autistic females tended to report that they camouflaged
across more situations, more frequently and more of
thetimethanautisticmales.
Camouflaging significantly predicted suicidality in the
ASC group, after controlling for age, sex, presence of at
least one developmental condition, depression, anxiety,
employment, and satisfaction with living arrangements.
Camouflaging and age of ASC diagnosis, and suicidality
and age of ASC diagnosis were not significantly correlated.
This suggests that camouflaging is directly associated with
suicidality rather than in combination with delay in ASC
diagnosis. Camouflaging also explained significant add-
itional variance in suicidality above depression or anxiety,
suggesting that the association with suicidality is, at least
in part, independent of mental health. This is the first
evidence of camouflaging being a unique independent
risk factor for suicidality in ASC.
In order to engage in camouflaging, one must have
insight into one’s own difficulties, how these may be nega-
tively perceived by others, and have a strong motivation to
adapt one’s social behaviour to be accepted. Understand-
ing associations between these factors with camouflaging,
and the consequent impact on mental health would be
valuable. For example, autistic people who have greater
insight into their own difficulties are more likely to be
depressed than those with less insight [44], and autistic
people are able to accurately predict how family members
perceive them, despite being different to their own view
[45]. It would be interesting to explore whether perspective
taking ability and insight into one’s own difficulties increase
likelihood of engaging in camouflaging behaviour with con-
sequent negative impact on mental health and suicidality.
Importantly, our findings challenge the assumption
that autistic people are socially unmotivated, consistent
with calls for more accurate and useful autism research,
embracing the unique nature of social interest in autism
[46]. It is perhaps more accurate to acknowledge a “double
empathy problem”, where autistic people are misinter-
preted by non-autistic people and vice versa [45,47,48],
which contribute to feelings of isolation among autistic
people [49]. Increasing acceptance of autistic people in
society could therefore lead to a reduced need for camou-
flaging and increased feelings of belonging—aprotective
factor for suicidality [17,23].
Contrary to expectations, and discussions with our
autistic steering group, age of ASC diagnosis was not
significantly correlated with any other variables, such as
mental health problems, suicidality, or NSSI. However,
this may have been due to the fact that the mean age of
ASC diagnosis was 34 years, and therefore, participants
represent autistic people diagnosed in adulthood. Future
research will need to explore whether those diagnosed in
childhood are significantly less likely to experience mental
health problems of suicidality compared to those diag-
nosed in adulthood. Another important theme identified
from discussions with our steering group was lack of
access to support, which could compound mental health
difficulties and suicidality. Previous research has shown
that the autistic community is disconnected from psychi-
atric services [18], as many practitioners are not trained in
ASC [50]. The current study therefore quantitatively
explored the mismatch between the number of areas an
individual would ideally like support, compared to the
number of areas they actually received support. These
unmet support needs significantly predicted suicidality
in the ASC group when controlling for the aforemen-
tioned variables. Hence, a clear recommendation for
policy and practice to reduce suicide risk in autistic
adults, a high-risk group for dying by suicide [15], is to
urgently identify and address unmet support needs in
this group. Meeting this shortfall in support could, at
least in part, help reduce high rates of suicidality and
death by suicide in the autistic community. Research
from our group is exploring in more depth barriers and
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enablers in accessing treatment and support in autistic
adults, to help assist in service planning.
The rate of NSSI in the ASC group (63.6%) was signifi-
cantly higher than the general population group (29.8%),
and similar to the rate reported in previous research [10]
(50%), which also utilised the NSSI-AT in autistic adults.
NSSI also significantly predicted suicidality in autistic
adults, after controlling for a range of known risk factors.
Hence, NSSI should not continue to be overlooked, or
seen as part of ASC, and rather must be addressed in its
own right. Our findings are therefore an important call to
action for the research community and clinicians to
increase understanding and support for those with ASC
experiencing NSSI. However, future studies will need to
explore whether this rate of NSSI in ASC adults remains
stable, and explore the measurement properties of NSSI
assessment tools in ASC.
The current study has a number of strengths as well
as limitations. This study is the first to use measures of
suicidality (SBQ-R) and NSSI (NSSI-AT) that have good
evidence of validity, albeit not yet in autistic adults [7,10].
There is a paucity of validated outcome measures for
autistic adults, and using tools validated for the general
population is an important stop gap until tools adapted
for autistic people become available [7,10,51–53]. The
current study was only cross-sectional, and it is unclear
for example whether unmet support needs are a cause or
consequence of suicidality. The current study focused on
adults, without intellectual disability (ID), and it is un-
known whether autism and autistic traits would similarly
be a unique risk marker for those with co-occurring ID.
Although autism, autistic traits, unmet support needs, and
camouflaging explained significant additional variance in
suicidality when statistically controlling for a number of
other factors, the additional variance explained was small.
ASC diagnosis was assessed by self-report only; however,
a majority of participants confirmed the clinic where this
diagnosis was obtained. Lifetime suicide attempts in the
general population (8%) and ASC group (38%) are similar
to previous studies [2,17], which suggests that the sample
was not biased in this respect. However, lifetime experi-
ence of depression in the general population (44.9%) and
ASC group (80%) were much higher than previous esti-
mates [2,22,54], despite participants not being recruited
because of experience with mental health problems. The
rate of mental health difficulties in the current sample
therefore may not be representative of the general or
autistic populations. A majority of participants in the
steering group and online survey were female. There-
fore, it could be argued that the topics explored in the
survey and study findings apply mostly to autistic females
and may not be generalisable to autistic males. However, a
majority of autistic males and autistic females reported
camouflaging, and regression analyses statistically
controlled for sex, suggesting this and other risk
markers apply to both sexes.
A key strength and novel aspect of the current study
was the participatory research element with a group of
autistic adults, who refined the focus of the study, and
the content of the survey. This ensured that the study
included a range of possible unique and common risk
factors for suicidality not explored or considered in pre-
vious research on this topic. It also ensured high content
validity of the survey, which was refined through three
iterations of feedback from the steering group. Previous
research has shown that the views of the autistic com-
munity which the research affects are rarely included,
which can hamper the potential benefits of ASC research
for the wider community [11]. Our study demonstrates
the importance of including the voices of autistic people
in important and sensitive research that can impact their
lives.
Conclusions
The current study is the first to use validated assessment
tools, and survey co-designed with autistic people, to
explore unique risk factors for suicidality in this group.
Results reiterate that rates of suicidality in autistic adults
are higher than the general population, and ASC diagnosis
and autistic traits are independent risk markers for suicid-
ality. Importantly, unique risk markers for suicidality in
ASC include camouflaging one’s ASC in order to fit in in
social situations and number of unmet support needs.
These explain small but significant additional variance in
suicidality in ASC, above a range of known risk factors
common with the general population. Future research
must further explore these and identify other unique
mechanisms driving suicidality in ASC to develop new
effective suicide prevention strategies for this group.
Abbreviations
ADHD: Attention deficit hyperactivity disorder; AQ: Autism-Spectrum
Quotient; AS: Asperger syndrome; ASC: Autism spectrum condition;
GP: General population; HFA: High functioning autism; ID: Intellectual
disability; NSSI: Non-suicidal self-injury; NSSI-AT: Non-suicidal self-injury as-
sessment tool; PDD: Pervasive developmental disorder; PDD-NOS: Pervasive
Developmental Disorder Not Otherwise Specified; SBQ-R: Suicidal Behaviours
Questionnaire-Revised
Acknowledgements
We would like to sincerely thank the members of the Coventry Autism
steering group, who assisted the researchers in designing and advertising
the study. We would also like to thank Paula Smith, database manager at the
Autism Research Centre, University of Cambridge for her assistance with
contacting participants registered in the Cambridge Autism Research
Database. We would also like to thank everyone for taking part in the study.
We appreciate that this is a difficult topic to think and talk about, and greatly
appreciate their support in increasing understanding and prevention of suicide.
Funding
This work was supported by the Economic and Social Research Council
[grant number ES/N000501/2]. This work also received support from a
research pump prime award from Coventry University. SBC was supported
by the Autism Research Trust, the MRC, and the National Institute for Health
Cassidy et al. Molecular Autism (2018) 9:42 Page 12 of 14
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Research (NIHR) Collaboration for Leadership in Applied Health Research and
Care East of England at Cambridgeshire and Peterborough NHS Foundation
Trust. The views expressed are those of the authors and not necessarily
those of the NHS, the NIHR, or the Department of Health.
Availability of data and materials
The datasets generated and/or analysed during the current study are not
publicly available due to participants not consenting to public sharing of
data, but anonymised data are available from the corresponding author (SC)
on reasonable request.
Authors’contributions
SC conceived and designed the study, collected and analysed the data, and
wrote the manuscript; LB helped design the study, collected the data, and
provided critical feedback on the manuscript. RS helped design the study,
collected the data, and provided critical feedback on the manuscript. SB
helped design the study and provided critical feedback on the manuscript.
All authors read and approved the final manuscript.
Ethics approval and consent to participate
Ethical approval for the current study was granted by the School of
Psychology Ethics Committee at Coventry University and was also approved
by the study steering group and Cambridge University Database Committee.
Competing interests
The authors declare that they have no competing interests.
Publisher’sNote
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Author details
1
School of Psychology, University of Nottingham, University Park,
Nottingham NG7 2RD, UK.
2
Centre for Innovative Research across the Life
Course, Coventry University, Coventry, UK.
3
Autism Research Centre,
University of Cambridge, Cambridge, UK.
4
Coventry and Warwickshire
Partnership Trust, Coventry, UK.
5
Cambridge Lifetime Asperger Syndrome
Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust,
Cambridge, UK.
Received: 22 February 2018 Accepted: 22 July 2018
References
1. Zahid S, Upthegrove R. Suicidality in autistic spectrum disorders: a
systematic review. Crisis. 2017;38(4):237.
2. Cassidy S, Bradley P, Robinson J, Allison C, McHugh M, Baron-Cohen S.
Suicidal ideation and suicide plans or attempts in adults with Asperger's
syndrome attending a specialist diagnostic clinic: a clinical cohort study.
Lancet Psychiatry. 2014;1(2):142–7.
3. Segers M, Rawana J. What do we know about suicidality in autism spectrum
disorders? A systematic review. Autism Res. 2014;7(4):507–21.
4. Hedley D, UljarevićM. Systematic review of suicide in autism spectrum
disorder: current trends and implications. Curr Dev Disord Rep. 2018;5(1):65-76.
5. Croen LA, Zerbo O, Qian Y, Massolo ML, Rich S, Sidney S, Kripke C. The
health status of adults on the autism spectrum. Autism. 2015;19(7):814–23.
6. Cassidy S, Rodgers J. Understanding and prevention of suicide in autism.
Lancet Psychiatry. 2017;4(6):e11.
7. Cassidy S, Bradley L, Wigham S, Bowen E, Rodgers J. Measurement
properties of tools used to assess suicidality in adults with and without
autism spectrum conditions: a systematic review. Clin Psychol Rev. In Press
8. Hannon G, Taylor EP. Suicidal behaviour in adolescents and young adults
with ASD: Findings from a systematic review. Clinical psychology review.
2013;33(8):1197-204.
9. Ribeiro JD, Franklin JC, Fox KR, Bentley KH, Kleiman EM, Chang BP, Nock MK.
Self-injurious thoughts and behaviors as risk factors for future suicide
ideation, attempts, and death: a meta-analysis of longitudinal studies.
Psychol Med. 2016;46(2):225–36.
10. Maddox BB, Trubanova A, White SW. Untended wounds: non-suicidal self-
injury in adults with autism spectrum disorder. Autism. 2017;21(4):412–22.
11. Pellicano L, Dinsmore A, Charman T. A Future Made Together: Shaping
autism research in the UK. 2013. http://discovery.ucl.ac.uk/1495583/1/A_
Future_Made_Together_1.2_LR.pdf. Accessed 21 Feb 2018.
12. Nock MK, Borges G, Bromet EJ, Alonso J, Angermeyer M, Beautrais A, et al.
Cross-national prevalence and risk factors for suicidal ideation, plans and
attempts. Br J Psychiatry. 2008;192(2):98–105.
13. Kessler RC, Borges G, Walters EE. Prevalence of and risk factors for lifetime
suicide attempts in the National Comorbidity Survey. Arch Gen Psychiatry.
1999;56(7):617–26.
14. O'Carroll PW. Attempted suicide among young adults: progress toward a
meaningful estimate of prevalence. Am J Psychiatr. 1992;149:41.
15. Hirvikoski T, Mittendorfer-Rutz E, Boman M, Larsson H, Lichtenstein P, Bölte S.
Premature mortality in autism spectrum disorder. Br J Psychiatry. 2016;208(3):
232–8.
16. Upthegrove R, Abu-Akel A, Chisholm K, Lin A, Zahid S, Pelton M, Apperly I,
Hansen PC, Wood SJ. Autism and psychosis: clinical implications for
depression and suicide. Schizophr Res. 2018;195:80–5.
17. Pelton MK, Cassidy SA. Are autistic traits associated with suicidality? A test
of the interpersonal-psychological theory of suicide in a non-clinical young
adult sample. Autism Res. 2017;10(11):1891–904.
18. Takara K, Kondo T. Comorbid atypical autistic traits as a potential risk factor
for suicide attempts among adult depressed patients: a case–control study.
Ann General Psychiatry. 2014;13(1):33.
19. Chen MH, Pan TL, Lan WH, Hsu JW, Huang KL, Su TP, Li CT, Lin WC, Wei HT,
Chen TJ, Bai YM. Risk of suicide attempts among adolescents and young
adults with autism spectrum disorder: a Nationwide longitudinal follow-up
study. J Clin Psychiatry. 2017;78(9):e1174–9.
20. Barraclough BJ, Bunch J, Nelson B, Sainsbury P. A hundred cases of suicide:
clinical aspects. Br J Psychiatry. 1974;125(587):355–73.
21. Wigham S, Barton S, Parr JR, Rodgers J. A systematic review of the rates of
depression in children and adults with high-functioning autism spectrum
disorder. J Ment Health Res Intellect Disabil. 2017;10(4):267–87.
22. Lever AG, Geurts HM. Psychiatric co-occurring symptoms and disorders in
young, middle-aged, and older adults with autism spectrum disorder. J
Autism Dev Disord. 2016;46(6):1916–30.
23. Van Orden KA, Witte TK, Cukrowicz KC, Braithwaite SR, Selby EA, Joiner TE Jr.
The interpersonal theory of suicide. Psychol Rev. 2010;117(2):575.
24. Orsmond GI, Shattuck PT, Cooper BP, Sterzing PR, Anderson KA. Social
participation among young adults with an autism spectrum disorder. J
Autism Dev Disord. 2013;43(11):2710–9.
25. Hedley D, UljarevićM, Wilmot M, Richdale A, Dissanayake C. Brief report:
social support, depression and suicidal ideation in adults with autism
spectrum disorder. J Autism Dev Disord. 2017;47(11):3669–77.
26. Hedley D, UljarevićM, Wilmot M, Richdale A, Dissanayake C. Understanding
depression and thoughts of self-harm in autism: a potential mechanism
involving loneliness. Res Autism Spectr Disord. 2018;46:1–7.
27. Crane L, Chester JW, Goddard L, Henry LA, Hill E. Experiences of autism
diagnosis: a survey of over 1000 parents in the United Kingdom. Autism.
2016;20(2):153–62.
28. Jones L, Goddard L, Hill EL, Henry LA, Crane L. Experiences of receiving a
diagnosis of autism spectrum disorder: a survey of adults in the United
Kingdom. J Autism Dev Disord. 2014;44(12):3033–44.
29. Lai MC, Baron-Cohen S. Identifying the lost generation of adults with autism
spectrum conditions. Lancet Psychiatry. 2015;2(11):1013–27.
30. World Health Organisation. (2018). World Health Statistics. Global Health
Observatory data. Available from: http://apps.who.int/iris/bitstream/handle/
10665/272596/9789241565585-eng.pdf?ua=1. Accessed 21 Feb 2018.
31. Lai MC, Lombardo MV, Ruigrok AN, Chakrabarti B, Auyeung B, Szatmari P,
Happé F, Baron-Cohen S, MRC AIMS Consortium. Quantifying and exploring
camouflaging in men and women with autism. Autism. 2017;21(6):690–702.
32. Hull L, Petrides KV, Allison C, Smith P, Baron-Cohen S, Lai MC, Mandy W.
“Putting on my best normal”: social camouflaging in adults with autism
spectrum conditions. J Autism Dev Disord. 2017;47(8):2519–34.
33. Rynkiewicz A, Schuller B, Marchi E, Piana S, Camurri A, Lassalle A, Baron-Cohen S.
An investigation of the ‘female camouflage effect’in autism using a computerized
ADOS-2 and a test of sex/gender differences. Mol Autism. 2016;7(1):10.
34. Duerden EG, Oatley HK, Mak-Fan KM, McGrath PA, Taylor MJ, Szatmari P, Roberts
SW. Risk factors associated with self-injurious behaviors in children and adolescents
with autism spectrum disorders. J Autism Dev Disord. 2012;42(11):2460–70.
35. South M, Ozonoff S, McMahon WM. Repetitive behavior profiles in Asperger
syndrome and high-functioning autism. J Autism Dev Disord. 2005;35(2):145–58.
Cassidy et al. Molecular Autism (2018) 9:42 Page 13 of 14
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

36. Whitlock J, Exner-Cortens D, Purington A. Assessment of nonsuicidal self-injury:
development and initial validation of the non-suicidal self-injury–assessment
tool (NSSI-AT). Psychol Assess. 2014;26(3):935.
37. Osman A, Bagge CL, Gutierrez PM, Konick LC, Kopper BA, Barrios FX. The
Suicidal Behaviors Questionnaire-Revised (SBQ-R): validation with clinical
and nonclinical samples. Assessment. 2001;8(4):443–54.
38. Baron-Cohen S, Wheelwright S, Skinner R, Martin J, Clubley E. The autism-
spectrum quotient (AQ): evidence from Asperger syndrome/high-
functioning autism, males and females, scientists and mathematicians. J
Autism Dev Disord. 2001;31(1):5–17.
39. Ruzich E, Allison C, Smith P, Watson P, Auyeung B, Ring H, Baron-Cohen S.
Measuring autistic traits in the general population: a systematic review of
the Autism-Spectrum Quotient (AQ) in a nonclinical population sample of
6,900 typical adult males and females. Mol Autism. 2015;6(1):2.
40. Woodbury-Smith MR, Robinson J, Wheelwright S, Baron-Cohen S. Screening
adults for Asperger syndrome using the AQ: a preliminary study of its
diagnostic validity in clinical practice. J Autism Dev Disord. 2005;35(3):331–5.
41. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed.
Hillsdale: Erlbaum Associates; 1988.
42. Field A. Discovering statistics using SPSS. London: Sage publications; 2009.
43. Ratto AB, Kenworthy L, Yerys BE, Bascom J, Wieckowski AT, White SW,
Wallace GL, Pugliese C, Schultz RT, Ollendick TH, Scarpa A. What about the
girls? Sex-based differences in autistic traits and adaptive skills. J Autism Dev
Disord. 2018;48(5):1698-711.
44. Gotham K, Bishop SL, Brunwasser S, Lord C. Rumination and perceived
impairment associated with depressive symptoms in a verbal adolescent–
adult ASD sample. Autism Res. 2014;7(3):381–91.
45. Heasman B, Gillespie A. Perspective-taking is two-sided: misunderstandings
between people with Asperger’s syndrome and their family members.
Autism. 2018;22(6):740–50. https://doi.org/10.1177/1362361317708287.
46. Jaswal VK, Akhtar N. Being vs. appearing socially uninterested: challenging
assumptions about social motivation in autism. Behav Brain Sci. 2018;19:1–84.
47. Sasson NJ, Faso DJ, Nugent J, Lovell S, Kennedy DP, Grossman RB.
Neurotypical peers are less willing to interact with those with autism based
on thin slice judgments. Sci Rep. 2017;7:40700.
48. Milton DE. On the ontological status of autism: the ‘double empathy
problem’. Disabil Soc. 2012;27(6):883–7.
49. Milton D, Sims T. How is a sense of well-being and belonging constructed
in the accounts of autistic adults? Disabil Soc. 2016;31(4):520–34.
50. Raja M. Suicide risk in adults with Asperger’s syndrome. Lancet Psychiatry.
2014;1(2):99–101.
51. Cassidy SA, Bradley L, Bowen E, Wigham S, Rodgers J. Measurement
properties of tools used to assess depression in adults with and without autism
spectrum conditions: a systematic review. Autism Res. 2018;11(5):738–54.
52. McConachie H, Parr JR, Glod M, Hanratty J, Livingstone N, Oono IP, Robalino S,
Baird G, Beresford B, Charman T, Garland D. Systematic review of tools to
measure outcomes for young children with autism spectrum disorder. https://
ore.exeter.ac.uk/repository/handle/10871/17760. Accessed 21 Feb 2018.
53. Wigham S, McConachie H. Systematic review of the properties of tools used
to measure outcomes in anxiety intervention studies for children with
autism spectrum disorders. PLoS One. 2014;9(1):e85268.
54. Kessler C, Berglund P, Demler O, Jin R, Merikangas R, Walters E. Lifetime
prevalence and age-of-onset distributions of DSM-IV disorders in the national
comorbidity survey replication. Arch Gen Psychiatry. 2005;62(6):593–602.
Cassidy et al. Molecular Autism (2018) 9:42 Page 14 of 14
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

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