Formal Thought Disorder and Executive Functioning in Children and Adolescents with Autism Spectrum Disorder: Old Leads and New Avenues
Formal Thought Disorder and Executive Functioning in Children and Adolescents with Autism Spectrum Disorder: Old Leads and New Avenues
Tim Ziermans 0 1 2 3 4 5
Hanna Swaab 0 1 2 3 4 5
Alexander Stockmann 0 1 2 3 4 5
Esther de Bruin 0 1 2 3 4 5
Sophie van Rijn 0 1 2 3 4 5
0 Autism Center Rivierduinen , Leiden , The Netherlands
1 Leiden Institute for Brain and Cognition, Leiden University , Leiden , The Netherlands
2 Department of Clinical Child and Adolescent Studies, Leiden University , Wassenaarseweg 52, Leiden 2333 AK , The Netherlands
3 UvA minds, Academic Outpatient Child and Adolescent Treatment Center , Amsterdam , The Netherlands
4 Research Priority Area Yield, University of Amsterdam , Amsterdam , The Netherlands
5 Research Institute Child Development and Education, University of Amsterdam , Amsterdam , The Netherlands
Formal thought disorder (FTD) is a disruption in the flow of thought and a common feature in psychotic disorders and autism spectrum disorder (ASD). Executive dysfunction has often been associated with FTD, yet for ASD convincing evidence is lacking. This study investigated FTD and three core executive functions in 50 young children and adolescents with high-functioning ASD and 56 matched controls. Higher overall levels of FTD marked ASD compared to controls. Furthermore, in ASD decreased performance on verbal working memory was correlated with increased FTD ratings and explained a significant amount of variance of objective and subjective FTD. Verbal working memory is currently the most promising target executive function for understanding the development of idiosyncratic thought disorders in ASD.
ASD; High-functioning; Thought disorder; Executive functioning; Working memory; Psychosis
Autism spectrum disorders (ASD) and psychotic disorders,
such as schizophrenia, both represent severely disabling
neurodevelopmental disorders (Goldstein et al. 2002), with
marked impairments in cognition and social functioning
(Couture et al. 2010; Sasson et al. 2011). For ASD, the first
behavioral problems typically occur during early
childhood, while psychotic disorders are primarily diagnosed in
late adolescence and young adulthood. Despite some
symptomatic overlap, both psychiatric classifications are largely
characterized by differential behavioral phenotypes and
appear mutually exclusive in diagnostic manuals such as
the Diagnostic Statistical Manual of Mental Disorders (5th
edition; DSM5; American Psychiatric Association 2013)
and the International Classification of Diseases (10th
edition; ICD-10; World Health Organization 1993).
Interestingly though, there is substantial evidence indicating that
children diagnosed with ASD have an increased prevalence
of psychotic disorders later in life and that psychotic
disorders are associated with increased rates of ASD (Chisholm
et al. 2015; Selten et al. 2015).
In recent years there has been a renewed interest in
specific overlapping autistic and psychotic symptoms, in
clinical and non-clinical samples, partially guiding the
ongoing quest for differential markers and potential risk factors
for psychosis in patients with ASD (Abu-Akel et al. 2016,
2015; Barneveld et al. 2011; Brosnan et al. 2014; Chung
et al. 2014; Crespi et al. 2016; Eack et al. 2013; Sasson
et al. 2016). One overlapping symptom that has received
relatively little attention is formal thought disorder (FTD).
FTD refers to a disruption in the flow of thought, as
observed by disorganized speech. Although speech is an
indirect measure of thought, “language serves essentially
for the expression of thought”, as phrased by the famous
linguist Noam Chomsky (Chomsky et al. 1979), whose
extensive work in this field implies that an understanding
of the rules of a language throws light on the principles that
regulate human thought.
FTD represents a hallmark feature of schizophrenia
and is also characteristic of childhood onset
schizophrenia, schizotypal personality disorder (Caplan 1994a), and
predictive of psychosis in adolescents at clinical high-risk
(Bearden et al. 2011). Likewise, speech disturbances, such
as pragmatic language impairments, are a common feature
in ASD. Obviously, it requires a minimal amount of speech
in order to tap into the organization of thought in terms of
logic and coherence. Indeed, when assessing FTD in verbal,
high-functioning individuals with ASD there is some
evidence of increased levels of FTD. Earlier studies in small
adult samples of high-functioning individuals reported that,
compared to adults with schizophrenia, those with ASD
demonstrated more ‘negative’ thought disorder, i.e. poverty
of (content of) speech, but not so much ‘positive’ features,
i.e. illogicality and derailment (Dykens et al. 1991; Rumsey
et al. 1986). More recently, elevated rates of FTD have also
been reported in children with high-functioning ASD
(Solomon et al. 2008; van der Gaag et al. 2005). These studies
did report elevated rates of ‘positive’ FTDs (i.e. ‘illogical
thinking’ and ‘loose associations’) in ASD compared to
typically developing children. This is relevant, because this
may point to disorganization of thought in a way that may
predispose to symptoms that are typically observed in
individuals with psychotic disorders.
There currently is no evidence suggesting that FTD is
indicative or predictive of a subsequent psychotic episode
in children with high-functioning ASD (Eussen et al. 2015;
van der Gaag et al. 2005), although this has never been
investigated in a direct manner. However, one long-term
clinical follow-up study of a group of 55 ASD children
meeting criteria for multiple complex developmental
disorder (MCDD), a descriptive ASD subtype marked
specifically by deregulation of thought and emotions (Buitelaar
and van der Gaag 1998; Sprong et al. 2008; van der Gaag
et al. 1995), reported that approximately 70% of
participants met criteria for schizophrenia spectrum disorder in
adolescence or adulthood (van Engeland and van der Gaag
1994). As such, it remains uncertain to what extent early
observation of FTD may contribute to the development of
psychotic disorders in later life.
In addition to a clear link with impaired semantic
processing skills, there is a seemingly strong
association between impaired executive functioning and FTD in
patients with schizophrenia (Docherty 2012; Kerns and
Berenbaum 2002). The term ‘executive functions’ refers to
a set of cognitive processes associated with the control of
thoughts and actions (Bunge and Souza 2009). Executive
functions include, but are not limited to, cognitive
abilities such as response inhibition, working
memory/updating, and set shifting (Friedman and Miyake 2016; Miyake
et al. 2000). It is well established that executive functions
are impaired along the full width of the psychosis spectrum
(e.g. Bora and Murray 2014; Giakoumaki 2012; Ziermans
2013), although results have been mixed concerning their
added use for predicting psychotic onset on an individual
level (Fusar-Poli et al. 2012; Lin et al. 2013; Metzler et al.
2016; Ziermans et al. 2014). Executive dysfunction has
also been historically linked to ASD (Pennington and
Ozonoff 1996) and impairments have been widely reported (for
a review see Russo et al. 2007), albeit within the context of
large individual and age-dependent differences (Pellicano
2010; van den Bergh et al. 2014). Such individual
differences in ASD may also partially account for the observed
symptomatic overlap with psychotic disorders, but only a
limited amount of studies have addressed this issue.
Only one pilot-study has previously investigated FTD in
relation to executive functioning in ASD (Solomon et al.
2008). Solomon and colleagues compared 17 adolescents
with high-functioning ASD to 21 matched controls on
objective rating scales for FTD and examined correlations
with one executive control task (Preparing to Overcome
Prepotency; POP-task; Barber and Carter 2005), which
measures inhibition of a prepotent response. They found
that only one type of FTD (illogical thinking) was
specifically correlated to response inhibition with borderline
significance. However, sample sizes were small and this study
focused specifically on inhibition, which limits the ability
to firmly establish which aspect of EF is most relevant for
The first goal of the current study was to compare the
prevalence of FTD, as measured by both objective ratings
and subjective self-reports, between a substantial group of
high-functioning children and adolescents with ASD and
their typically developing controls (TDC), matched for age,
gender and (verbal) IQ. Based on two previous reports in
smaller samples, we expected that children and adolescents
with ASD would show higher levels of FTD, in
particular for ratings of illogical thinking and loose associations
(Solomon et al. 2008; van der Gaag et al. 2005). Second,
we aimed to determine whether level of FTD was impacted
by cognitive performance on three core executive functions
(response inhibition, working memory and cognitive
flexibility) in high-functioning ASD. Establishing the relative
contribution of executive functions to FTD, in the context
of relatively preserved verbal skills, can potentially lead to
improved early identification of cognitive risk factors for
the development of psychotic symptoms in ASD, as well
as provide new incentive for fine-tuning research into the
underlying neurodevelopment of both types of disorders.
We expected to find multiple associations between
executive functions and FTD parameters and, more specifically,
that response inhibition measures would explain a
significant amount of variance in FTD (Barneveld et al. 2013;
Solomon et al. 2008).
The ASD group was recruited from a child psychiatric
outpatient department with specialized services for children
with autism (Autism Center Rivierduinen), serving a large
region in the Netherlands. All children with ASD were
classified according to the Diagnostic and Statistical Manual
of Mental Disorders, Fourth Edition (DSM-IV; American
Psychiatric Association, 1994) criteria and were considered
to be high-functioning (IQ ≥ 70). The clinical procedures
for diagnosis of ASD included questionnaires for parents,
an interview with parents (Autism Diagnostic
InterviewRevised; Le Couteur et al. 2003; ADI-R), developmental
history and family history, information from treating
physicians and extensive expert clinical observations. Consensus
regarding the diagnostic classification of ASD had to be
reached by board-certified child psychiatrists (with
experience in the field of autism) and by a consensus meeting
with a multidisciplinary team.
Typically developing controls (TDC) were recruited
from schools distributed across the western part of the
Netherlands and screened for psychopathology: none
scored in the clinical range (T ≥ 70) on the diagnostic
subscales of the Childhood Behavior Checklist (CBCL;
Achenbach 1991). Inclusion criteria for all participants
were: Dutch as the primary language and aged between
9 and 19 years. Exclusion criteria were a recent history
of substance abuse, intellectual disability (diagnosed or
IQ < 70) and neurological conditions. After providing all
necessary information about the study to the subjects and
their parents, written informed consent was obtained, in
accordance with the Declaration of Helsinki. The Ethical
Committee of Leiden University Medical Center, the
Netherlands, approved this study.
The subtests Block Design and Vocabulary of the Dutch
adaptations of the third edition of the Wechsler
Intelligence Scales for Children (WISC-III-NL; Kort et al. 2002)
were used to assess IQ, i.e. the Vocabulary-Block Design
(V-BD) short form. This form is frequently used to estimate
full-scale IQ (FSIQ) according to the algorithm (2.9 × [sum
of normed scores] + 42) (Campbell 1998). The V-BD short
form correlates highly with FSIQ (r = .88) (Herrera-Graf
et al. 1996), and has been found valid for the estimation of
intelligence, with a good reliability (r = .91) and validity
(0.82) (Campbell 1998).
The Autism spectrum Quotient - Children’s version
(AQChild; Auyeung et al. 2008) is a parent questionnaire of
50-items that can reliably assess the degree to which an
individual might have features of the core autistic
phenotype. The AQ-Child is an adaptation of the self-report
version (Baron-Cohen et al. 2001). For the Dutch versions
only the self-report version has been validated (Hoekstra
et al. 2008), and the parent report is a similar adaptation
for children as for the English versions. Five subscales
cover personality traits associated with the autism
spectrum; social skills, communication, imagination, attention
to detail, and attention switching. Binary scoring was used
for all items with a maximum score range of 0–50. Higher
scores on the AQ indicate higher levels of autism traits.
Thought Disorder Measures
The Kiddie‑Formal Thought Disorder Rating Scale
The golden standard assessment for FTD in children is the
Kiddie-Formal Thought Disorder Story Game procedure
with its accompanying rating Scale (K-FTDS), a frequently
used and reliable, objective measure of FTD in children ≥7
years (Caplan 1994b; Caplan et al. 2000). In the first and
third part, the child listened to an audiotaped story: (1) the
first story is about a boy dreaming about a friendly ghost
and the third story is about a boy who is excluded from his
group of friends and badly teased. Children were asked
standard questions, for instance: “What did you like about
this story?” In the second part of the story game, the child
was asked to make up his or her own story chosen from
four topics: (a) the horrible hulk (b) a witch, (c) a
disobedient child or (d) an unhappy child. Assessments lasted for
about 20–30 min and speech samples were recorded using
a digital audio recorder.
Four different subtypes of FTD were coded
according to the guidelines by Caplan (1994b): Illogical
Thinking (ILL); Loose Associations (LA); Poverty of Content
(POC) and Incoherence (INC). Utterance counts for the
total speech sample were also calculated. There were two
independent raters who were never the same person as
the interviewer. Both received training from author EdB,
who was formally trained in K-FTDS assessment and
rating procedures by Caplan. The raters were blind to group
membership and diagnosis. Inter-rater reliability was
maintained through regular consensus meetings in which
the independent coding of all participants by both raters
was discussed. The raw error scores were divided by
the number of utterances to correct for variance in total
amount of speech produced and to calculate the number
of errors per minute. In addition, a total sum score was
also calculated (Total FTD), and available cut-off scores
(Caplan et al. 1989) for optimal sensitivity and specificity
were used to create dichotomized scores for ILL, LA and
Total FTD. Scores above the cut-off point reflect a higher
likelihood of pathology. Caplan and colleagues were
unable to calculate reliable cut-off scores for POC and INC
due to infrequent ratings for these subscales.
Schizotypal Personality Questionnaire—Odd Speech
Although K-FTDS outcomes are considered an
objective measure of FTD, its training and rating procedures
are also very time consuming and difficult to obtain
during clinical assessment (de Bruin et al. 2007).
Therefore it is worth investigating alternative, more subjective
measures of FTD, which can be more readily assessed.
The Schizotypal Personality Questionnaire (SPQ; Raine
1991) is a self-report questionnaire assessing schizotypal
traits. For this study we used the Odd Speech subscale
of a previously validated Dutch translation, adjusted for
children (SPQ-C-D; van Rijn et al. 2015). Odd Speech is
thought to reflect disorganized thought of the individual
and together with the Eccentric/Odd Behavior subscale
constitutes the Disorganization dimension of the SPQ.
The subscale consists of nine items, which ask about
subjective and external qualifications about the individual’s
speech. For example, ‘People sometimes find it hard to
understand what I am saying’, or ‘I sometimes use words
in unusual ways’. All items are answered with ‘correct’
(i.e. applies to me) or ‘incorrect’ (i.e. does not apply to
me) and receive a binary score, based on which a sum
score is calculated (range 0–9).
No formal clinical cut-off score is available for the
Odd Speech subscale; therefore we used data from our
validation sample of 219 typically developing children
and adolescents (van Rijn et al. 2015) to establish a proxy
for a clinical cut-off score. A T-score of 67 is a
commonly used borderline score on clinical questionnaires,
which is equivalent to a score within the 95th percentile.
The 95th percentile for the Odd Speech subscale referred
to a score of 8, which was used as a clinical cut-off to
create a dichotomous variable for the purpose of this study.
Executive Functioning Measures
Three computerized tasks from the Amsterdam
Neuropsychological Tasks (ANT, version 2.0; de Sonneville 2005)
and one subtest (number repetition) of the Dutch version of
the Clinical Evaluation of Language Fundamentals
(CELFIV; Kort et al. 2008) were included in this study. The ANT
has been used extensively to examine executive functions
and related cognitive processes in various clinical and
nonclinical populations and has high sensitivity for
neuropsychological dysfunction as well as good reliability and
validity (de Sonneville 2014). All computer tasks were preceded
by instructions of the test leader and practice trials.
Number repetition was administered following CELF manual
Visuospatial working memory was measured with the
ANT Spatial Temporal Span (STS). In this task a gray
square containing nine smaller squares positioned on a
3 × 3 matrix is visible on the screen. After presentation of
an auditory cue a hand animation is run and successively
points at a number of these nine squares (1000 ms stimulus
presentation, 750 ms to move hand to the next stimulus).
Children are instructed to remember the locations
(ranging from 2 to a maximum of 9) and after the stimulus is
presented indicate the locations by clicking on them in the
order they appeared on the screen (i.e., the correct temporal
order). The task consists of two parts of a maximum of 24
trials: forward span and backward span. In both parts the
task automatically ends after two consecutive errors of the
same type. The number of correctly completed trials in the
correct order for the backwards condition was used as the
variable of interest in this study.
Verbal working memory was assessed with the digit
span subtest ‘number repetition’ of the CELF (CELF-NR),
which also contains a forward and backward condition. In
this subtest children are asked to repeat orally presented
strings of numbers (which increase in size) in either the
correct (forward) or reverse order (backward). Total
number of correct items backwards was used for the analyses.
The ANT Go-NoGo (GNG) task was used to measure
the capacity to inhibit a prepotent response. Stimuli
consisted of ‘Go’-stimuli (gray square with yellow frame) and
‘NoGo’-Stimuli (same as Go, with a small spatial gap at the
bottom of the frame). Children were instructed to click a
mouse button as quickly and accurately as possible when
a Go-stimulus was presented. If the NoGo-stimulus was
presented, the subjects were instructed to withhold clicking
the button. The stimulus was presented for 300 ms. The
valid response window was 200–1500 ms post onset of the
stimulus. Stimuli were pseudo-randomly presented (biased
condition: 56 Go-stimuli and 18 NoGo-stimuli) to
measure inhibition of an ongoing response. Variables of
interest were speed (reaction time Go-signals) and accuracy (d’:
Z(hit rate) − Z(false alarm rate)).
The ANT Shifting Set Visual (SSV) task was used to
measure cognitive flexibility of participants. During this task a
green or red colored square jumps randomly to the right
or left on a horizontal bar of ten gray squares. Depending
on the color of the square, the participant has to execute
a compatible (pressing the key in the same direction) or
an incompatible response (opposite direction). The task is
self-paced with a response window of 150–5000 ms. The
test consists of three parts: the first part requires compatible
responses to 40 left/right jumps of the green square, the
second part requires 40 incompatible responses to a
jumping red square and for the third part the color of the square
varies between red and green (random condition). The third
part consists of 80 trials (40 compatible, 40 incompatible)
and flexibility can be measured by contrasting part one
and the compatible condition of part three on speed and
Data were analyzed with IBM SPSS version 22.
Baseline characteristics of the control and training group were
compared with Chi square and independent t tests or
nonparametric Mann–Whitney U tests for test variables with
non-normal distributions. Cohen’s d was calculated based
on pooled group variances (M1 − M /spooled, where spooled =
√[(s12 + s22)/2]) to determine the effect size of group mean
differences. Two-tailed Spearman’s rank correlations were
performed to check for any significant associations between
dependent and independent variables in the ASD group.
Next, regression analyses were used to investigate whether
performance on executive tasks could predict the level of
thought disorder in ASD. First by using linear regression
with continuous dependent variables and second by means
of logistic regression and binary dependent variables (based
on cut-off scores). To check for the potential influence of
age, sex and medication use (binary), all regression
analyses were repeated with these background variables entered
as covariates. Finally, to explore whether autistic traits were
moderating any relations between EF and FTD,
regression analyses were repeated with mean-centered total AQ
scores and its interaction-term with relevant EF-variables
The total participant group consisted of 50 children and
adolescents with ASD (41 boys, 9 girls) and 56 TDC (47
boys, 9 girls). To prevent unequal gender distributions,
female control participants were selected from a large pool
of control girls and individually matched to ASD girls
based on age and FSIQ scores. For five ASD individuals
we were unable to conduct the ADI-R parent-interview.
Of the remaining 45 individuals, 34 (75.6%) scored above
cut-off on all three ADI-R domains and an additional 9
(20%) scored above cut-off on two domains. ADI data
was used in the diagnostic evaluation; all ASD individuals
received a formal diagnosis of ASD after a thorough
clinical evaluation procedure, described in the “Methods”
section above. Further group characteristics are displayed in
Table 1. Groups did not differ on age and IQ scores, and
TDC showed significantly fewer ASD symptoms on all
AQ scales. Finally, five ASD individuals (3 boys, 2 girls)
received psychotropic medication.
Formal Thought Disorder
K-FTDS data was missing for three individuals with ASD
and SPQ-C-D data for two individuals with ASD. All data
distributions were skewed and there were no extreme
outliers. Consequently, analyses were performed with
non-parametric Mann–Whitney U tests and group comparisons for
K-FTDS and Odd Speech are listed in Table 2.
Participants with ASD showed significantly higher rates
of FTD as measured by Total FTD and INC, but not for
any of the other subdomains. Effect sizes were small for all
variables (drange = 0.09–0.31). Percentages of cases
scoring above clinical cut-off indicated that in absolute terms
more individuals with ASD than TDC scored in the clinical
range on K-FTDS total score (25.5 vs. 14.3%), ILL (46.8
vs. 28.6%) and LA (4.3 vs. 0.0%).
Individuals with ASD reported significantly more FTD than
TDC and the effect size was medium (d = 0.71) according
to Cohen’s definition of effect sizes. Percentages of cases
scoring above the cut-off indicated that more children and
Table 2 Group comparisons for thought disorder measures
U = 1902.0
Table 1 Group characteristics
aAQ data was missing for 1 control and 7 ASD individuals
adolescents with ASD than TDC reported elevated levels of
subjective FTD (16.3 vs. 7.1%).
Working memory data (STS and CELF-NR) was missing
for one individual with ASD. For the response inhibition
task (GNG) data was missing for three TDC and one
participant with ASD. In addition, two outliers (controls) with
a false alarm rate >90% were removed for analysis. Data
on cognitive flexibility was missing for one TDC and one
individual with ASD. Except for speed parameters (GNG
and SSV) data were not normally distributed.
Correlations with Age, IQ and Autism Symptoms
Correlations are displayed in Table 3 for the ASD group
only. Both working memory measures and both inhibition
measures were significantly correlated with each other
(CELF-NR–STS: r = .36, p = .011; GNG speed/accuracy:
r = −.35, p = .015). STS was also significantly correlated
to GNG (speed: r = −.38, p = .008; accuracy: r = .43;
p = .002). Concerning background variables, all EF
measures showed increased performance with age, although
this did not reach statistical significance for CELF-NR
and SSV (accuracy). Furthermore, CELF-NR, STS and
SSV (accuracy) were positively correlated with FSIQ
(all p < .05, STS p < .01). These correlations were mainly
driven by performance on the performal subtask and not
correlated with verbal skills. There were also no
significant correlations between executive functioning and AQ.
Correlations for the total group including controls are
available in the Supplemental Table.
Regressing Executive Functions on Formal Thought
Disorder in ASD
To minimize the number of predictor variables, only
executive functioning measures correlating with FTD measures
were entered in linear regression models, and for logistic
regression models only the four highest correlating
variables were entered as predictors (n.b. logistic regression
does not assume a linear relationship between dependent
and independent), allowing for a ratio of at least ten cases
per predictor (See Table 3 for correlations). In addition, a
forward stepwise method (Likelihood Ratio) was used for
logistic regression. Although all assumptions for both types
of regression analyses were met, it is worth noting that
residuals indicated limited homoscedasticity in general. No
influential cases were detected.
Linear Regression Models
There was one significantly correlated variable-pair:
CELFNR and SPQ-Odd Speech; K-FTDS measures did not have
linear relationships with executive functions (Table 3). In
the regression analysis CELF-NR significantly predicted
Odd Speech (R2 = 0.11; β = −0.37, t = −2.71, p = .009)
and remained significant after adjusting for age, sex and
medication (R2 = 0.11; β = − 0.33, t = −2.29, p = .027) and
there was no significant moderating effect of autism traits
(CELF-NR × Total AQ: p = .30). The negative beta
indicated that a worse performance on verbal working memory
was associated with increased levels of (subjective) FTD in
children and adolescents with ASD.
Logistic Regression Models
Models were run for two dependent variables; binary
variables for Total FTD and Odd Speech. Both variables
Table 4 Univariate models of
executive functions predicting
clinical level of formal thought
correlated highest with the four variables for working
memory and response inhibition. Regression results showed that
for both the subjective and objective FTD measures
CELFNR was the only significant predictor in the final model,
with odds ratios indicating that better WM performance
decreases the odds of scoring above clinical threshold.
When age, sex and medication were forced into the model
with significant predictors, both the model and CELF-NR
backwards remained unchanged in terms of significance.
However, none of these background variables contributed
significantly to the model, which rendered their inclusion
unnecessary. Furthermore, no significant interactions of
CELF-NR with total AQ were detected (p = .20 and p = .24,
respectively). Parameters for both univariate models are
displayed in Table 4.
The findings in the current study suggest that children
and adolescents with high-functioning ASD experience
elevated levels of FTD, both objectively and subjectively,
even in the context of intact (verbal) intellectual
functioning. This corroborates previous accounts of increased rates
of FTD in children and adolescents with high-functioning
ASD (Solomon et al. 2008; van der Gaag et al. 2005). Few
studies have investigated putative cognitive mechanisms
driving these observed difficulties in the organization of
thought and speech in ASD. Executive functions
represent a set of interrelated cognitive skills that allow people
to exercise a certain amount of control over their thoughts.
These cognitive functions are often impaired in ASD and
sometimes linked to FTD in schizophrenia spectrum
disorders (Barrera et al. 2005; Docherty 2012). As such, we
hypothesized that impaired executive functioning, in
particular inhibitory control, would predict levels of FTD in
ASD as well. Our study showed that, when evaluating
multiple executive functions, verbal working memory was the
single one associated with FTD.
aLogistic regression with forward stepwise elimination—final models (p< .05)
Increased presence of FTD may or may not predispose
adolescents for psychotic disorders. Evidence from a
clinical high-risk population (CHR), presumably without ASD
diagnosis, suggests that higher ratings for illogical thinking
and poverty of content can help predict the onset of
psychosis and level of social functioning approximately one
year after intake (Bearden et al. 2011). The only known
follow-up study that investigated predictive validity of FTD
in high-functioning ASD reported that illogical thinking
in young children did not predict prodromal symptoms in
adolescence 7 years later, and instead was more indicative
of ASD symptom severity (Eussen et al. 2015). However,
the outcome measure consisted of a screening
questionnaire for prodromal symptoms, assessed in children aged
12–20 years, so before the peak age of a first psychotic
episode, and only 2 of 32 participants scoring above the
screening threshold met formal criteria for CHR. Despite
a few studies reporting on elevated levels of CHR
symptoms in ASD and vice versa (Eussen et al. 2015; Solomon
et al. 2011; Sprong et al. 2008), study samples are typically
not screened concurrently for both conditions, and
therefore very little is known about the predictive validity of
prodromal symptoms in ASD. One 6-year follow-up study
(de Wit et al. 2014) showed that out of 17 adolescents with
ASD diagnosis and clinical high-risk, one individual (6%)
had become psychotic, 5 (29%) were still considered
atrisk, and 11 (65%) had remitted. Clearly additional
followup studies in larger ASD/high-risk cohorts are required to
address whether FTD constitutes a true risk factor for
psychotic disorders in ASD.
Despite a global increase in overall FTD in our study,
specific K-FTDS subtypes such as ‘Loose Associations’
and ‘Illogical Thinking’ did not differentiate between
individuals with ASD and controls, which is inconsistent with
the large effect sizes reported for these measures in
previous studies (Solomon et al. 2008; van der Gaag et al.
2005). The only subtype that differed between groups was
‘Incoherence’, which denotes utterances that are difficult to
understand due to insufficient organization. However, all
effect sizes were small. A closer look at K-FTDS ratings
across studies suggests that the average ratings in our study
were quite low compared to the study by van der Gaag
et al., possibly due to inclusion of a more mildly affected,
slightly older ASD group and a lower utterance count. In
terms of age, our study sample was similar to the Solomon
et al. sample and FTD ratings for ASD were also highly
comparable. However, FTD ratings for the control group in
the Solomon study were virtually absent, whereas our
control group did show some variation across FTD subtypes,
and may therefore have been representative of a broader
population. In addition, our sample sizes for both groups
were roughly two-to-three times larger than in the two
previously conducted studies, although the van der Gaag study
also included an additional clinical comparison group
diagnosed with MCDD. Interestingly, the MCDD group did not
differ from the other ASD group on K-FTDS ratings.
To complement the objective measurement of FTDs, a
subjective measure of FTD was also included in this study:
the Odd Speech subscale of the Schizotypal Personality
Questionnaire. For this measure we did find a significant
group difference in the expected direction. Although the
use of self-report questionnaires in individuals with ASD
is sometimes scrutinized, the Odd Speech items are rather
concrete and ask for both personal and observer
qualifications of the subject’s speech difficulties. The fact that they
are worded so that subjects also report on external
corroboration of these symptoms probably indicates why the
subscale can be measured quite reliably (Raine 1991), and why
it has previously been used as a measure of FTD in patients
with schizophrenia (Badcock et al. 2011). Training and
rating procedures of K-FTDS are very time consuming and
difficult to complete during clinical assessment (de Bruin
et al. 2007), and therefore it is worth investigating
alternative FTD measures that require less time and effort and
may be more suitable for application in clinical or research
settings where limited resources are available. Even though
continuous measures for Odd Speech and K-FTDS were
not significantly correlated, the binary variables (based
on clinical cut-offs) were (Odd Speech − FTD Total: ϕ
= 0.38, p ≡ .01). Although this suggests that both
measures are only moderately tapping into the same construct,
it is not uncommon for informant- and performance-based
tasks measuring similar constructs to show limited
correlations (Toplak et al. 2013). Clearly, different types of
raterbias and test impurity can dampen the strength of these
monotrait-heteromethod correlations, possibly because one
or several mediating variables are unaccounted for.
However, both methods may also provide complementary
information on the same underlying latent construct. Therefore,
our first recommendation is to further investigate the
reliability and validity of the Odd Speech subscale as a proxy
for FTD in a multitrait-multimethod matrix and second, to
establish whether it can explain additional variance in
prediction models of psychosis, for example in CHR samples.
Despite robust findings of executive dysfunction in
ASD, the literature on this topic is vast and riddled with
conflicting findings. For example, it has been claimed that
response inhibition is the only core executive function not
impaired in ASD (Russo et al. 2007). However, a recent
meta-analysis on prepotent response inhibition and
interference control in ASD concluded that the evidence suggests
otherwise (Geurts et al. 2014). Substantial
inconsistencies have also been highlighted for working memory and
cognitive flexibility performance in ASD (de Vries and
Geurts 2014; de Vries et al. 2015), although rigorous
metaanalyses for these constructs are currently lacking in the
literature. Additionally, executive dysfunctions tend to have
limited discriminative value across psychiatric
classifications. Enriching between-group analyses with within-group
associations may therefore be better suited to help identify
specific associations between cognitive markers and
heterogeneous behavioral phenotypes.
By applying this strategy, we were able to detect an
association between executive functioning and FTD within the
ASD group. Lower verbal working memory performance
significantly predicted higher levels of FTD in both linear
and logistic models and for both subjective and objective
FTD in the latter. This suggests that individuals with ASD
who experience verbal working memory difficulties may
be particularly vulnerable for developing subsequent FTD
symptoms. The task used (CELF-NR) is a digit span task,
which (along with other distractibility tasks) has previously
been associated with FTD in children with ADHD, but not
in children with schizophrenia (Caplan et al. 2001). Given
the high comorbidity of ADHD and ASD symptoms in
general, it is possible that the association was mostly
reflecting increased distractibility in some of our individuals with
ASD. This would subsequently limit the capacity to encode
and retrieve verbal information in/from working memory
and thereby reduce reproduction of the presented stories in
the story game, for example. However, the absence of
similar associations for visuospatial working memory, as well
as for the other non-verbal executive functioning
parameters, and the relative preserved verbal skills which were
not correlated to FTD in our ASD sample, all strengthen
the notion that executive control over verbal processing is
key to understanding FTD in ASD. Furthermore, Docherty
(Docherty 2012) also found that verbal working memory
(digit span task) predicted FTD in adults with
schizophrenia. Although this does not directly implicate an increased
risk for schizophrenia in ASD individuals with FTD, it
could entail that the combination of clinical levels of FTD
and verbal working memory problems poses a potential
risk factor for psychotic episodes in ASD.
Two known studies have also directly addressed
relations between executive functioning and FTD in ASD.
Both indicated that prepotent response inhibition in ASD
was significantly associated with FTD, respectively for
K-FTDS—Illogical thinking (Solomon et al. 2008) and
SPQ – Disorganization (= Odd Speech + Eccentric
Behavior) (Barneveld et al. 2013). However, these studies
consisted of smaller samples and correlational analyses were
conducted with similar but slightly different parameters for
only one executive functioning measure. Given the
hypothesized dependent nature of FTD, regression analyses can
provide better clues as to the relative impact of executive
functions on FTD.
Two main limitations of our study need to be
highlighted. Although we were able to increase sample size
and include additional cognitive parameters and analyses
compared to previous FTD studies in ASD samples, our
study was still too limited to include additional predictors
from other relevant neurocognitive domains, such as
attention and language, which we recommend for future studies.
An additional limitation is the use of cross-sectional data,
which prohibits any inferences about the causal nature of
any associations under investigation.
To conclude, the current study aimed to investigate
relations between executive functions and FTD in children
and adolescents with ASD and matched typically
developing controls. In sum, we found evidence for an increased
prevalence of FTD and a significant negative association
between verbal working memory skills and FTD, which
may overrule the potential impact of response inhibition
or cognitive flexibility on disorganized speech. We
therefore suggest that poor verbal working memory skills may
predispose some children and adolescents with autism
to develop thought disorder and advise researchers in the
field to shift their focus from solely on executive control
to include the role of executive verbal processing skills in
relation to FTD in this target population.
Acknowledgments This work was supported by a Veni grant (Grant
Number 016.095.060 to SVR) from the Netherlands Organization
for Scientific Research (http://www.nwo.nl). The funders had no role
in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Author contributions TZ conceived of the study and its design,
performed the statistical analyses, interpreted the data and drafted
the manuscript; HS participated in study design and coordination. AS
participated in coordination of patient recruitment; EdB helped with
K-FTDS data acquisition and interpretation; SvR conceived of the
study, and participated in its design and coordination and helped to
interpret the statistical analyses and draft the manuscript. All authors
critically read and approved the final manuscript.
Open Access This article is distributed under the terms of the
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appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
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