Investigating The Effects of Executive Functions and Social Cognition on the Relationship Between Autistic Traits and Mental Health
Phase: NA
Conditions: Autism or Autistic Traits, Mental Health Disorder, Executive Dysfunction, Social Cognition
Sponsor: Ibn Haldun University

 
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INVESTIGATING THE EFFECTS OF EXECUTIVE 
FUNCTIONS AND SOCIAL COGNITION ON THE 
RELATIONSHIP BETWEEN AUTISTIC TRAITS AND MENTAL 
HEALTH 
 
 
 
DİLRUBA SÖNMEZ 
 
7 MARCH 2025 
 
 
 NCT06213194 
 
 
 
 
 
 
 
 
 
 

 
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Introduction  
Nowadays, digital interventions have become more popular day by day to use in different areas 
including mental health problems, executive functions including working memory (WM), 
cognitive flexibility and inhibitory control, and social cognitive skills in both clinical and non- 
clinical populations (Sandgreen et al., 2021). In terms of non-clinical populations, the studies 
have indicated that executive function training could be effective for both the enhancement of 
cognitive functions as well as mental health conditions (Beloe & Derakshan, 2020; Sari, et al., 
2020). For example, Beloe and Derakshan (2020) have reported that adaptive WM training 
decreases anxiety and depression symptoms in adolescents and the effects of training lasted for a 
month. Another study by Roughan and Hadwin (2011) showed that WM training reduces school-
related difficulties and associated mental health problems in adolescents. Another study 
conducted smartphone compassion training for Swedish university students, which resulted in 
improved self-compassion and emotional awareness compared to the wait-list group (Andersson 
et al., 2021). Bendtsen and colleagues (2020) developed a mobile health intervention program to 
promote the mental health of university students. In their randomized control trial (RCT) study, 
participants showed improvement in positive mental health and reduced depression and anxiety 
symptoms compared to a control group. Olfers and Band (2018) applied game-based training to 
improve flexibility and attention and measured in Electroencephalographic (EGG) activity. Their 
results showed that flexibility and attention show increased performance in healthy young adults 
compared to the control group. In addition, response selection was improved due to flexibility 
training. This was indicated by a larger N2 amplitude compared to the control group. 
Additionally, conflict monitoring was more efficient, as shown by reduced Nc/CRN and larger 
Pe amplitude (Olfers & Band, 2018). Although studies in Türkiye included both social cognitive 
training and mental health, which are rare, Sari and colleagues (2020) observed reduced trait 
anxiety and test anxiety in university students after WM training.  
Ben-Zion et al. (2018) have found that cognitive flexibility is a significant predictor of post- 
traumatic stress disorder (PTSD) and have suggested neurocognitive skills intervention could be 
an important prevention. Roepke and colleagues (2015) conducted an RCT to examine the 
effects of smartphone training for depression and depression scores of participants declined after 
the  

 
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training compared to the control group. Similarly, the digital intervention of cognitive behavioral 
therapy (iCBT) was also shown to be effective in anxiety and depression compared to the control 
group after 8 weeks of training (Richards et al., 2020). Similarly, smartphone-based CBT was 
also found to be effective for depression compared to the control group (Lukas et al., 2021). 
Previous research shows the effectiveness of computer-based social cognitive training in 
schizophrenia by focusing on emotion recognition, social perception, social discrimination, and 
theory of mind (Sacks et al., 2013). In other studies, computer-based social cognitive training 
shows the efficacy of social cognition and social functioning in schizophrenia (Nahum et al., 
2021) and the same training program was also effective for ASD and healthy older adults 
(Nahum et al., 2013). In another study, a randomized control trial (RCT) conducted with ASD 
participants found an overall improvement in WM, cognitive flexibility, social behavior, ADHD 
behavior, and quality of life, and the authors suggested a need for further research into the 
usefulness of cognitive interventions (de Vries et al., 2015). A recent study has shown that game-
based cognitive training in school- aged children with ASD provides an improvement in 
attention, WM, emotion regulation, flexibility, social skills, and communication (Macoun et al., 
2021). Moreover, computer-based social cognitive training in adolescents and adults with ASD 
increases amygdala and fusiform area activation which are associated with facial affect response 
skills (Bölte et al., 2015). Virtual Reality Social Cognition Training for Autism by Didehbani 
and colleagues (2016) designed for 5 weeks including emotion recognition, social understanding, 
and empathy skills shows improvements in emotion recognition, ToM skills, and executive 
functions. Another digital intervention called the MindChip for socio-emotional skills in autism 
showed improvements in cognitive empathy and affective empathy skills. A significant 
difference in self-efficacy, autistic traits, and mental health outcomes was found within the 
analysis; however, there are no significant differences in self- efficacy, autistic traits, and mental 
health outcomes between experimental and control groups (Tang et al., 2021). The recent meta-
analysis study for digital intervention in ASD by Sandgreen and colleagues (2021) summarized 
that digital interventions are mostly designed in computer- based format and targeted to social 
skills. It was found .32 effect size according to Cohen’s d, which is a positive but small effect. 
However, due to the limitation of digital intervention, more studies are needed to see whether 
these interventions are effective in both clinical and non-clinical populations (Sandgreen et al., 
2021) and specifically, there is limited research in Türkiye for digital  

 
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mental health intervention to suggest conducting different studies in the recent systematic review 
by Akgün et al. (2019).  
Accordingly, the primary aim of the current study is to test the efficacy of the online training 
program on mental health (DASS-21 and its subscales) regarding autistic traits. The secondary 
aim of the current study is to test the efficacy of the online training program on executive 
functions (working memory, inhibitory control, and cognitive flexibility), and social cognitive 
skills (cognitive empathy and affective empathy).  
The following two hypotheses were addressed in the current study:  
1. Online training on executive functions and social cognitive skills will promote 
mental health by reducing DASS-21 and its subscales scores in the current sample.  
2. Online training on executive functions and social cognitive skills will promote 
executive functions (working memory, inhibitory control, and cognitive flexibility) 
and social cognitive skills (cognitive empathy and affective empathy) in the current 
sample.  
Methods Study Design  
The present study adopted a multifactorial design including pretest and posttest conditions to test 
the efficacy of combined EFs and social cognition online training via computers, tablets, or 
smartphones for mental health symptoms (depression, anxiety, and stress) in the experimental 
and control groups. Multifactorial design also called mixed design refers to including both 
within- participant design (testing the same participants over time) and between-participant 
design (comparing different groups, Breakwell et al., 2012). The independent variable for this 
study is online training while the dependent variables are mental health scores (depression, 
anxiety, and stress symptoms), executive functions (cognitive flexibility, inhibition, and working 
memory), and social cognition (cognitive empathy and affective empathy). According to our 
previous findings  
(Chapter 4), autistic traits are included in this study as covariates, which are defined by 
characteristics that might affect the study’s outcome (Cambridge University Press, n.d.).  

 
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Participants  
A power analysis (G*Power) was conducted to determine the number of participants needed to 
achieve this goal. For repeated measures analyses, 44 participants are required in order to reach a 
medium effect size of .25 with an adequate power of .80 at a = .05 (Faul et al., 2009) to 
determine interaction effects of between and within participants’ factors. Convenience sampling 
via advertisement through social media, mail groups, and on campuses was used to collect 
participants. Initially, 178 adult participants were recruited for this study to reach adequate 
power for multivariate analysis. Participants randomly and equally were assigned to the 
experimental group (89 participants) and control group (89 participants) to see whether the 
combined training program was effective for the general population. 33 participants for the 
experimental group and 48 participants for the control group completed the posttest. However, 
after checking outliers and normality analysis, 31 participants for the experimental group (28 
female, 3 male), and 34 participants for the control group (29 female, 5 male) were included in 
the further analyses. Please see the figure 6.1. the flow of participants through each stage of the 
study. The details of the participants were presented the Table 6.1. Demographic Characteristics. 
To reduce drop-out, incentives such as drawing for money/prizes were used. Inclusion criteria 
for adult participants are being aged 18 or above, being able to use computers, smartphones, or 
tablets, being native Turkish citizens, having no record of any psychiatric disorders, and having 
no record of any physical and neurological conditions that prevent to use of technological 
devices. Participants who are under the age of 18 and have any record of psychiatric and physical 
conditions that prevent to use of technological devices were excluded from the study.  

 
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Materials  
Self-Report Questionnaires  
Figure 1. The Flow of Participants  
Demographic Information Form  
Basic information such as age, gender, education level (i.e., undergraduate, postgraduate), and 
income was obtained from the participants, and it was developed by the researcher.  
Autism Quotient (AQ) for Adults Turkish Version (Baron-Cohen et al., 2006; Baron-Cohen 
et al., 2001a; Köse et al., 2010)  

 
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To measure autistic traits, the Autism Quotient (AQ; Baron-Cohen et al., 2001) was used. AQ for 
adults is adapted to Turkish culture by Köse and colleagues (2010). The self-report questionnaire 
consists of 50 questions using a Likert-scale rating; “definitely agree”, “slightly agree”, “slightly 
disagree”, and “definitely disagree”. In the Turkish adaptation of the AQ for adults, Cronbach’s  
alpha value for this scale is .64, and test-retest reliability is r = .72. The AQ is a widely used 
assessment tool that measures five subscales: social skills, communication, attention to detail, 
attention switching, and imagination. It is available in different languages (e.g., Turkish by Köse 
et al., 2010; Dutch by Hoekstra et al., 2008; Japanese by Wakabayashi et al., 2006).  
Depression Anxiety Stress Scale 21(DASS – 21; Lovibond & Lovibond, 1995; Sarıçam, 
2018)  
DASS-21 is a self-report scale to examine depression, anxiety, and stress levels for adults by 
Lovibond and Lovibond (1995). The Turkish adaptation study for DASS-21 was conducted by 
Sarıçam (2018). This scale consists of three subscales, one for depression, one for anxiety, and 
one for stress. The total number of items is 21. For this scale, inter-scale reliability with 
Cronbach’s Alpha is .87 for depression, .85 for anxiety, and .81 for stress subscales. Test-retest 
reliability is r = .68 for depression, .66 for anxiety, and .61 for stress.  
Performance Tasks  
It was administered the following performance tasks to evaluate executive functions such as 
cognitive flexibility, WM, and inhibitory control, as well as social cognition including cognitive 
empathy and affective empathy. To ensure standardized measurement, we recorded the errors for 
each task based on previous intervention studies (Chooi & Logie, 2020; de Vries et al., 2015;  
Macoun et al., 2021; Maraver et al., 2016). Each task begins with a non-scored trial to ensure 
that participants understand the task before scoring begins. The only exceptions are for the self- 
assessment manikin for affective empathy, and the Eyes Test for which detailed information was 
provided.  
Wisconsin Card Sorting Task (WCST; Berg, 1948)  

 
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The Wisconsin Card Sorting Task (WCST) is a cognitive flexibility performance task that was 
first developed by Berg in 1948. During the task, 200 cards in two blocks are displayed on the 
screen and the sorting rule changes after every 10 cards. Participants are expected to learn from 
feedback and adapt the rules during the task by trial and error. They need to match the cards 
according to their color, number, and shape. The task measures the error rates of the participants. 
Participants receive feedback only on the accuracy of their sorting, which helps them understand 
and adjust the current sorting rule. Feedback is given after each card selection.  
N Back Task (Kirchner, 1958)  
Working memory was evaluated through the N Back Task (Kirchner, 1958) in three different 
conditions - one back, two back, and three back. In this study, the n = 2 rule was applied. A 
sequence of stimuli was displayed one by one, and participants had to decide if the presented 
stimuli were the same as the stimuli that appeared in N trials earlier. The complete stimulus 
sequence consists of 15 letters and each stimulus was displayed for 500 milliseconds. 
Participants had three seconds to react (3000 milliseconds) and a new letter appeared every three 
seconds (3000 milliseconds). The letters A, B, C, D, E, H, I, K, L, M, O, P, R, S, and T were 
used in the sequence. There were eight blocks, with each block containing 50 trials. False errors 
were measured.  
Go / No Go Task (Donders, 1969)  
Go / No Go Task was used to measure inhibition. The task requires participants to respond as 
quickly and accurately as to the presented target stimulus (“go” trials) but avoid responding to 
non-target stimulus (“no go” trials). Participants need to respond in 2000 milliseconds when the  
“go” sign is presented and avoid responding when “no-go” is presented. There are 12 blocks of 
50 trials each. Commission errors (i.e., incorrectly responding to no-go trials) were measured.  
The Eyes Test - for Adults (Baron-Cohen et al. 2001b; Girli, 2014)  
The Eyes Test is a performance task for emotion recognition which is widely regarded as an 
indicator of cognitive empathy. In this test, participants were presented with a series of 36 black- 

 
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and-white photographs of human eyes. For each photograph, participants were asked to choose 
which of 4 words best describes what the person in the photograph is feeling or thinking. The 
version used was adapted for Turkish by Girli (2014). The Cronbach alpha internal consistency 
coefficient for this test is greater than .70. Accuracy of the test was measured.  
Self-Assessment Manikin (SAM; Bradley & Lang, 1994)  
Self-Assessment Manikin was carried out to measure self-reported emotional responses to facial 
expression images for affective empathy. Karolinska Directed Emotional Faces (KDEF, Conley 
et al., 2018; Lundqvist et al., 1998) were used to express facial emotions. In total, 30 images (15 
male, 15 female) were chosen and seven emotional expressions including happiness, neutral, 
anger, fear, and disgust were depicted. The task requires participants to examine each facial 
expression and rate how they feel it on a valence scale (more negative (1) to more positive (9). 
The tasks were adapted from Wai and Tiliopoulos (2012). Valence scores for each emotion were 
obtained by summing responses for all images.  
Procedure  
Approval from the ethical committee of Ibn Haldun University was obtained for this study (No. 
E-71395021-050.06.04-34359) and the protocol ID of clinical trials was obtained 
(NCT06213194). The participants for the study were recruited using convenience sampling 
through advertisements on social media, mail groups, and campuses. Once recruited, all 
participants completed pretest questionnaires and tasks before assigning them to the groups and 
undergoing training on the MindZone training website (www.mindzone.com.tr). 31 participants  
for the experimental group (28 female, 3 male), and 34 participants for the control group (29 
female, 5 male) were included for the study. The experimental group underwent an online 6-
week training period through the website developed by the researcher (www.mindzone.com.tr), 
while the control group was placed on a waiting list. Posttests were collected at the end of the 6th 
week from both experimental and control groups. Additionally, the researcher and research 
assistant checked each participant's progress weekly, sent reminder messages, and made phone 
calls to improve training continuity if participants had not completed the requirements. Details 
about training are presented in Table 5.2. MindZone Manual (see Chapter 5). After the 

 
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completion of the research studies, the control group (on the waiting list) is scheduled to access 
the online training program in accordance with ethical guidelines.  
Data Analysis  
The data from the current study was analyzed using the SPSS 25.0 package. Initial analyses were 
performed to determine if the data showed a normal distribution. Before conducting parametric 
tests, the Shapiro-Wilk test, box plots, and skewness and kurtosis scores were used to check for 
normal distribution. The self-report questionnaires' data was found to be normally distributed 
according to the Shapiro-Wilk test (p > .05). As for the performance tasks, the skewness and 
kurtosis of the data fell within an acceptable range for applying parametric tests, as specified by 
Hair and colleagues (2010). Covariate analyses were conducted to account for the effects of 
autistic traits in the intervention model. Before including covariates in the analyses, correlation 
analyses and tests for homogeneity of regression slopes were performed according to the 
assumptions of covariance (Field, 2013). The results showed that only communication and 
attention-switching had significant correlations with dependent variables (p < .05) and met the 
assumptions for being used as covariates for mental health symptoms (Field, 2013). Regarding 
EFs and social cognitive skills, communication, attention to detail and imagination entered as 
covariates in the model (p < .05); however, only communication met the assumptions for 
homogeneity of regression slopes for EFs and social cognitive skills (Field, 2013). All 
correlation tables for these assumptions were presented in Appendix C, D, and E. Moreover, t-
test analysis was carried out to see whether the pretests of dependent variables and AQ and its 
subscales for experimental and control groups  
differ. Due to more than 8 variables; a conservative p-value was set (p = .01). The results showed 
no significant differences in all pretest scores and AQ (all ps > .01).  
In the experimental study, 2 x 2 mixed design repeated measure ANOVAs were conducted to 
examine the group (experimental and control group) and the effects of time (pretest and posttest) 
on mental health (DASS-21 and its subscales), as well as executive functions (working memory, 
inhibitory control, and cognitive flexibility), and social cognitive skills (cognitive empathy and 
affective empathy). In terms of performance tasks, to ensure standardized measurement, errors 

 
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were used in the analyses for each EF task based on previous intervention studies (Chooi & 
Logie, 2020; de Vries et al., 2015; Macoun et al., 2021; Maraver et al., 2016). While accuracy 
was used for cognitive empathy and summing scores of images in affective empathy entered as 
dependent variables.