Perceptions of social and work functioning are related to social anxiety and executive function in autistic adults

Abstract

Autistic adults report concerns with social skills and unemployment. Despite anxiety and difficulty with executive cognitive skills being associated with autism, no studies to date have investigated relationships between anxiety or executive cognition with social and work functioning. This study aimed to investigate the associations between perceived social anxiety, perceived and objective executive function, and perceived social and work functioning in a sample of autistic people. A total of 62 participants completed self-report questionnaires of social anxiety (via the Liebowitz Social Anxiety Scale), mental health (via the Depression Anxiety Stress Scale), executive cognition (via the Behaviour Rating Inventory of Executive Function) and perceived social and work functioning (the Work and Social Adjustment Scale), and a smaller subset (n = 36–40) completed performance-based executive function tasks (Trail Making Task and Rapid Visual Processing Task). Participants who reported having more social anxiety and more difficulty with executive cognition also perceived themselves as having poorer social and work functioning. Performance-based executive function was not related to social or work functioning. Our results suggest that perceived social anxiety and executive cognition are both areas that have potential to be targeted to investigate whether they improve social and vocational outcomes for autistic people.

Lay abstract

Many autistic adults have trouble in social situations and at work. Researchers do not know exactly why autistic people might find it difficult in these environments, and no studies to date have looked the way anxiety or other cognitive processes might affect autistic peoples’ ability to socialise and succeed in getting and keeping jobs. Anxiety (how much you worry) and difficulty with getting stuff done or switching attention (known as executive function) can be concerns for autistic people and may contribute to social and work difficulties. This study looked at the relationships between the way autistic people perceived their anxiety and executive functioning and their ability to socialise and work. Sixty-two autistic participants completed questionnaires related to their ability to socialise and work, their social anxiety and their executive function. We found that participants who thought that they had poorer ability to work also found themselves to have more difficulties with executive function and they were more socially anxious. Our results showed that how autistic participants perceived their social anxiety and executive function were important in their perception of their social skills and work ability. This study supports the idea that anxiety and executive function could be targeted in interventions to support autistic people and their social and work outcomes.

Keywords

autism spectrum disorder executive function functional ability social anxiety social functioning work functioning

It is well established that autistic adults face challenges in both social and occupational settings which contribute to lower quality of life in autistic people (Park et al., 2019). For example, autistic people report greater poorer social functioning (Barneveld et al., 2014; Levy & Perry, 2011; Pepper et al., 2018) and higher rates of unemployment, even when compared to other disability populations (Hedley, Uljarević, Cameron, et al., 2017; Hedley, Uljarević, & Hedley, 2017). There is much evidence that both social and work functioning are interrelated, as they both describe an individuals’ ability to interact socially with their environment, and there are social aspects of workplaces that can be difficult for autistic people (such as interactions with co-workers) (Bosc, 2000). Furthermore, social functioning and employment are predictive of quality of life above and beyond other factors (e.g. cognitive and adaptive abilities) in autistic people (Kandalaft & DeBrabander, 2021).

Socially, autistic people report that they struggle in areas such as making and sustaining friends and romantic partners, and in maintaining employment (Barneveld et al., 2014; Levy & Perry, 2011; Howlin et al., 2004). Furthermore, in Australia, the rate of labour force engagement for autistic people is around 42%, which is much lower compared to that of the general population (83%) and individuals with other disabilities (53%; Australian Bureau of Statistics, 2019). These statistics are comparable to countries such as the United States and the United Kingdom (Howlin et al., 2004; Ohl et al., 2017). That being said, relatively little research has been undertaken to understand the underlying factors that may be associated with the social functioning and employment success of autistic people (Roux et al., 2021).

Mechanisms of functioning

Studies investigating barriers and enablers of successful employment have looked at autistic people’s behavioural characteristics, with findings indicating that maladaptive behaviours (e.g. internalising or externalising behaviours) and overall severity of symptoms associated with the diagnosis of autism may relate to social and vocational functional outcomes (Kandalaft & DeBrabander, 2021; Taylor et al., 2014). Generally, studies show that if a person displays more diagnostic severity, cognitive impairment and behavioural issues, then they are more likely to also report co-occurring social dysfunction and are less likely to be employed (Kandalaft & DeBrabander, 2021; Levy & Perry, 2011).

Several studies (Pugliese et al., 2016; Saris et al., 2017) and reviews (Howlin & Magiati, 2017) have highlighted the role of psychosocial factors such as mood (Lai et al., 2019; Lugo-Marín et al., 2019), and difficulties with cognitive control processes, known as executive function (EF; Demetriou, Lampit et al., 2018), in the prediction of disability outcomes including social and work function. Cognitive models (Bishop, 2009; Eysenck, 1979; Eysenck et al., 2005; Shields et al., 2016) suggest that mood interacts with EF by dominating existing cognitive resources and further reducing attention and strategic processes to increase potential for poor outcomes (Demetriou et al., 2021). In other populations (such as multiple sclerosis and attention deficit hyperactivity disorder), both mental health and EF have been shown to affect both social functioning and employment outcomes (Barkley & Murphy, 2010; Rao et al., 1991). In autistic populations, where EF is typically already compromised (Demetriou, Lampit et al., 2018), co-occurring anxiety and depression may place EF at further risk of impairment and thus have a disproportionate impact on social functioning and employment outcomes. Yet to date, there has been no study which has examined these two factors and their influence on perceived social and work function.

Anxiety and depression in autism

It is well established that autistic individuals are at elevated risk of anxiety (particularly social anxiety) and depression (Hollocks et al., 2019; Park et al., 2020). A recent review found that in the autistic population, anxiety and depression were among the highest reported comorbid mental health issues (at 20% and 11%, respectively; Lai et al., 2019), which is higher than general population estimates (anxiety reported at 14.4% and depression at 6.2%; ‘Mental Health Services in Australia, Prevalence, Impact and Burden’, 2019). Although no existing studies have investigated the link between anxiety and depression and employment in autistic adults, studies have demonstrated a significant link in autistic populations between anxiety and social function in autistic people who often display higher rates of avoidance of social stimuli linked to intolerance of uncertainty around change, sensory stimuli and coping with unpleasant events (Gillott & Standen, 2007; Kuusikko et al., 2008; Wigham et al., 2015), higher rates of social fears during social interactions (Bejerot et al., 2014) and the role of depression in contributing to self-reports of overall disability outcomes (Pepper et al., 2018).

EF in autism

There is extensive evidence for EF difficulties in autistic children, adolescents and adults (see Demetriou, Lampit et al., 2018), including difficulties with cognitive flexibility (the ability to switch between thinking about different concepts), inhibitory control (the ability to inhibit irrelevant information), response inhibition (the ability to inhibit behaviours), working memory (the ability to store and manipulate information) and higher-order planning ability (monitoring and evaluating sequential actions towards a goal) (Jones et al., 2018; Miyake & Friedman, 2012). EF difficulties have also been shown to be a predictor of adaptive ability (the ability to function independently), over and above intellectual functioning or autism symptom severity (Gilotty et al., 2002; Kenny et al., 2019). In particular, the ability to initiate tasks is predictive of autistic individuals’ ability to socialise and communicate with others more effectively, (Gilotty et al., 2002) both of which are important in a workplace context. EF has also been linked to employment, where EF difficulties in other clinical populations, such as multiple sclerosis or people born with cognitive impairment, display poorer work functioning (Clemens & Langdon, 2018; Kroll et al., 2017; Tomaszewski et al., 2018). Furthermore, EF difficulties have been posited to impact other areas of functioning in autistic people, such as social cognition (Jones et al., 2018; Pellicano, 2010), social interactions (Moriguchi, 2014), mental health (Barnhill & Myles, 2001; Zimmerman et al., 2017), disability (Demetriou, Song et al., 2018) and daily functioning (Pugliese et al., 2016). It is therefore critical to collectively address co-occurring anxiety, depression and issues with EF when considering overall functioning in autistic individuals.

Much of the research on EF has shown that self-report/informant-report and performance-based (henceforth known as ‘objective’) measures of EF can yield different results. Self-report or informant-report measures of EF have been shown to have a higher correlation to other measures of disability and functioning (Barkley & Murphy, 2010), and may better differentiate between autistic and non-autistic individuals (Demetriou, Lampit et al., 2018). However, some have argued that it is important to consider both perceived (self-report) and objective measures of EF in order to account for potential bias in self-report measures (Alexander & Wilkins, 1982; Demetriou, Lampit et al., 2018). To address these issues, objective measures and self-report or informant-report measures should be aligned to EF domains where possible to provide a more comprehensive assessment of cognitive and behavioural regulation indices.

The current study

The aim of this study was to examine the influence of mental health factors and EF on perceived social and work functioning in a population of autistic adults. Negative perception of social and work functioning is significantly associated with poorer work outcomes, which can include beginning employment, leave taking and termination (Ilmarinen et al., 1991; Kandalaft & DeBrabander, 2021). There is little known, however, about the relationship between anxiety, depression, EF and self-perceived social and work functioning in autistic people. Understanding how autistic people view their ability to interact with others, sustain and maintain relationships and succeed at work is an important step towards understanding how to best support them. Taking into account cognitive models of anxiety and EF (Eysenck, 1979), we aimed to investigate the relationship between scores on self-reported social anxiety (measured via the Liebowitz Social Anxiety Scale (LSAS); Baker et al., 2002), self-reported depression (measured via the Depression Anxiety Stress Scale; Lovibond & Lovibond, 1995) and self-reported (measured via the Behaviour Rating Inventory of Executive Function, BRIEF-A; Roth et al., 2005) and objective EF tasks with the self-perceived functional ability related to work and social skills (as measured via the Work and Social Adjustment Scale (WSAS); Mundt et al., 2002) within a population of autistic adults without an additional intellectual disability. This study used both perceived and objective measures of EF in order to account for bias (e.g. mis-reporting; Alexander & Wilkins, 1982). The objective measures (the Trail Making Task and the Rapid Visual Processing Task; CANTAB Cognitive Research Software, 2004; Reitan & Wolfson, 1985) and self-report measures (the BRIEF-A metacognitive and behavioural regulation indices) were selected to align in the EF measured. We hypothesised that poorer perceived social and work functioning would be related to higher levels of perceived social anxiety, depression and anxiety symptoms, and both subjective and objective EF difficulties.

Method

Design

This study utilised a cross-sectional design. This project was a subset of a larger study investigating social and cognitive functioning in autistic adults. Participants attended a study visit at Headspace (a national youth mental health service) or the Autism Clinic for Translational Research, where they gave informed consent, followed by administration of the neuropsychological assessment and diagnostic assessment batteries (see University of Sydney, Project no. 2015/365 for full protocol). Participants attended clinics for a variety of reasons, including diagnostic assessment or support for mental health or autism-related symptoms. Questionnaires were completed by participants following diagnostic assessment at Headspace or the Autism Clinic for Translational Research. Autism Awareness Australia, Neurodevelopment Australia and their community representatives were involved in the development of the study, review of its writeup and submission process.

Participants

Sixty-two participants were recruited between January 2014 and June 2019 from Headspace and the Autism Clinic for Translational Research, located at the Brain and Mind Centre, University of Sydney. All participants had a clinical diagnosis of an autism spectrum disorder (ASD) (according to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) and also reached threshold for autism using a standardised research diagnostic assessment, the Autism Diagnostic Observation Schedule–Second Edition (ADOS-2, see Table 1; Lord et al., 2012), by research-reliable assessors (McGonagle et al., 2015). Intellectual functioning was indexed by the Wechsler Test of Adult Reading (WTAR; Holdnack, 2001), which has been demonstrated as reliable in autistic populations (Venter et al., 1992) and participants were excluded if they obtained an intelligence quotient (IQ) score below 70.

Table 1.

Participant demographics (n = 62).

	N	%
Gender (female)	20	32.26
Employed	57	91.94
Country of birth (Australia)	59	95.16
	M	SD	Range
Age (years)	23.27	6.79	16–46
IQ	107.17	10.07	73–119
ADOS-2 comparison score	9.71	2.75	7–18

SD: standard deviation; IQ: intelligence quotient (WTAR, Wechsler Test of Adult Reading, Holdnack, 2001), ADOS-2: Autism Diagnostic Observation Schedule–Second Edition (Lord et al., 2012).

WTAR normative M = 100, SD = 15, higher scores on ADOS-2 reflect greater autistic features.

Materials

Work functioning measure

WSAS

The WSAS (Mundt et al., 2002) is a 5-item tool used to measure self-reported functional difficulties in performing everyday activities. Each item is rated using an 8-point Likert-type scale ranging from 0 (not at all impaired) to 7 (very severely impaired). The WSAS has been validated in clinical populations, has good reported internal consistency (Cronbach’s α coefficients = 0.70–0.93) and test–retest reliability (2 weeks = 0.73). The WSAS had good internal consistency in this sample (Cronbach’s α coefficient = 0.71). We utilised the raw total score from this scale to index participants’ ability to carry out activities related to work, social life and leisure.

Social anxiety measure

LSAS–Self Report

The LSAS–Self-Report (Baker et al., 2002) is a 24-item self-report questionnaire measuring a person’s degree of social anxiety. The LSAS contains two domains: fear and avoidance. The LSAS has reported high internal consistency (Cronbach’s α coefficients for total scores = 0.96, in this study α = 0.91) and good test–retest reliability (12 weeks, r = 0.83). The total score was used in this study; higher scores indicate greater social anxiety.

Mental health measure

The Depression Anxiety Stress Scales

The Depression Anxiety Stress Scales (DASS-21; Lovibond & Lovibond, 1995) were used to screen participants’ state-based self-reported depressive, stress and anxiety symptoms. The DASS-21 is a 21-item questionnaire measuring three domains: depression, anxiety and stress. Behavioural items relating to these domains are rated on a 4-point Likert-type scale, ranging from ‘did not apply to me’ (score of 0) to ‘applied to me most of the time’ (score of 3). In this sample, items relate to one of the three domains and are summed to determine the total domain score, ranging from 0 to 21 for all three domains. The DASS-21 has good internal consistency (Cronbach’s α coefficients ranging 0.82–0.97, for this study α = 0.86–0.92), and acceptable concurrent validity (r = 0.40–0.65). This study used the three domain scores, and a higher score indicated the presence of more symptoms.

EF measures

In order to gain an overview of participants’ EF, we measured both self-reported EF and then aligned the EF domains measured in the self-report assessment with objective measures that measure similar constructs.

BRIEF-A

BRIEF-A (Roth et al., 2005) is a 75-item self-report questionnaire that assesses everyday EF. The BRIEF-A also yields a global executive composite, and two index scores: behavioural regulation index (made up of the domains: inhibit, shift and emotional control) and Metacognition Index (made up of the domains: initiate, working memory, plan/organise, task monitor and organisation). This study utilised the BRIEF-A behavioural regulation index and Metacognition Index T-scores, where a higher score indicated more EF difficulty. The BRIEF-A has demonstrated excellent internal consistency (Cronbach’s α coefficients ranging from 0.93 to 0.96 for the three indices) and 1-month test–retest (r = 0.93–0.94). Reliability estimates for this scale in the current sample were excellent: α = 0.96 for the global executive composite, α = 0.93 for the Behaviour Regulation Index and α = 0.95 for the Metacognition Index.

Rapid Visual Processing Test

The Rapid Visual Processing Test (RVP; CANTAB Cognitive Research Software, 2004) is also part of the CANTAB battery and measures sustained attention, which aligns with the some of the domains in the BRIEF-A Metacognition Index (working memory). The RVP was completed by 36 participants. The RVP involves a white box shown in the centre of a PC screen, inside which digits from 2 to 9 appear in a pseudo-random order, at the rate of 100 digits per minute. Participants are requested to detect target sequences of digits (e.g. 2-4-6, 3-5-7 and 4-6-8). When the participant sees the target sequence, they must respond by selecting a button in centre-screen as quickly as possible. The outcome measure of the RVP is latency, false alarms and sensitivity to the target (ranging from 0 to 1; d prime) which is derived from Signal Detection Theory (Stanislaw & Todorov, 1999). A score of ‘1’ indicates that the participant always detected the target.

Trail Making Test A/B

The Trail Making Test (TMT; Reitan & Wolfson, 1985) is an objective measure of psychomotor speed and mental flexibility. The TMT was completed by 40 participants. The TMT consists of part A, where the participant is asked to draw lines connecting numbers on a page in an ascending order, and part B, where the participant must alternate between numbers and letters in ascending order (e.g. 1, A, 2, B). TMT A measures mental tracking and motor speed, and TMT B captures selective attention and cognitive flexibility (aligning with some of the tasks within the BRIEF-A behavioural regulation index, i.e. inhibit and shift) (Roth et al., 2005). We also calculated time difference known as TMT interference (TMT B time − TMT A time), which removes the speed component from the test and gives an indication of ability to detect problems with multiple tracking (Zhang et al., 2015).

Statistical analysis

Data analysis was conducted in Stata (Baum et al., 2010). Shapiro–Wilk tests indicated that some of our variables (WSAS, DASS depression and anxiety domains, RVP, and TMT A and B) deviated significantly from normality (p < 0.05, see Supplementary Table 10); therefore, non-parametric tests were used when analysing these variables specifically, and bootstrapping was performed on the regression analysis. Some performance-based measures were not completed by all participants due to testing fatigue (between 30% and 37% of participants); therefore, the n is smaller for those assessments. In order to account for the missing data in those measures, we have performed worst–best sensitivity analysis as recommended by Jakobsen et al. (2017) (see Supplementary Tables 8 and 9). There were no significant differences between those who did or did not complete the performance-based measures on any of our variables of interest (see Supplementary Table 11). All variables that did not deviate from normality were investigated using parametric tests where appropriate. First, we conducted t-tests to determine any differences in participants in relation to their employment status in the areas of perceived social anxiety, depression, anxiety and EF. Pearson’s or Spearman’s correlations were then conducted to determine if any relationships existed between depression, anxiety, social anxiety scores and EF and work, social or leisure functioning scores (on the WSAS). Based on those relationships, we performed a multiple linear regression on significant variables, using backwards stepwise elimination in order to remove variables that did not have a significant effect on the model, to determine whether individual differences in these variables contributed to variation in participants’ work, social and leisure functioning.

Results

Descriptive statistics for the 62 participants are shown in Table 2. Participants who were employed and were not employed did not differ significantly in relation to their scores for the LSAS (t(61) = 1.51, p = 0.14, d = 0.36), DASS depression (H(1) = 0.66, p = 0.42, d = 0.02), DASS anxiety (H(1) = 0.19, p = 0.67, d = 0.30), DASS stress (t(61) = −0.15, p = 0.89, d = 0.07), BRIEF-A behavioural regulation index (t(61) = −0.43, p = 0.67, d = −0.23), BRIEF-A Metacognitive Index (t(61) = −0.29, p = 0.78, d = −0.14), TMT A (H(1) = 0.07, p = 0.79, d = −0.33), TMT B (H(1) = 0.13, p = 0.72, d = −0.61) or RVP (H(1) = 1.81, p = 0.18, d = 0.86) or on their WSAS total (H(1) = 3.23, p = 0.07, d = 0.46) (see Supplementary Table 11). When worst–best sensitivity analyses were run, participants still did not differ significantly on any measure (p = 0.28–0.91, see Supplementary Tables 8 and 9).

Table 2.

Participant scores on the social, mental health and EF measures.

Measure	Employed				Not employed
Measure	n	M	SD	Range	n	M	SD	Range
WSAS total	57	21.13	17.12	0–83	5	28.80	6.91	20–39
LSAS	57	64.77	31.91	3–144	5	76.22	32.48	31–114
DASS depressive	57	10.11	6.10	0–21	5	10.2	6.30	2–19
DASS stress	57	11.51	5.05	1–21	5	11.80	5.93	6–20
DASS anxiety	57	8.11	5.67	0–21	5	9.80	5.63	2–17
BRIEF-A Behaviour Regulation Index (T-score)	57	65.81	13.91	39–98	5	60.80	8.80	48–69
BRIEF-A Metacognition Index (T-score)	57	64.46	12.94	41–95	5	63.40	11.10	51–79
RVP	36	0.88	0.07	0.73–0.97	3	0.94	0.04	0.9–0.98
TMT A	40	38.7	20.85	13–133	3	32.00	44.94	35–210
TMT B	40	83.15	44.93	13–210	3	56.33	19.01	37–75
TMT interference	40	44.45	35.78	2–157	3	24.33	12.74	16–39

EF: executive function; SD: standard deviation; WSAS: Work and Social Adjustment Scale; DASS: Depression Anxiety Stress Scale; BRIEF-A: Behaviour Rating Inventory of Executive Function; LSAS: Liebowitz Social Anxiety Scale; RVP: Rapid Visual Processing Test; TMT: Trail Making Task.

WTAR normative M = 100, SD = 15, higher scores on ADOS-2 reflect greater autistic features.

Associations with perceived work functioning

Correlations with Bonferroni’s corrections between variables are presented in Table 3. As our primary interest for this study was social and work functioning, we then entered significant variables (see Table 3) into a regression model to determine the predictive ability of significant variables on WSAS total score (see Table 4). Bootstrapping was performed on the regression to account for repeated comparisons. The EF and social variables that were found to be significantly related to WSAS scores were entered into this backwards stepwise regression, with IQ, ADOS-2 scores, employment status and age included as covariates, and significant contributors to the model are included in Table 4. The final model demonstrated that increases on the BRIEF-A Metacognition Index and the LSAS significantly predicted increases in scores on the WSAS total score, R² = 0.53, F(2, 61) = 43.11, p < 0.001, η² = 0.59.

Table 3.

Correlation matrix for WSAS total, WSAS work functioning, EF, social anxiety and mental health (with Bonferroni’s corrections).

	1. WSAS total	2. LSAS	3. DASS depression	4. DASS anxiety	5. DASS stress	6. BRIEF-A BRI	7. BRIEF-A MI	8. RVP	9. TMT A	10. TMT B	11. TMT interference	12. IQ
1. WSAS total	–
2. LSAS	0.64***	–
3. DASS depression	0.54***	0.67***	–
4. DASS anxiety	0.45***	0.53***	0.74***	–
5. DASS stress	0.44***	0.46***	0.61**	0.63***	–
6. BRIEF-A BRI	0.28*	0.32	0.59**	0.50**	0.76***	–
7. BRIEF-A MI	0.48***	0.33	0.52**	0.29	0.50**	0.60**	–
8. RVP	0.21	0.18	0.16	0.06	−0.19	−0.18	0.04	–
9. TMT A	0.14	0.16	0.05	0.01	0.05	0.17	−0.15	−0.18	–
10. TMT B	0.17	0.22	−0.03	−0.05	−0.07	0.16	−0.04	−0.03	0.85***	–
11. TMT interference	0.15	0.004	−0.25	−0.29	−0.26	0.07	0.15	0.17	0.34	0.71***	–
12. IQ	0.24	0.13	0.08	−0.19	−0.26	−0.20	−0.21	0.28	−0.17	−0.32*	−0.34*	–

WSAS: Work and Social Adjustment Scale; EF: executive function; DASS: Depression Anxiety Stress Scale; BRIEF-A: Behaviour Rating Inventory of Executive Function; BRI: Behaviour Regulation Index; LSAS: Liebowitz Social Anxiety Scale; MI: Metacognition Index; RVP: Rapid Visual Processing Test; TMT: Trail Making Task; IQ: intelligence quotient.

p < 0.05; **p < 0.01; ***p < 0.001.

Table 4.

Regression analysis of variables that significantly contribute to participant WSAS total score.

WSAS total (DV)	Standardised coefficients beta	Standard error	p-value	z	95% CI bootstrapped
LSAS	0.29	0.05	0.000**	3.17	0.19 to 0.38
BRIEF-A Metacognition Index	0.30	0.07	0.000**	3.42	0.17 to 0.44
Constant	−21.03	7.04	0.003**	−3.92	−34.83 to –7.23

WSAS: Work and Social Adjustment Scale; CI: confidence interval; BRIEF-A: Behaviour Rating Inventory of Executive Function; DV: Dependant Variable; LSAS: Liebowitz Social Anxiety Scale.

p < 0.05; **p < 0.01; ***p < 0.001.

Discussion

This study explored contributors to perceived social and work functioning in a sample of autistic adults. Specifically, we showed that self-reported social anxiety and self-reported EF both significantly contributed to self-perceived social and work functioning, independent of employment status, IQ or autism symptom severity. We also found that self-reported social anxiety and self-reported EF contributed to self-perceived social and work functioning. The more severe the social anxiety and perceived difficulties in metacognition EF, the poorer participants perceived their own social and work functioning. As perceived work functioning has been associated with poorer work outcomes, excess leave and termination, at least in non-autistic populations (Ilmarinen et al., 1991), our findings suggest that social anxiety and everyday EF might be two potential targets to support autistic people’s ability to gain and sustain employment. Furthermore, due to the interconnectedness of social and work function, and the influence of both on a person’s quality of life and independence (Kandalaft & DeBrabander, 2021; Pellicano et al., 2014), helping to improve social anxiety symptoms and EF may have significant benefits for autistic people.

In terms of social anxiety, the lifetime prevalence for autistic individuals experiencing clinical social anxiety has been reported to be as high as 29.2% (Simonoff et al., 2008), which is much higher than the general population estimates (8.4%; Crome et al., 2015). This study showed that 68% of this population met clinical cut-offs for Social Anxiety Disorder on the LSAS. Theories underlying social anxiety in autism posit that autistic people have increased difficulty with social skills leading to fear of negative evaluation in social situations and social withdrawal (Bemmer et al., 2021; Spain et al., 2016). This could be a potential barrier to not only sustaining relationships with others, but also in their employment, as focusing on negative cues in the workplace could exacerbate negative experiences in work situations for autistic people. Studies investigating the implications of social anxiety on employment outcomes are scarce; however, one study has reported unemployment rates for non-autistic individuals with social anxiety to be around 16% (Moitra et al., 2011). Strategies aimed at reducing social anxiety and fear of negative evaluation for the individual in their workplace and social settings may be beneficial to gaining and sustaining employment.

Self-reported metacognitive EF was positively related to social and work functioning, such that greater perceived EF difficulties were associated with poorer perceived social and work functioning. In particular, participants who rated their functioning as poorer also reported poorer metacognition, including difficulty with initiating activities, generating problem-solving ideas, sustaining working memory, and planning and organising activities. Our results are in line with previous research demonstrating that self-reported difficulties in EF, particularly working memory, is related to both issues with social competence and communication (Berard et al., 2017; McEvoy et al., 1993) and also with poorer employment outcomes in other clinical populations (Altshuler et al., 2007; Tomaszewski et al., 2018). Environmental or individual supports (e.g. social skills training, self-regulation skills, job coaching, supervisory mentoring on work tasks and organisation skills) for autistic people who report having difficulty with domains of EF, such as working memory, may be considered as interventions to improve confidence and outcomes.

Our objective measures of EF did not, however, predict perceived social and work functioning. There is already a growing body of evidence suggesting neuropsychological tests are less predictive of everyday outcomes for autistic people, and non-autistic people with other disorders such as depression, in comparison to self-report or informant-report measures of EF (Demetriou, Song et al., 2018; Kenworthy et al., 2008). It has been argued that self-report or informant-report measures may better assess everyday tasks required for real-world functioning (Demetriou, Lampit et al., 2018). It may also be the case, however, that in this study the self-report measures were conflated, and in fact, EF is not related to social and work function. We should also note that the smaller sample size may also be related to the lack of associations between the objective EF measures and social and work function in this study. Although we do report similar findings using worst–best sensitivity analysis, our results should be interpreted with the sample size considered. Further evaluation of self-report or informant-report and objective EF using objectively assessed social skills or work performance indicators might be useful to further tease apart these relationships.

In general, cognitive-behavioural interventions have been found to improve quality of life and coping responses, particularly in anxious populations (for meta-analyses, see Carolan et al., 2017; van der Klink et al., 2001). Previous studies investigating employment interventions within autistic populations have focussed on job coaching and supported work placement (for a review, see Taylor et al., 2012). Yet, no interventions within autism research have previously implemented a combination of anxiety-focussed therapies with vocational and social interventions, nor have any focussed on improving EF. Our findings suggest that interventions targeting social anxiety and executive functioning could provide benefit for autistic individuals as part of social and work function support.

There are limitations to this study. First, we used self-report measures of perceived social and work functioning, EF and social anxiety, which may have conflated our results. Future studies are required to explore how social anxiety and EF may relate to objective functioning measures. Nevertheless, perceived social and work functioning, regardless of the objective outcome, has been shown to impact quality of life, confidence, independence and long-term work outcomes (for a review, see Compte & Postlewaite, 2004), making this area a viable target for intervention and support. Second, our assessments of EF did not encompass all commonly accepted domains of EF (Miyake & Friedman, 2012); however, we did measure a broad range of EF. A recent meta-analysis by Demetriou et al. (2018) has suggested that measurement and impairment across EF domains, such as those included in the behavioural regulation and metacognition indices, in autistic people may be relatively equivalent (in other words, there is consistent executive dysfunction regardless of domain). Future research should further investigate the relationship between various EF domains and social and work function outcomes. Third, there were no participants with an IQ below 70 in this study, and the sample overall showed a relatively high IQ level. Further this sample presented to service for a mix of diagnostic, mental health or support relating to autism symptoms. This sample is, therefore, not representative of all autistic adults, and future studies could include individuals with additional intellectual disabilities and sample those broadly from the general community. Finally, our sample size was moderate, although we had very few unemployed participants, and the performance-based EF assessments were not completed by all participants due to testing fatigue. In addition, the attrition in objective EF tasks may not have been random and were very likely due to resource availability, where participants with more difficulty in EF may not have been able to complete the tasks, and therefore, our results may have been minimised due to less variance in objective EF. We did, however, include worst–best sensitivity analyses (see Supplementary Tables 8 and 9) and we found no significant results when imputing data. A post hoc power analysis of our sample revealed that we were sufficiently powered for regression analysis with a medium effect size (0.15); however, replication of this study is required in a larger sample, with emphasis on objective measures.

Conclusion

This is the first study known to examine the potential sources of perceived social and work functioning in young adults who are autistic. Our results showed that self-reported EF and social anxiety contribute to perceived social and work functioning. This study highlights the importance of taking into account perceived EF and social anxiety when considering how best to support positive outcomes, such as getting and sustaining relationships and work, in autistic populations. The results from this study should be used to inform social skills and employment interventions for autistic individuals, potentially utilising cognitive behavioural therapy (CBT) and other neurocognitive therapies (e.g. cognitive remediation), as well as considering social and workplace training to support their needs.

Supplemental Material

sj-pdf-1-aut-10.1177_13623613211013664 – Supplemental material for Perceptions of social and work functioning are related to social anxiety and executive function in autistic adults

Supplemental material, sj-pdf-1-aut-10.1177_13623613211013664 for Perceptions of social and work functioning are related to social anxiety and executive function in autistic adults by Alix Woolard, Elizabeth Stratton, Eleni A Demetriou, Kelsie A Boulton, Elizabeth Pellicano, Nick Glozier, Vicki Gibbs, Nicole Rogerson, Philippa Quinn, Ian B Hickie and Adam J Guastella in Autism

Footnotes

Author contributions

A.W., E.S. and A.J.G. designed the study. E.A.D. collected the study data. A.W. and E.S. analysed the data. A.W. developed the first draft. A.W., E.S., E.A.D., K.B., E.P., N.G., V.G., N.G., P.Q., I.H. and A.J.G. provided comment on drafts and approved final submission.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethical approval

The ethical approval was provided by the University of Sydney Ethics Committee (Protocol no. 2013/352).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This project was supported by an Infrastructure, Linkage and Capacity Building Project from the National Disability Insurance Scheme.

ORCID iDs

Alix Woolard

Elizabeth Stratton

Kelsie Boulton

Elizabeth Pellicano

Adam J Guastella

Supplemental material

Supplemental material for this article is available online.

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