Expression Recognition Difficulty Is Associated with Social But Not Attention-to-Detail Autistic Traits and Reflects Both Alexithymia and Perceptual Difficulty

Face perception and facial emotional expression recognition ability: Both unique predictors of the broader autism phenotype

Autism spectrum disorder (ASD) and the broader autistic phenotype (BAP) have been suggested to be associated with perceptual-cognitive difficulties processing human faces. However, the empirical results are mixed, arguably, in part due to inadequate samples and analyses. Consequently, we administered the Cambridge Face Perception Test (CFPT), the Reading the Mind in the Eyes Test (RMET), a vocabulary test, and the Autism Quotient (AQ) to a sample of 318 adults in the general community. Based on a disattenuated path analytic modelling strategy, we found that both face perception ability (β = -.21) and facial emotional expression recognition ability (β = -.27) predicted uniquely and significantly the Communication dimension of AQ. Vocabulary failed to yield a significant, direct effect onto the Communication dimension of the AQ. We conclude that difficulties perceiving information from the faces of others may contribute to difficulties in nonverbal communication, as conceptualised and measured within the context of BAP.

The Relationship Between Autistic Traits and Quality of Life: Investigation of Indirect Effects Through Self-Determination

Background

Self-determination, described broadly as experiencing causal agency, is positively associated with quality of life (QoL) and increases through satisfaction of three basic psychological needs: autonomy (feeling able to make choices free from pressure), competence (perceived self-efficacy), and relatedness (social connection). Both unsupportive environments and challenges with social interaction can interfere with satisfaction of psychological needs. Social challenges are a key trait for autism diagnosis, and unsupportive environments are also known to adversely affect QoL for autistic people. Autistic people report, on average, lower self-determination than non-autistic people. Therefore, it is hypothesized that higher levels of autistic traits may reduce opportunities to develop self-determination, affecting QoL.

Methods

We tested a parallel indirect effects model where we hypothesized that the relationships between autistic traits and four domains of QoL (psychological, social, physical, and environmental) would be indirectly influenced through self-determination (represented through satisfaction of the basic psychological needs for autonomy, competence, and relatedness). This study drew participants from the general population (N = 262; M AGE = 37.6, standard deviation = 11.92; 1.9% reported an autism diagnosis and 2.7% identified as autistic without a diagnosis). Participants completed an online survey.

Results

Higher levels of autistic traits were associated with lower levels of self-determination and lower levels of QoL, and there was a significant indirect effect between autistic traits and QoL via self-determination. More specifically, we found a significant indirect effect between autistic traits and all QoL domains via competence; between autistic traits and the environmental, social, and psychological QoL domains via relatedness; and between autistic traits and the physical and environmental QoL domains through autonomy.

Conclusions

Our results suggest that supporting satisfaction of the needs for autonomy, competence, and relatedness may represent an important element in designing effective programs to support the development of self-determination in people with higher levels of autistic traits (potentially including autistic individuals) and also to support these people to improve their QoL.

General figure and face-specific closure ability: predictors of trait-autism?

Little research has examined the association between general figure closure speed, a stratum I ability within the Cattell-Horn-Carroll (CHC) model of intelligence, and face-specific closure ability; an important consideration, as some research suggests face processing is independent of other abilities. Additionally, figure closure ability (general and face) may correlate negatively with trait-autism, due to theorised autism-related difficulties in global processing. Therefore, in addition to developing a psychometrically robust short-form Mooney face detection task, we administered the Gestalt Figure Completion Test and the Autism Spectrum Quotient to a sample of 263 general community adults. We found convergent validity between face-specific and general figure closure ability (r = .44, 95%CI:[.30, .58]). Furthermore, based on a latent variable model, general figure closure ability was directly, and face-specific figure closure ability indirectly, negatively associated with trait-autism (i.e., nonverbal communication). We conclude that face detection ability evidences convergent validity with general figure closure ability and can be measured reliably in less than four minutes. Finally, a general, rather than face-specific, figure closure process may tap more directly into autism-like nonverbal communication ability, supporting the notion that global processing abilities of non-face objects may better reflect the requirements to ‘fill in the gaps’ in social contexts.

Autism traits dimensionality and multivariate relationship with alexithymia and anxiety in the general population

BACKGROUND

Autism is characterized by social and non-social alterations observed beyond the clinical diagnosis. Research analyzing the expression of autism traits in the general population helps to unravel the relationship between autism dimensions and other associated variables, such as alexithymia and anxiety. The Autism-Spectrum Quotient (AQ) was developed to assess autism traits in the general population; however, inconsistent results regarding its dimensionality have emerged.

AIMS

This study aimed to extend evidence about the AQ measurement model, and explore the multivariate relationship between autism traits, alexithymia, and trait anxiety.

METHODS

292 adults of the general population were recruited. An Exploratory Factor Analysis and Confirmatory Factor Analysis were performed to assess the factorial structure of AQ. A path analysis was carried out to explore the relationship between autism traits, alexithymia, and trait anxiety.

RESULTS

The results supported a three-factor model of AQ. The path analysis model showed evidence of a significant role of alexithymia as a mediator of the relationship between autism traits and anxiety.

CONCLUSIONS AND IMPLICATIONS

The present study provides empirical support for a three-factor model of AQ in the general population. The association between autism traits, alexithymia, and anxiety dimensions highlights the multidimensional nature of these variables and the need to account for their distinct impact on autism-related variables.

Alexithymia in autism: cross-sectional and longitudinal associations with social-communication difficulties, anxiety and depression symptoms

BACKGROUND

Alexithymia (difficulties in identifying and describing emotion) is a transdiagnostic trait implicated in social-emotional and mental health problems in the general population. Many autistic individuals experience significant social-communication difficulties and elevated anxiety/depression and alexithymia. Nevertheless, the role of alexithymia in explaining individual variability in the quality/severity of social-communication difficulties and/or anxiety and depression symptoms in autism remains poorly understood.

METHODS

In total, 337 adolescents and adults (autism N = 179) were assessed for alexithymia on the Toronto Alexithymia Scale and for social-communication difficulties, anxiety and depression symptoms. A total of 135 individuals (autism N = 76) were followed up 12-24 months later. We used regression models to establish cross-sectional and longitudinal associations between alexithymia, social-communication difficulties, anxiety and depression symptoms.

RESULTS

Autistic individuals reported significantly higher alexithymia than comparison individuals (p < 0.001, r effect size = 0.48), with 47.3% of autistic females and 21.0% of autistic males meeting cut-off for clinically relevant alexithymia (score ⩾61). Difficulties in describing feelings were particularly associated with current self-reported social-communication difficulties [p < 0.001, β = 0.57, 95% confidence interval (CI) 0.44-0.67] and predicted later social-communication difficulties (p = 0.02, β = 0.43, 95% CI 0.07-0.82). Difficulties in identifying feelings were particularly associated with current anxiety symptom severity (p < 0.001, β = 0.54, 95% CI 0.41-0.77) and predicted later anxiety (p = 0.01; β = 0.31, 95% CI 0.08-0.62).

CONCLUSIONS

Our findings suggest that difficulties in identifying v. describing emotion are associated with differential clinical outcomes in autism. Psychological therapies targeting emotional awareness may improve social-communication and anxiety symptoms in autism, potentially conferring long-term benefits.

Objective and Subjective Measurement of Alexithymia in Adults with Autism

High rates of alexithymia, a condition characterised by difficulties identifying and describing emotions, are frequently reported in both children and adults with autism spectrum disorder (ASD). However, the dilemma of measuring alexithymia via self-report has rarely been addressed. In this study, we compared objective and subjective measures of alexithymia in adults with ASD and typically developing adults. We found significantly higher levels of alexithymia in the ASD sample as measured by both self-report on the Toronto Alexithymia Scale (TAS-20) and by the observer rated Alexithymia Provoked Response Scale (APRQ). However, the two measures did not correlate with each other. We explore the different facets of the alexithymia construct that these two measures may be distinguishing.

Autistic Traits are Associated with Less Precise Perceptual Integration of Face Identity

Face recognition difficulties are common in autism and could be a consequence of perceptual atypicalities that disrupt the ability to integrate current and prior information. We tested this theory by measuring the strength of serial dependence for faces (i.e. how likely is it that current perception of a face is biased towards a previously seen face) across the broader autism phenotype. Though serial dependence was not weaker in individuals with more autistic traits, more autistic traits were associated with greater integration of less similar faces. These results suggest that serial dependence is less specialised, and may not operate optimally, in individuals with more autistic traits and could therefore be a contributing factor to autism-linked face recognition difficulties.

The Prediction Analysis of Autistic and Schizotypal Traits in Attentional Networks

OBJECTIVE

Empirical findings confirmed that autistic and schizotypal traits are associated with attentional function as well as include various dimensions. So far, no study has reported which dimension of these traits relates to attentional networks. This study aimed to find out whether there are associations between attentional networks and autistic traits; and between attentional networks and schizotypal traits.

METHODS

A total of 449 volunteers was included in this study, and autism-spectrum quotient (AQ), schizotypal personality questionnaire (SPQ), and attention network test (ANT) were used to measure autistic traits and schizotypal traits. The three independent attentional networks, including alerting network, orienting network, and executive control network, were also measured.

RESULTS

Autistic traits were associated with the orienting network, whereas schizotypal traits were associated with the orienting network and executive control network. Furthermore, attentional networks could be predicted by specific dimensions of autistic and schizotypal traits. AQ-attention switching [0.104 (-1.175- -0.025), p=0.041] and AQ-attention to detail [-0.097 (-0.798- -0.001), p=0.049] were significant predictors of orienting network and gender were significant predictor of executive network (Beta=0.107; 95% CI=-0.476-10.139; p=0.031). Whereas, schizotypal dimension "interpersonal" was a significant predictor of all three attentional networks [Alerting: 0.147 (-0.010-0.861), p=0.045; Orienting: 0.147 (0.018-0.733), p=0.040; Executive: 0.198 (0.215-1.309), p=0.006].

CONCLUSION

This study demonstrated that autistic and schizotypal traits were associated with attentional networks. The specific dimensions of autistic and schizotypal traits could predict attentional networks. Nevertheless, the attentional networks predicted with these two traits were different.