Gender bias in autism screening: measurement invariance of different model frameworks of the Autism Spectrum Quotient

Sex Differences in Adult Autism Screening: A Comparison of Current Self-Report and Retrospective Parent-Report Measures

This study investigated sex differences in adult autism screening by comparing self-reports on current traits (Autism Spectrum Quotient; AQ) and parent-reports on childhood traits (Relatives Questionnaire; RQ). The aim was to examine the differential contribution of these distinct measures to diagnostic classification in both sexes. The study compared 102 clinically diagnosed autistic adults (30 females) and 152 non-autistic adults (60 females), aged 17-35 years. Participants completed the AQ, while their parents completed the RQ. Multivariate analysis of variance and sex-stratified discriminant analyses were employed to evaluate measurement patterns in males and in females. Significant main effects were found for diagnostic group on both measures and for sex on the RQ only. Group × sex interactions were significant for both measures. Within the autistic group, males and females showed no significant difference in AQ scores, but females scored significantly lower than males on the RQ. Discriminant analyses revealed high classification accuracies for both males (95.1%) and females (96.7%), with different weighting patterns between males (AQ = 0.597 [CI: 0.413-0.720], RQ = 0.712 [CI: 0.553-0.789]) and females (AQ = 0.763 [CI: 0.637-0.898], RQ = 0.478 [CI: 0.191-0.616]). The findings suggest that current self-report may be more central for identifying autism in females, while a more balanced combination of current-self and past-parent reports may be optimal for males. These sex-specific patterns highlight the importance of considering both current self-reported traits and developmental history in adult autism screening, with potential implications for improving diagnostic accuracy across sexes.

"What does 'often' even mean?" Revising and validating the Comprehensive Autistic Trait Inventory in partnership with autistic people

BACKGROUND

In this study, we revised the comprehensive autistic trait inventory (CATI)-a self-report inventory of autistic traits, in collaboration with autistic people and provided preliminary evidence for its validity as a self-report measure of autistic traits in the general population. An established strength of the CATI is its ability to capture female autistic traits. Our project aimed to extend this further, to increase the inventory's accessibility, and to minimise stigma induced by deficit-based representations of autistic experience.

METHODS

Together with 22 individuals from the autism and autistic communities, we created the Revised Comprehensive Autistic Trait Inventory (CATI-R). Revisions included rewording items to increase clarity or reduce stigma and expanding items to capture diverse autistic experiences. We also present a series of guidelines for developing self-report inventories of subclinical neurodivergent traits. We validated the CATI-R within a large sample (n = 1439), comprising people with a self-reported autism diagnosis (n = 331), people who self-identified as autistic (n = 44), and non-autistic participants (n = 1046).

RESULTS

We successfully validated a revision of the CATI. A confirmatory factor analysis supported the six-subscale structure (two-factor bifactors model: Chi-squared = 2705.73, p < .001, RMSEA = .04, SRMR = .03, CFI = .95, TLI = .94). Spearman's rank correlations showed positive relationships between all subscales (all rs >  .56, ps < .001). Convergent validity was demonstrated by significant correlations between the CATI-R and two contemporary inventories of autistic traits: the AQ (rho = .86, p < .01) and BAPQ (rho = .82, p < .01). Finally, a measurement invariance analysis indicated that total-scale scores can be compared across genders.

LIMITATIONS

Our study presents only initial evidence for the validity of the CATI-R that should be enriched with further analyses and types of data, including a larger number of participants who do not identify as male or female.

CONCLUSIONS

This project provides a revised trait inventory that resonates with actual autistic experience, along with guidelines for creating self-report measures that are sensitive, accessible, and non-stigmatising.

Autistic Traits, Communicative Efficiency, and Social Biases Shape Language Learning in Autistic and Allistic Learners

There is ample evidence that individual-level cognitive mechanisms active during language learning and use can contribute to the evolution of language. For example, experimental work suggests that learners will reduce case marking in a language where grammatical roles are reliably indicated by fixed word order, a correlation found robustly in the languages of the world. However, such research often assumes homogeneity among language learners and users, or at least does not dig into individual differences in behavior. Yet, it is increasingly clear that language users vary in a large number of ways: in culture, in demographics, and-critically for present purposes-in terms of cognitive diversity. Here, we explore how neurodiversity impacts behavior in an experimental task similar to the one summarized above, and how this behavior interacts with social pressures. We find both similarities and differences between autistic and nonautistic English-speaking individuals, suggesting that neurodiversity can impact language change in the lab. This, in turn, highlights the potential for future research on the role of neurodivergent populations in language evolution more generally.

Protocol for a systematic review evaluating psychometric properties and gender-related measurement (non)invariance of self-report assessment tools for autism in adults

BACKGROUND

Given the recent evidence on gender differences in the presentation of autism, there is an increasing concern that current tools for autism do not adequately capture traits more often found in women. If tools for autism measure autistic traits differently based on gender alone, their validity may be compromised as they may not be measuring the same construct across genders. Measurement invariance investigations of autism measures can help assess the validity of autism constructs for different genders. The aim of this systematic review is to identify and critically appraise the psychometric properties of all self-report tools for autism in adults that meet two criteria: (a) they have been published since or included in the NICE (2014) recommendations, and (b) they have undergone gender-related measurement invariance investigations as part of their validation process.

METHODS

A search of electronic databases will be conducted from 2014 until the present using MEDLINE, Embase, and PsycINFO using predefined search terms to identify eligible studies. The search for grey literature will include sources such as OpenGrey, APA PsycEXTRA, and Scopus. Two reviewers will independently screen titles, abstracts, and full texts for eligibility. The references of included studies will be searched for additional records. The methodological quality of the studies will be evaluated using the COSMIN Risk of Bias checklist, while psychometric quality of findings will be assessed based on criteria for good measurement properties and ConPsy checklist. The quality of the total body of evidence will be appraised using the approach outlined in the modified GRADE guidelines.

DISCUSSION

This systematic review will be among the first to assess the psychometric properties and gender-related measurement invariance of self-reported measures for autism in adults that were published since (or included in) NICE (2014) guidelines. The review will provide recommendations for the most suitable tool to assess for autism without gender bias. If no such measure is found, it will identify existing tools with promising psychometric properties that require further testing, or suggest developing a new measure.

SYSTEMATIC REVIEW REGISTRATION

The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO). The registration number is CRD42023429350.

Special considerations for assessing and caring for autism in girls and women

PURPOSE OF REVIEW

As the specificities of autistic women are increasingly recognized, this review aims to highlight emerging areas of research. These areas primarily focus on measurement bias of diagnostic tools, the physical and mental health of autistic women, and the unique aspects of the lives of autistic women, both personally and professionally across all life stages.

RECENT FINDINGS

Conventional diagnostic tools struggle to capture the specificities of autism in females, but more sensitive instruments like the GQ-ASC (Girls' Questionnaire for Autism Spectrum Conditions), later also referred to as Q-ASC (Questionnaire for Autism Spectrum Conditions) in the scientific literature, show better performances. Autistic women face particular challenges, including an increased risk of physical and mental health problems throughout their lives as women (puberty, motherhood, menopause). Autistic women also encounter specific difficulties in their employment that require greater consideration.

SUMMARY

The findings of this review identify research areas that need to be developed to better understand and support autistic girls and women and to enhance clinical practice for them.

Racial, Ethnic, and Geographic Diversity in Population Neuroscience

In this chapter, we consider lack of racial, ethnic, and geographic diversity in research studies from a public health perspective in which representation of a target population is critical. We review the state of the research field with respect to racial, ethnic, and geographic diversity in study participants. We next focus on key factors which can arise from the lack of diversity and can negatively impact external validity. Finally, we argue that the public's health, and future research, will ultimately be served by approaches from both recruitment and representation science and population neuroscience, and we close with recommendations from these two fields to improve diversity in studies.

Measuring the Autistic Women's Experience (AWE)

We developed a Dutch questionnaire called the Autistic Women's Experience (AWE) and compared its psychometric properties to the Autism Spectrum Quotient (AQ). Whilst attenuated gender differences on the AQ have been widely replicated, this instrument may not fully capture the unique experience of autistic women. The AWE was co-developed with autistic women to include items that reflect autistic women's experience. We investigated the AWE (49 items) and compared it with the AQ (50 items) in Dutch autistic individuals (N = 153, n = 85 women) and in the general population (N = 489, n = 246 women) aged 16+. Both the AQ and AWE had excellent internal consistency and were highly and equally predictive of autism in both women and men. Whilst there was a gender difference on the AQ among non-autistic people (men > women), there was no gender difference among autistic people, confirming all earlier studies. No gender differences were detected on the AWE overall scale, yet subtle gender differences were observed on the subscales. We conclude that the AQ is valid for both genders, but the AWE provides an additional useful perspective on the characteristics of autistic women. The AWE needs further validation in independent samples using techniques that allow for testing gender biases, as well as a confirmatory factor analysis in a larger sample.