Skip to main content
Frontiers in Psychiatry logoLink to Frontiers in Psychiatry
. 2026 Jan 5;16:1704579. doi: 10.3389/fpsyt.2025.1704579

Female gender and autism: underdiagnosis and misdiagnosis – clinical and scientific urgency

Roberta Minutoli 1,2, Chiara Marraffa 1,3, Chiara Failla 1,*, Giovanni Pioggia 1, Flavia Marino 1
PMCID: PMC12812640  PMID: 41561981

Introduction

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by difficulties in communication and social interaction, along with restricted interests and repetitive behaviors. Symptom expression is highly heterogeneous, encompassing a wide range of functional impairments and levels of severity (1, 2). Epidemiological data indicate a higher prevalence of ASD among males than females. Some studies suggest that this apparent gender disparity is largely attributable to underdiagnosis and/or misdiagnosis in females, rather than a true lower incidence of the condition (3, 4). Population-based screening studies have estimated a true prevalence ratio of approximately 3.25 males for every female (5), and population-based predictive models suggest that up to 39% more girls could be expected to be diagnosed with ASD than are currently identified (6). Research indicates that cognitively competent females with ASD tend to be diagnosed significantly later than their male peers, despite similar levels of parental concern and a comparable number of professional referrals (7, 8). Females are more likely to receive subthreshold or alternative diagnoses, such as pervasive developmental disorder not otherwise specified or social communication disorder, rather than a full diagnosis of ASD (9, 10). Several studies have reported that females must exhibit greater intellectual or behavioral difficulties (11), emotional difficulties (12), or more pronounced ASD features (13) than males to receive a diagnosis, while parent-reported repetitive or restricted behaviors tend to lead to ASD diagnoses more frequently in males (12). Historically, the conceptualization and nosology of ASD have been shaped by predominantly male clinical samples (14, 15). The term “female” is primarily used to refer to people assigned female at birth (AFAB). However, we recognize that gender identity is distinct from biological sex, and that some transgender or non-binary individuals may share characteristics of the female autistic phenotype. Therefore, when we discuss autistic women and girls, we intend to include both AFAB individuals and people who identify as female, acknowledging the variability of experience and identity. Consequently, current diagnostic criteria and assessment tools are largely based on a male-centered understanding of autism, potentially overlooking the distinctive features of a female autistic phenotype (FAP). If such a sex/gender-specific phenotype exists, current diagnostic frameworks may fail to adequately capture it (16, 17), resulting in many autistic women remaining under the diagnostic radar. Clinical observations and autobiographical accounts further suggest that many girls and women on the autism spectrum engage in camouflaging or masking behaviors – compensatory social strategies aimed at hiding autistic traits – such as deliberately adapting facial expressions or tone of voice to conform to social norms, often practicing these behaviors in front of a mirror (18). These early-learned adaptive behaviors make autistic traits less recognizable to professionals and contribute to delayed or missed diagnoses (19, 37). However, the effort required to maintain such camouflaging often comes at a considerable emotional and psychological cost, increasing vulnerability to anxiety, depression, and burnout among autistic women (18). Taken together, these findings underscore the need to more clearly define and operationalize a Female Autism Phenotype (FAP). Future work should compare and adapt existing diagnostic instruments by integrating gender-sensitive probes and explicit measures of camouflaging. A coordinated research and clinical roadmap—with short-, medium-, and long-term objectives—will be essential to improving the identification, diagnosis, and support of autistic women across the lifespan. In this our opinion paper, we translate “camouflaging” as “masking,” meaning the set of behavioral and cognitive strategies that autistic people use to adapt to social norms and hide autistic traits. “Camouflaging” is considered a subcategory of masking, specifically referring to the imitation or reproduction of social behaviors observed in others, without altering internal experience.

Female autism: a different phenotype

We can distinguish two main perspectives on female autism can be distinguished. On one side, the FAP is conceptualized as a relatively stable set of clinical characteristics, including patterns of interests that appear socially acceptable, relational styles that are superficially coherent, and internalized repetitive behaviors, which differ in frequency or manifestation from those typically observed in males (21). Qualitative studies have shown that these features contribute to delayed diagnosis in women (21). On the other side, the camouflaging perspective interprets many observed aspects in females as the result of adaptive processes and compensatory strategies—such as masking, scripting, and imitation—implemented to reduce the visibility of autistic traits (22). Quantitative research, for example using the CAT-Q, indicates that females with autism score higher on overall camouflaging compared to males (22, 37). These perspectives are not mutually exclusive: an integrated view suggests that FAP encompasses both genuine phenotypic differences and outcomes of camouflaging processes that alter the clinical presentation. Accordingly, research and clinical practice should simultaneously assess observable features (interest patterns, relational and repetitive behaviors) and subjective compensatory processes (masking, scripting, social exhaustion). For instance, a woman may display socially acceptable interests while relying on pre-learned scripts for peer interactions, reflecting both FAP and camouflaging. This integration highlights that delayed diagnoses and misattribution of comorbidities in women may result not only from different phenotypic expressions but also from camouflaging mechanisms that obscure the detection of autism (23, 24). Diagnostic criteria for ASD are primarily based on male samples, which contributes to missed or delayed diagnoses in females (see Table 1). The FAP is characterized by features that diverge from typical male presentations, particularly in the social-relational domain, demonstrating interests and social skills that are perceived by others as socially appropriate and well-developed (2326). During initial social exposure, neurodivergent girls and women are often labeled as shy or reserved due to their more withdrawn behavior. Many women with FAP demonstrate advanced skills in some forms of nonverbal communication, such as gestures or facial expressions, which may mask autistic traits. However, some challenges persist in social interaction, such as interpreting sarcasm, metaphors, or implicit intentions, which depend more on contextual understanding than on basic nonverbal skills. Separating these domains helps clarify which difficulties are genuine phenomena of the female phenotype and which reflect compensatory or masking strategies. One distinctive feature of FAP is an enhanced capacity for observation, which manifests as a tendency to internalize social rules before actively engaging in interactions, despite frequent experiences of loneliness and frustration in forming and maintaining friendships (27, 28). In this context, camouflaging becomes a central aspect of FAP, characterized by the voluntary implementation of emotional and behavioral strategies to align with social expectations, thereby masking core autistic traits (29, 30). Camouflaging has several implications for psychological well-being, often resulting in emotional crises, psychosomatic symptoms (31), loss of spontaneity, identity confusion, chronic fatigue, and an increased risk of anxiety and depression (32, 33).

Table 1.

Diagnostic tools: gender biases, supporting evidence, and proposed adaptations.

Diagnostic tool Gender bias/limitation Recent evidence Proposed adaptation or alternative
ADOS-2 (Autism Diagnostic Observation Schedule) Items largely derived from male samples; reduced sensitivity to camouflaging and subtle social reciprocity in females lower sensitivity for female participants (41) Add clinical probes for compensatory strategies and social tone; complement with self-report tools such as CAT-Q
ADI-R (Autism Diagnostic Interview – Revised) Emphasis on early observable behaviors; limited assessment of relational development bias toward externalized symptoms (29) Incorporate qualitative parental narratives and contextual developmental histories
RAADS-R (Ritvo Autism Asperger Diagnostic Scale – Revised) Focus on “atypical” interests and overt repetitive behaviors possible under-identification in females (20) Revise items to include socially normative but restricted interests (e.g., animals, fashion, relationships)
CAT-Q (Camouflaging Autistic Traits Questionnaire) New measure; focuses on internal compensatory processes validated self-report for camouflaging (22) Systematically include in adult diagnostic protocols as complementary assessment
GQ-ASC (Gender Quotient Autism Spectrum Checklist) Specifically designed for gender-sensitive autism screening initial validation studies (42) Encourage cross-cultural validation and integration in clinical practice

Diagnostic biases and current instrument limitations

Standard diagnostic tools, such as the Autism Diagnostic Observation Schedule – Second Edition (ADOS-2) (34) and the Autism Diagnostic Interview-Revised (ADI-R) (15), may have reduced sensitivity for identifying autism in females. Women with autism spectrum disorder (ASD) often exhibit internalizing, restricted, or repetitive behaviors, or employ compensatory strategies such as masking, social scripting, and mimicry, which are less frequently captured by standard items (2123, 35). Measurement invariance studies reveal sex-related differences in item factor loadings across several ADOS-2 modules, suggesting that some items perform differently for women and that targeted probes or item revisions may be necessary (23, 36). Moreover, camouflage strategies can lead to under-identification or delayed diagnosis in girls, particularly when behaviors appear culturally acceptable, such as restricted interests in animals, dolls, or singers, or when social difficulties are attributed to shyness or anxiety rather than neurodivergence (3, 4, 37). Many female-specific autistic manifestations are subtle or internalized, with nonverbal communication often being the most affected component, including rigid postures, difficulty interpreting sarcasm, or challenges understanding metaphors. Test administration may be further complicated by literal interpretations or narrow responses, as observed in measures such as the RAADS-R, requiring contextual examples for accurate assessment (38). During adolescence, emotional dysregulation or cognitive inflexibility may be misclassified within other diagnostic frameworks, leading to frequent secondary diagnoses of mood disorders, feeding and eating disorders, or ADHD (19). Discrepancies between caregiver reports and specialist observations are often greater for girls than for boys, with observational instruments underestimating symptom severity and delaying diagnosis and intervention (39). To address these limitations, practical countermeasures include (1) systematic integration of camouflage measures, such as the Camouflaging Autistic Traits Questionnaire (CAT-Q), into the diagnostic process (22); (2) the use of multiple informants and ecological observations to capture subtle or context-dependent behaviors (21); and (3) revision of ADOS-2 and ADI-R items with analyses of measurement invariance across sex, including probes specifically aimed at identifying camouflaging strategies (36, 40) (see Table 1). Implementing these strategies may reduce male-biased detection and better account for female phenotypic expressions and compensatory adaptations, ultimately improving diagnostic accuracy.

Sociocultural determinants and psychological consequences of diagnostic delay in autistic women

Sociocultural factors play a crucial role in shaping the perception of female behavior and in influencing the recognition of neurodivergent signals. Parents, teachers, and pediatricians often hold gendered expectations—assuming that girls are naturally more relational and adaptable—which can normalize or minimize atypical behaviors, attributing them to personality traits or sensitivity rather than neurodevelopmental differences (21, 22, 43). Consequently, autistic girls often remain “invisible” within educational settings, delaying referral and diagnosis (29). Many develop early compensatory strategies, masking social difficulties through learned behaviors that demand sustained cognitive and emotional effort (22). Such camouflaging allows temporary social adaptation but comes at the cost of significant psychological strain. Supportive family contexts or small, familiar environments can further postpone the emergence of overt difficulties until adolescence or adulthood, when complex social demands—such as those encountered in university or the workplace—reveal underlying vulnerabilities (44). This prolonged mismatch between external expectations and internal experience often produces emotional exhaustion, dissociation, and psychosomatic symptoms (21, 22). The discrepancy between public functioning and private suffering fosters a loss of authenticity and self-awareness, frequently compounded by bullying, exclusion, and gendered pressures to conform (29, 43). Over time, this cycle contributes to perfectionism, rigid routines, and heightened risk for internalizing disorders such as anxiety, depression, and eating disorders (23, 24, 44). Many women continue to camouflage effectively into adulthood, with compensatory abilities often declining around menopause, when diagnosis is finally obtained after decades of misrecognition (21, 22) (see Table 2). Recognizing how sociocultural mechanisms interact with psychological adaptation is therefore essential for clinicians: interventions must address both the systemic biases that delay diagnosis and the internalized coping strategies that, while adaptive, contribute to emotional distress and identity fragmentation (22, 23).

Table 2.

Camouflaging: forms, functions, and clinical implications.

Type of camouflaging Clinical Examples Adaptive function Clinical consequences
Behavioral Mimicking gestures or tone of voice Avoid social rejection Chronic fatigue, burnout, reduced social spontaneity, increased risk of stress-related illnesses (22, 23)
Cognitive Prepared scripts, post-event analysis Control of social interactions Social anxiety, rumination, impaired decision-making, difficulty engaging in spontaneous conversation (22, 24)
Emotional Suppression of authentic emotions Reduce social dissonance Depression, feelings of alienation, emotional numbness, difficulty forming genuine connections (22, 43)
Identity-related Creation of “socially false selves” Apparent social integration Dissociation, loss of authenticity, identity confusion, vulnerability to long-term self-esteem issues (24, 44)

Discussion

Early and accurate diagnosis of autism in women remains one of the most complex challenges in contemporary clinical practice. A consistent body of research indicates that standard diagnostic instruments—largely developed and validated on male samples—tend to underestimate or misinterpret the presentation of autism in females (2123). It is worth noting that the female autistic phenotype often becomes visible only in specific transitional contexts, such as adolescence, university life, or motherhood—stages that current diagnostic protocols capture only partially (29, 44). In these contexts, compensatory mechanisms, particularly camouflaging, play a paradoxical role: they facilitate short-term adaptation to social norms but generate significant cognitive and emotional strain in the long run (22, 24). Camouflaging can manifest in several interrelated forms—behavioral, cognitive, emotional, and identity-related—each with its own adaptive purpose and potential clinical cost. Cognitive forms, including pre-rehearsed scripts or post-interaction analyses, may enhance social control while fueling anxiety and rumination (22, 43). Emotional masking often involves suppressing authentic affect to maintain social harmony, which may result in emotional numbness or depressive symptoms. Finally, identity-related masking—what some women describe as “performing a socially acceptable self”—can erode authenticity and foster dissociative experiences over time (24, 44). Thus, camouflaging can be understood as both a creative coping strategy and a psychological vulnerability, illustrating the tension between social inclusion and self-coherence. The question is not only what is observed, but also how and through which expectations observations are made. Despite recent proposals for incremental adaptations to screening tools, many approaches still rely on male-centered paradigms that fail to reflect the diversity of female neurodevelopment (36, 40). A more gender-sensitive and developmental approach is required, combining standardized tools such as the CAT-Q and GQ-ASC with multi-informant and ecological assessments (21, 22). Improving diagnostic accuracy also depends on rethinking professional training. Clinicians would benefit from structured, interdisciplinary curricula that integrate clinical neuroscience with gender studies and the sociology of neurodiversity. Such programs could help dismantle persistent stereotypes and increase sensitivity to the nuanced presentation of autism in women. A feasible pathway could follow three interconnected phases:

  • Short term: integrate gender-sensitive self-report tools (e.g., CAT-Q, GQ-ASC), introduce explicit masking probes in ADOS/ADI-R assessments, and organize workshops to enhance clinicians’ awareness of female-specific features.

  • Medium term: conduct systematic validation studies on measurement invariance, develop standardized gender-based training programs, and establish interdisciplinary research networks to consolidate empirical knowledge.

  • Long term: promote structural reform by updating diagnostic guidelines, embedding gender-inclusive modules into medical and psychological training, and developing AI-based aids calibrated for sex- and gender-related variability.

Finally, it is crucial that autistic women participate as co-researchers and consultants in this diagnostic innovation process. Their lived experience provides insights that can bridge the gap between scientific models and real-world presentation, ultimately fostering more timely, accurate, and humane assessments.

Funding Statement

The author(s) declared that financial support was received for this work and/or its publication. AREA - Assistenza e Riabilitazione attraverso modelli d’intervento Evolutivo comportamentali per l’Autismo ASP – Trapani N. 20190003196 DEL 10/12/2019.

Footnotes

Edited by: Rita Barone, University of Catania, Italy

Reviewed by: Kate Seers, Charles Sturt University, Australia

Emily Cary, The Ohio State University, United States

Author contributions

RM: Conceptualization, Methodology, Writing – original draft, Writing – review & editing. CM: Conceptualization, Methodology, Writing – original draft. CF: Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing. GP: Funding acquisition, Project administration, Writing – original draft, Writing – review & editing. FM: Conceptualization, Funding acquisition, Project administration, Supervision, Writing – original draft, Writing – review & editing.

Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

  • 1. American Psychiatric Association . Diagnostic and statistical manual of mental disorders. 5th ed. Washington (DC: American Psychiatric Publishing; (2022). [Google Scholar]
  • 2. World Health Organization . International statistical classification of diseases and related health problems. 11th ed. Geneva: World Health Organization; (2019). [Google Scholar]
  • 3. Young H, Oreve MJ, Speranza M. Clinical characteristics and problems diagnosing autism spectrum disorder in girls. Arch Pediatr. (2018) 25:399–403. doi:  10.1016/j.arcped.2018.06.008, PMID: [DOI] [PubMed] [Google Scholar]
  • 4. Hodge MA, Sutherland R, Boulton KA, Baracz SJ, Ong N, Bennett B, et al. Focusing on autism symptoms masks sex-specific needs of autistic children: an example from the Sydney Child Neurodevelopment Research Registry. Autism. (2025) 29:1318–32. doi:  10.1177/13623613241303550, PMID: [DOI] [PubMed] [Google Scholar]
  • 5. Loomes R, Hull L, Mandy W. What is the male-to-female ratio in autism spectrum disorder? A systematic meta-analysis. J Am Acad Child Adolesc Psychiatry. (2017) 56:466–74. doi:  10.1016/j.jaac.2017.03.013, PMID: [DOI] [PubMed] [Google Scholar]
  • 6. Barnard-Brak L, Richman D, Almekdash MH. How many girls are we missing in ASD? An examination from a clinic- and community-based sample. Adv Autism. (2019) 5:214–24. doi:  10.1108/AIA-11-2018-0048 [DOI] [Google Scholar]
  • 7. Siklos S, Kerns KA. Assessing the diagnostic experiences of a small sample of parents of children with autism spectrum disorders. Res Dev Disabil. (2007) 28:9–22. doi:  10.1016/j.ridd.2005.09.003, PMID: [DOI] [PubMed] [Google Scholar]
  • 8. Begeer S, Mandell D, Wijnker-Holmes B, Venderbosch S, Rem D, Stekelenburg F, et al. Sex differences in the timing of identification among children and adults with autism spectrum disorders. J Autism Dev Disord. (2013) 43:1151–6. doi:  10.1007/s10803-012-1656-z, PMID: [DOI] [PubMed] [Google Scholar]
  • 9. Wilson CE, Murphy CM, McAlonan G, Robertson DM, Spain D, Hayward H, et al. Does sex influence the diagnostic evaluation of autism spectrum disorder in adults? Autism. (2016) 20:808–19. doi:  10.1177/1362361315611381, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Ratto AB, Kenworthy L, Yerys BE, Bascome J, Trubanova Wieckowski A, White SW, et al. What about the girls? Sex-based differences in autistic traits and adaptive skills. J Autism Dev Disord. (2018) 48(5):1698–711. doi:  10.1007/s10803-017-3413-9, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Dworzynski K, Ronald A, Bolton P, Happé F. How different are girls and boys above and below the diagnostic threshold for autism spectrum disorders? J Am Acad Child Adolesc Psychiatry. (2012) 51:788–97. doi:  10.1016/j.jaac.2012.05.018, PMID: [DOI] [PubMed] [Google Scholar]
  • 12. Duvekot J, van der Ende J, Verhulst FC, Sleppendel G, van Daalen E, Maras A, et al. Factors influencing the probability of a diagnosis of autism spectrum disorder in girls versus boys. Autism. (2016) 21(6):646–58. doi:  10.1177/1362361316672178, PMID: [DOI] [PubMed] [Google Scholar]
  • 13. Russell G, Steer C, Golding J. Social and demographic factors that influence the diagnosis of autistic spectrum disorders. Soc Psychiatry Psychiatr Epidemiol. (2011) 46:1283–93. doi:  10.1007/s00127-010-0294-z, PMID: [DOI] [PubMed] [Google Scholar]
  • 14. Kreiser NL, White SW. ASD in females: Are we overstating the gender difference in diagnosis? Clin Child Family psychol Rev. (2014) 17:67–84. doi:  10.1007/s10567-013-0148-9, PMID: [DOI] [PubMed] [Google Scholar]
  • 15. Rutter M, LeCouteur A, Lord C. The autism diagnostic interview-revised (ADI-R). Los Angeles: Western Psychological Services; (2003). [Google Scholar]
  • 16. Lai MC, Lombardo MV, Auyeung B, Chakrabarti B, Baron-Cohen S. Sex/gender differences and autism: Setting the scene for future research. J Am Acad Child Adolesc Psychiatry. (2015) 54:11–24. doi:  10.1016/j.jaac.2014.10.003, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. van Wijngaarden-Cremers PJM, van Eeten E, Groen WB, van Deurzen PA, Oosterling IJ, van der Gaag R. Gender and age differences in the core triad of impairments in autism spectrum disorders: A systematic review and metaanalysis. J Autism Dev Disord. (2014) 44:627–35. doi:  10.1007/s10803-013-1913-9, PMID: [DOI] [PubMed] [Google Scholar]
  • 18. Howe SJ, Hull L, Sedgewick F, Hannon B, McMorris CA. Understanding camouflaging and identity in autistic children and adolescents using photo-elicitation. Res Autism Spectr Disord. (2023) 108:102232. doi:  10.1016/j.rasd.2023.102232 [DOI] [Google Scholar]
  • 19. Rutherford M, McKenzie K, Johnson T, Catchpole C, O’Hare A, McClure I, et al. Gender ratio in a clinical population sample, age of diagnosis and duration of assessment in children and adults with autism spectrum disorder. Autism. (2016) 20:628–34. doi:  10.1177/1362361315617879, PMID: [DOI] [PubMed] [Google Scholar]
  • 20. Cook J, Hull L, Crane L, Mandy W. Camouflaging in autism: a systematic review. Clin Psychol Rev. (2021) 89:102080. doi:  10.1016/j.cpr.2021.102080, PMID: [DOI] [PubMed] [Google Scholar]
  • 21. Bargiela S, Steward R, Mandy W. The experiences of late-diagnosed women with autism spectrum conditions: An investigation of the female autism phenotype. J Autism Dev Disord. (2016) 46:3281–94. doi:  10.1007/s10803-016-2872-8, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Hull L, Mandy W, Lai M-C, Baron−Cohen S, Allison C, Smith P, et al. Development and validation of the camouflaging autistic traits questionnaire (CAT−Q). J Autism Dev Disord. (2019) 49:819–33. doi:  10.1007/s10803-018-3792-6, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Wood-Downie H, Wong B, Kovshoff H, Mandy W, Hull L, Hadwin JA. Sex/gender differences in camouflaging in children and adolescents with autism. J Autism Dev Disord. (2021) 51:1353–64. doi:  10.1007/s10803-020-04615-z, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Cassidy S, Bradley L, Shaw R, Baron-Cohen S. Risk markers for suicidality in autistic adults. Mol Autism. (2018) 9:42. doi:  10.1186/s13229-018-0226-4, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Rivet TT, Matson JL. Review of gender differences in core symptomatology in autism spectrum disorders. Res Autism Spectr Disord. (2011) 5:957–76. doi:  10.1016/j.rasd.2010.12.003 [DOI] [Google Scholar]
  • 26. McFayden TC, Antezana L, Albright J, Muskett A, Scarpa A. Sex differences in an autism spectrum disorder diagnosis: are restricted repetitive behaviors and interests the key? Rev J Autism Dev Disord. (2020) 7(2):119–26. doi:  10.1007/s40489-019-00183-W [DOI] [Google Scholar]
  • 27. Head AM, McGillivray JA, Stokes MA. Gender differences in emotionality and sociability in children with autism spectrum disorders. Mol Autism. (2014) 5:19. doi:  10.1186/2040-2392-5-19, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Hiller RM, Young RL, Weber N. Sex differences in autism spectrum disorder based on DSM-5 criteria: evidence from clinician and teacher reporting. J Abnorm Child Psychol. (2014) 42:1381–93. doi:  10.1007/s10802-014-9881-x, PMID: [DOI] [PubMed] [Google Scholar]
  • 29. Lai MC, Lombardo MV, Ruigrok AN, Chakrabarti B, Auyeung B, Szatmari P, et al. Quantifying and exploring camouflaging in men and women with autism. Autism. (2017) 21:690–702. doi:  10.1177/1362361316671012, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Alaghband-Rad J, Hajikarim-Hamedani A, Motamed M. Camouflage and masking behavior in adult autism. Front Psychiatry. (2023) 14:1108110. doi:  10.3389/fpsyt.2023.1108110, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Milner V, Mandy W, Happé F, Colvert E. Sex differences in predictors and outcomes of camouflaging: comparing diagnosed autistic, high autistic trait and low autistic trait young adults. Autism. (2023) 27:402–14. doi:  10.1177/13623613221098240, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Bernardin CJ, Lewis T, Bell D, Kanne S. Associations between social camouflaging and internalizing symptoms in autistic and non-autistic adolescents. Autism. (2021) 25(6):1580–91. doi:  10.1177/1362361321997284, PMID: [DOI] [PubMed] [Google Scholar]
  • 33. Ross A, Grove R, McAloon J. The relationship between camouflaging and mental health in autistic children and adolescents. Autism Res. (2023) 16:190–9. doi:  10.1002/aur.2859, PMID: [DOI] [PubMed] [Google Scholar]
  • 34. Lord C, Rutter M, DiLavore P, Risi S, Gotham K, Bishop SL. The autism diagnostic observation scale (ADOS). Los Angeles (CA): Western Psychological Services; (2002). [Google Scholar]
  • 35. Rynkiewicz A, Schuller B, Marchi E, Piana S, Camurri A, Lassalle A, et al. An investigation of the ‘female camouflage effect’in autism using a computerized ADOS-2 and a test of sex/gender differences. Mol Autism. (2016) 7:10. doi:  10.1186/s13229-016-0073-0, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Belcher HL, Uglik-Marucha N, Vitoratou S, Ford RM, Morein-Zamir S. Gender bias in autism screening: measurement invariance of different model frameworks of the Autism Spectrum Quotient. BJPsych Open. (2023) 9:e173. doi:  10.1192/bjo.2023.562, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Edwards H, Wright S, Sargeant C, Cortese S, Wood-Downie H. Research review: A systematic review and meta-analysis of sex differences in narrow constructs of restricted and repetitive behaviours and interests in autistic children, adolescents, and adults. J Child Psychol Psychiatry. (2024) 65:4–17. doi:  10.1111/jcpp.13855, PMID: [DOI] [PubMed] [Google Scholar]
  • 38. Ritvo RA, Ritvo ER, Guthrie D, Ritvo MJ, Hufnagel DH, McMahon W, et al. The Ritvo Autism Asperger Diagnostic Scale-Revised (RAADS-R): a scale to assist the diagnosis of autism spectrum disorder in adults: an international validation study. J Autism Dev Disord. (2011) 41:1076–89. doi:  10.1007/s10803-010-1133-5, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Azu MA, Han GT, Wolf JM, Naples AJ, Chawarska K, Dawson G, et al. Clinician–caregiver informant discrepancy is associated with sex, diagnosis age, and intervention use among autistic children. Autism. (2025) 29(3):614–26. doi:  10.1177/13623613241279999, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Sirgiotis JM. A different’different’: the female presentation of autism spectrum disorder and implications for detection and diagnosis. Adelaide (SA), Australia: Flinders University, College of Education, Psychology and Social Work; (2020). [Google Scholar]
  • 41. Rea HM, Øien RA, Shic F, Webb SJ, Ratto AB. Sex differences on the ADOS-2. J Autism Dev Disord (2022) 53(7):2878–90. doi:  10.1007/s10803-022-05566-3, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Brown CM, Attwood T, Garnett M, Stokes MA. Am I autistic? Utility of the girls questionnaire for autism spectrum condition as an autism assessment in adult women. Autism Res. (2020) 13:1390–402. doi:  10.1089/aut.2019.0054, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Mandy W. Social camouflaging in autism: Is it time to lose the mask? Autism. (2019) 23:1879–81. doi:  10.1177/1362361319878559, PMID: [DOI] [PubMed] [Google Scholar]
  • 44. Harrop C, Tomaszewski B, Putnam O, Klein C, Lamarche E, Klinger L. Are the diagnostic rates of autistic females increasing? An examination of state-wide trends. J Child Psychol Psychiatry. (2024) 65:973–83. doi:  10.1111/jcpp.13939, PMID: [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Frontiers in Psychiatry are provided here courtesy of Frontiers Media SA

RESOURCES