The Invisible Spectrum: Gender Disparities in Autism Diagnosis and the Underrecognition of Autistic Girls and Women

Introduction: Autism Spectrum Disorder (ASD) is a relevant neurodevelopmental condition, whose understanding has historically been centered on the male profile, contributing to the invisibility of girls and women in the diagnostic and support systems. Objectives: This review investigates the factors that contribute to the invisibility of autistic girls and women, highlighting gender disparities in the diagnosis of autism and the clinical and social impacts of social camouflage, especially in cases of late or absent diagnosis. Methods: This integrative literature review (2020–2025), based on studies from PubMed, Scopus and Web of Science databases, investigated gender disparities in the diagnosis of autism, focusing on social camouflage and its clinical impacts. Results: The findings indicate that the real ratio between autistic men and women may be lower than the traditional one (4:1), with estimates between 2–3:1 or even 1:1. Approximately 50% of the studies analyzed reported significant underdiagnosis in girls, with diagnosis often being delayed. Social camouflage strategies, more common in autistic women, hinder clinical identification and are associated with a higher risk of mental disorders. Conclusions: It is concluded that underreporting of autism in women is a public health problem, requiring a review of diagnostic criteria with gender sensitivity, adequate professional training and centrality of female experiences in clinical practices and research.

Authors

Publication Details

Journal
COGNITIONIS Scientific Journal
Published
2025-09-09
DOI
https://doi.org/10.38087/2595.8801.670
Primary Topic
Autism Spectrum Disorder Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Invisible Spectrum: Gender Disparities in Autism Diagnosis and the Underrecognition of Autistic Girls and Women

Antônio Cezar de Castro Lima, Francis Moreira da Silveira, Nara Moraes Guimarães
1 links
COGNITIONIS Scientific Journal
Autism Spectrum Disorder Research
article

The Invisible Spectrum: Gender Disparities in Autism Diagnosis and the Underrecognition of Autistic Girls and Women

Antônio Cezar de Castro Lima, Francis Moreira da Silveira, Nara Moraes Guimarães
article en

Abstract

Introduction: Autism Spectrum Disorder (ASD) is a relevant neurodevelopmental condition, whose understanding has historically been centered on the male profile, contributing to the invisibility of girls and women in the diagnostic and support systems. Objectives: This review investigates the factors that contribute to the invisibility of autistic girls and women, highlighting gender disparities in the diagnosis of autism and the clinical and social impacts of social camouflage, especially in cases of late or absent diagnosis. Methods: This integrative literature review (2020–2025), based on studies from PubMed, Scopus and Web of Science databases, investigated gender disparities in the diagnosis of autism, focusing on social camouflage and its clinical impacts. Results: The findings indicate that the real ratio between autistic men and women may be lower than the traditional one (4:1), with estimates between 2–3:1 or even 1:1. Approximately 50% of the studies analyzed reported significant underdiagnosis in girls, with diagnosis often being delayed. Social camouflage strategies, more common in autistic women, hinder clinical identification and are associated with a higher risk of mental disorders. Conclusions: It is concluded that underreporting of autism in women is a public health problem, requiring a review of diagnostic criteria with gender sensitivity, adequate professional training and centrality of female experiences in clinical practices and research.

COGNITIONIS Scientific JournalVol. 8(2)
Openalex Percentile: Top 76%
Autism Spectrum Disorder Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.