Evidence map›Paper›PMID 41898058›Full record

ReviewBehavioral sciences (Basel, Switzerland)2026

Expanding Understanding of Autism Spectrum Disorder in Girls and Women: A New Paradigm.

Dylan Rose Bitensky, Caroline S Clauss-Ehlers, Kyle M Veksler

Abstract readReview
In one paragraph

Review in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dylan Rose BitenskyDepartment of Psychology, School of Health Professions, Long Island University Brooklyn, Brooklyn, NY 11201, USA.
Caroline S Clauss-EhlersDepartment of Psychology, School of Health Professions, Long Island University Brooklyn, Brooklyn, NY 11201, USA.
Kyle M VekslerDepartment of Psychology, School of Health Professions, Long Island University Brooklyn, Brooklyn, NY 11201, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The definition of Autism Spectrum Disorder (ASD) has evolved since the diagnosis was first conceptualized. However, past and current understandings of ASD have largely been shaped by research focused on individuals assigned male at birth. This has influenced current diagnostic criteria, which often fail to capture female presentations and likely contribute to lower reported prevalence rates in girls. Recognizing female-specific presentations is critical to reducing misdiagnosis and underdiagnosis; therefore, this paper reviews research on how the DSM-5-TR two-factor model applies to girls. We then describe how female presentations of ASD are characterized by distinct cognitive profiles and frequent use of camouflaging to mask typical ASD symptoms, particularly social difficulties, which can obscure clinical presentation and delay diagnosis. Subsequently, we evaluate how current assessments and accommodations may fail to address the needs of females. Clauss-Ehlers introduces the Multimodal Autism Assessment for Girls and Women, which emphasizes the importance of assessing girls within an appropriate contextual lens. Finally, the paper calls for a gender-focused neurodiversity paradigm that highlights differences in presentation, promotes an approach focused on strength-based interventions, and outlines directions for future research and clinical implications based on this framework.

Indexed as

autism spectrum disorderfemale autism phenotypeMultimodal Autism Assessment for Girls and Women (MAAGW)neurodiversity paradigmsex-differences

Identifiers

PMID41898058
PMCPMC13024071

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.