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Rethinking psychometric testing in autism: overcoming the challenges of comorbidity and diagnostic overshadowing

Published online by Cambridge University Press:  17 January 2025

Nihit Gupta
Affiliation:
Department of Child and Adolescent Psychiatry, Dayton Children’s Hospital, Dayton, OH, USA
Srinija Srinivasan
Affiliation:
Northwestern University, Chicago, IL, USA
Mayank Gupta*
Affiliation:
Southwood Children Behavioral Health, Pittsburgh, PA, USA
*
Corresponding author: Mayank Gupta; Email: mayank6nov@gmail.com
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Abstract

Epidemiological data indicates a rising prevalence of autism spectrum disorder (ASD) among eight-year-old children, with rates increasing from 1 in 44 to 1 in 36 between 2022 and 2023. This growing prevalence poses significant challenges in achieving accurate diagnoses, particularly due to comorbid conditions and diagnostic overshadowing. Certain subgroups—such as females with ASD, individuals with high cognitive abilities, and ethnic minorities—remain at heightened risk of underdiagnosis. Diagnostic tools like the Autism Diagnostic Observation Schedule (ADOS-2) have limitations, particularly in clinical settings where gender biases and cultural differences in symptom presentation can complicate accurate assessment. Moreover, rural areas face additional burdens due to limited access to care, further exacerbating diagnostic challenges. The review underscores the necessity for improved screening and diagnostic methods tailored to diverse populations, acknowledging the current limitations of existing tools. It also highlights significant barriers such as workforce shortages and lengthy wait times for evaluations. Emphasizing the importance of clinician education and targeted diagnostic approaches, the review calls for attention to cultural and gender differences in ASD evaluation.

Information

Type
Original Research
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. Search methodology.

Figure 1

Table 1. Comparison between Diagnostic and Screening Tools for ASD

Figure 2

Figure 2. How to ask narrow questions to screen for ASD in complex phenotypic presentation.

Figure 3

Table 2. A Symptom Checklist Based on Domains of Impairments in Individuals with ASD

Figure 4

Table 3. Effective Strategies for Incorporating Empirical Data Gaps into Clinical Practice and Decision-Making.