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Gepubliceerd in: Journal of Autism and Developmental Disorders 10/2022

20-10-2021 | Original Paper

A Mixed-Methods Investigation of Diagnostician Sex/Gender-Bias and Challenges in Assessing Females for Autism Spectrum Disorder

Auteurs: Joanna M. Tsirgiotis, Robyn L. Young, Nathan Weber

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 10/2022

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Abstract

Despite the importance of clinical judgement in autism spectrum disorder (ASD) assessment, little is currently known about challenges faced by diagnosticians when the client is female, any sex/gender biases during the assessment process, and how these issues affect diagnostic outcomes. Forty-seven ASD diagnosticians completed a questionnaire containing two hypothetical case studies (a ‘male’ and ‘female’ ASD presentation), with sex/gender randomly assigned within each. Diagnosticians reported greater ASD symptom severity when female sex/gender pseudonyms were allocated to the case studies, but their confidence in ASD diagnosis was similar regardless of condition. Diagnosticians identified a large number of challenges associated with assessing females for ASD. Many of these related to sex/gender differences in ASD presentation and limitations of diagnostic instruments.
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Voetnoten
1
Sex refers to biological characteristics differentiating males and females and gender to socially constructed roles and attributes viewed as normative for a particular sex (American Psychiatric Association, 2011). Gendered socialisation begins at birth and resultantly, biological sex and socialised gender are not easily separated, mutually informing an individual’s identity. Therefore, as proposed by Springer et al. (2011) and recommended by Lai et al. (2015), the term sex/gender will be used to reflect the overlap between both constructs (unless otherwise stated).
 
2
Supplied as supplementary material.
 
3
Only the child’s pseudonym, gendered pronouns and names of friends were altered across conditions. Gender neutral interests were selected.
 
4
The precise nature of the regression differed depending on the outcome variable. The probability that a criterion was met (categorical) was modelled using conditional logistic regression with the relevant probabilities estimated from a linear combination of the predictors via a logit link. The remaining dependent variables were numerical and, therefore, modelled as normally distributed and estimated as a linear combination of the predictors via an identity link function.
 
5
Descriptive statistics are supplied as supplementary material.
 
6
There was some evidence that overall, and in some criteria in particular, criteria were more likely to be considered met for female sex/gender conditions. Due to the categorical treatment of the probability that criteria were met, there was considerable uncertainty surrounding this effect.
 
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Metagegevens
Titel
A Mixed-Methods Investigation of Diagnostician Sex/Gender-Bias and Challenges in Assessing Females for Autism Spectrum Disorder
Auteurs
Joanna M. Tsirgiotis
Robyn L. Young
Nathan Weber
Publicatiedatum
20-10-2021
Uitgeverij
Springer US
Gepubliceerd in
Journal of Autism and Developmental Disorders / Uitgave 10/2022
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI
https://doi.org/10.1007/s10803-021-05300-5

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