Profiling Autism Symptomatology: An Exploration of the Q-ASC Parental Report Scale in Capturing Sex Differences in Autism

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Simcoe, S. M., Brownlow, C., Garnett, M. S., Rynkiewicz, A., & Attwood, T. (2017). Profiling Autism Symptomatology: An Exploration of the Q-ASC Parental Report Scale in Capturing Sex Differences in Autism. Journal of Autism and Developmental Disorders, 48(2), 389-403. https://doi.org/10.1007/s10803-017-3324-9

Publication date: 20 Oct 2017 Added to AutiHub: 7 Sep 2026 Type: Article Article language: English
Publisher source (DOI) OpenAlex source

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Authors

Publication authors
5
Publication authors identified as autistic
2 / 5 (40.0%)
  1. Sarah Mae Simcoe
  2. Charlotte Brownlow
  3. Michelle Sarah Garnett *
  4. Agnieszka Rynkiewicz
  5. Tony Attwood *

Abstract

The Questionnaire for Autism Spectrum Conditions (Q-ASC) was developed by Attwood et al. (2011) to identify gender-sensitive profiles of autism symptomatology; prioritise and adjust the direction of clinical interventions; and support positive psychosocial outcomes and prognosis into adulthood. The current research piloted the Q-ASC with parents of 238 children with a clinical diagnosis of ASD-Level 1 (without intellectual or language impairment). Data analysis revealed eight interpretable and reliable components of the Q-ASC using Principle components analysis. Comparisons across age and gender groups found statistically significant mean differences of parent-reported characteristics. The findings from this study aim to identify improvements in the Q-ASC towards the future assessment of the sensitivity and diversity of presentations of autism among female children and adolescents.

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 12 Sep 2026 01:04.

Cited references
71
With a DOI
52
Without a DOI, from raw bibliography text
14
6 / 71 (8.5%) cited references include at least one author identified as autistic.
References with data to complete
8 / 71 (11.3%)
References with detected author names
68 / 71 (95.8%)
Without detected author names
3
Without a structured title
8
Without a stable identifier
13
References with raw author names still to review
3
References with external metadata lookup issues
2
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
201
From DOI or external metadata
201
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
6
60 / 201 (29.9%) names are linked to an author already present in AutiHub. 141 / 201 (70.1%) names are not yet linked.
Names linked to a person identified as autistic
7 / 201 (3.5%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 7 / 60 (11.7%). Distinct people identified as autistic: 4 / 175 (2.3%).
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