Variability and stability of autistic traits in the general population: A systematic comparison between online and in-lab samples
Creators
Abstract
The surge of online psychological assessments have brought the autism research community both opportunities and challenges: while they enable rapid large-scale data collection and more power to characterize individual differences, they also bring concerns about data quality, generalizability beyond online samples, and whether autistic traits can be reliably characterized with self-report measures administered online. Here we tackle these concerns by providing a systematic characterization of the autistic traits variability across individuals in a large cross-sectional dataset (N = 2826) as well as its temporal reliability within individuals in a test-retest dataset (N = 247), with both online and in-lab samples. We measured autistic traits using the Social Responsiveness Scale, 2nd version, Adult Self Report (SRS-2-ASR) – a tool that quantifies individual differences in autistic traits along a continuum for the general adult population. Across individuals, we found elevated SRS scores in online samples and were able to trace this effect to specific subsets of SRS items. SRS scores also covaried with internalizing symptoms, decreased with age, and were lower in women compared to other genders. Within individuals, we find moderate-to-good test-retest reliability of SRS scores over long intervals, with no difference between online and in-lab samples, suggesting robust temporal stability. We conclude that there are systematic differences in autistic traits between online and in-lab samples that are partly explained by systematic population-level differences in internalizing symptoms, particularly social anxiety. Future studies that sample across different populations should measure, control for, or stratify with respect to these factors.
Copyright and License
© The Author(s), 2025. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Acknowledgement
We would like to thank John O’Doherty for sharing some of the data, and Sarah Oh and Julia Simon for part of the data curation.
Funding
This work was supported by the National Institute of Mental Health (CJC, grant number R00 MH123669), and Simons Foundation Autism Research Initiative (SFARI; QW, NK and RA, grant number 990500). QH was funded by a grant from the Simons Foundation (AN-SURFiN-00003522, Adolphs).
Contributions
Conceptualization: CJC, QW, LKP, RA, NK; Data Curation: QW, LKP, CJC, NK, QH; Formal Analysis: CJC, QW, QH; Funding acquisition: RA; Writing (original draft): QW, CJC; Writing (review & editing): QW, CJC, RA, NK, LKP, QH.
Data Availability
De-identified data and code are available at: https://github.com/wuqy052/SRS_variability_stability
Supplemental Material
Supplementary material (DOCX)
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Additional details
Identifiers
- PMID
- 41089295
- PMCID
- PMC12516608
Related works
- Describes
- Journal Article: 41089295 (PMID)
- Journal Article: PMC12516608 (PMCID)
- Is supplemented by
- Dataset: https://github.com/wuqy052/SRS_variability_stability (URL)
Funding
- National Institute of Mental Health
- R00 MH123669
- Simons Foundation
- Autism Research Initiative 990500
- Simons Foundation
- AN-SURFiN-00003522
Dates
- Accepted
- 
      2025-08-06