Autism Identity and the “Lost Generation”: Structural Validation of the Autism Spectrum Identity Scale and Comparison of Diagnosed and Self-Diagnosed Adults on the Autism Spectrum

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McDonald, T. A. (2020). Autism Identity and the “Lost Generation”: Structural Validation of the Autism Spectrum Identity Scale and Comparison of Diagnosed and Self-Diagnosed Adults on the Autism Spectrum. Autism in Adulthood, 2(1), 13-23. https://doi.org/10.1089/aut.2019.0069

Publication date: 26 Feb 2020 Added to AutiHub: 5 Oct 2026 Type: Article Article language: English
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Authors

Publication authors
1
Publication authors identified as autistic
1 / 1 (100.0%)
  1. T. A. McDonald *

Abstract

Background: A population segment of autistic adults are underidentified due, in part, to historic changes in criteria for diagnosing autism and diagnostic biases related to gender, socioeconomic status, and other individual characteristics such as intellectual functioning. Some of these individuals, described as the “lost generation,” may choose to self-diagnose. Although little is known about this population, it is possible that they share similar self-conceptualizations or internalized stigma as their diagnosed counterparts. This study reports on the structural validity of the Autism Spectrum Identity Scale (ASIS) with individuals diagnosed and self-diagnosed with autism and compares the demographic characteristics, stigma, self-concept, and quality of life of these two groups. Methods: Over 1000 adults diagnosed (n = 893) or self-diagnosed (n = 245) with autism were recruited through organizations serving the autism community to participate in a nationally distributed online survey that included demographic questions and measures for stigma, self-concept, quality of life, and well-being. The diagnosed data set was randomly split with exploratory factor analysis performed on a training data set. Split-half cross-validation was used to predict the factor structure of the holdout data set. Then, the full diagnosed data set structure was used to determine the generalizability of the factor structure to the self-diagnosed data set. The diagnosed and self-diagnosed were also compared for differences in gender, age, employment status, diagnostic term preference, and factors of self-concept (autism identity and self-esteem), stigma, and quality of life. Results: Factor analysis of diagnosed participants yielded a four-factor structure, consistent with previous research, with strong split-sample cross-validation and good internal consistency. Factor predictions of the self-diagnosed data set from the diagnosed data set ranged from 0.97 to 1.00 with similar internal consistency. Self-diagnosed participants were more likely to be older, women, or employed and less likely to be students or prefer the term “autism” than those with an autism diagnosis. The groups were remarkably similar in reported stigma, self-esteem, quality of life, and in ASIS factors; both groups reported lower quality of life than the general population. Conclusions: The ASIS demonstrated the same internal structure with both the diagnosed and self-diagnosed samples. The profile of self-diagnosed participants matches the profile hypothesized for the “lost generation” and others at risk of being underidentified for autism. Both populations appear to be similarly struggling with employment, stigma, and quality of life. Future research should examine whether self-diagnosed individuals meet criteria for autism or could benefit from interventions, programs, or services serving autism communities.

Bibliography cited by this reference

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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: 17 Oct 2026 01:10.

Cited references
38
With a DOI
27
Without a DOI, from raw bibliography text
10
2 / 38 (5.3%) cited references include at least one author identified as autistic.
References with data to complete
6 / 38 (15.8%)
References with detected author names
33 / 38 (86.8%)
Without detected author names
5
Without a structured title
6
Without a stable identifier
10
References with raw author names still to review
5
References with external metadata lookup issues
0
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
169
From DOI or external metadata
169
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
5
39 / 169 (23.1%) names are linked to an author already present in AutiHub. 130 / 169 (76.9%) names are not yet linked.
Names linked to a person identified as autistic
3 / 169 (1.8%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 3 / 39 (7.7%). Distinct people identified as autistic: 3 / 144 (2.1%).
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