Employment profiles of autistic people: An 8-year longitudinal study
Open accessAbstract
Autistic adults experience high rates of unemployment, yet research investigating what predicts employment success produces inconsistent results. By utilising longitudinal person-oriented analyses, this study aimed to identify employment trajectories of autistic adults to better understand what may predict stable autistic employment. Participants were 2449 autistic adults (1077 men, 1352 women, 20 non-binary, M = 42.25 years, SD = 14.24), recruited via the Netherlands Autism Register. Latent class analysis utilising employment status across eight annual waves was used to identify longitudinal employment profiles. Fit indices and the interpretability of results indicated a four-class model best fit the data, with profiles reflecting stable unemployment ( n = 1189), stable employment ( n = 801), early unemployment increasing in probability of employment ( n = 183) and high probability of employment reducing across time to low employment ( n = 134). Multinominal analyses suggested that compared to the ‘stable unemployment’ group, membership in the ‘stable employment’ profile was predicted by fewer autistic traits, lower age, male gender, higher education and diagnosis age, and fewer co-occurring conditions. Higher education predicted both other profiles, with lower age and fewer co-occurring conditions predicting membership in the increasing employment class. Taken together, findings highlight the utility of person-oriented approaches in understanding the longitudinal challenges autistic adults experience maintaining employment and identifies key areas of support. Lay abstract: Autistic adults experience difficulties finding and keeping employment. However, research investigating reasons that might explain this difficulty produce mixed results. We gave a survey to 2449 autistic adults and used a statistic method to group them based on their employment status over 8 years. We identified four employment groups that best captured the experiences of autistic adults; this included a group that experienced stable unemployment, a group that experienced stable employment, a group that had high employment that reduced over time, and a group whose employment increased over the 8 years. Further analysis showed that those with fewer autistic traits, younger age, male gender, higher education, later diagnosis age and no co-occurring conditions were more likely to have stable employment. People whose employment changed over time were more likely to have a higher level of education than the stable unemployment group, and those in the increasing employment group were younger age and had no co-occurring conditions. These findings help us better understand that not all autistic adults’ experiences of employment are the same, which helps focus where employment programmes and support may be most needed, for example, people who identify as women or have a co-occurring condition.
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Among individuals diagnosed with autism spectrum disorders (ASD), as many as 60-80% are unemployed.
“The problem is even more pressing among individuals diagnosed with autism spectrum disorders (ASD), where as many as 60-80% are unemployed, which the UN Secretary-General directly refers to as enormous untapped potential [8, 9, 10, 11].”
Higher education is the strongest indicator differentiating between employed and unemployed individuals with ASD.
“However, it is the strongest indicator differentiating between employed and unemployed individuals with ASD [10].”
Long-term longitudinal studies confirm that high levels of unemployment and unstable employment profiles persist among autistic adults, and higher education only partially improves the situation.
“Long-term longitudinal studies confirm that high levels of unemployment and unstable employment profiles persist among autistic adults, and higher education only partially improves the situation.”
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Nishith, S., O’Brien, A. M., Li, C., Bungert, L., Oddis, K., Riddle, J., & Gabrieli, J. D. E. (2025) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-025-07036-y · Cited by 9 · see citing works
Matulewski, J., Sikorski, Ł., & Baczała, D. (2026) · Proceedings of the 63rd ACM Conference on Computers and People Research · doi:10.1145/3768310.3807803
- Authors
- Bury, S. M., Hedley, D., Uljarević, M., Li, X., Stokes, M. A., & Begeer, S.
- Affiliations
- La Trobe University (AU)
- The University of Melbourne (AU)
- Deakin University (AU)
- Vrije Universiteit Amsterdam (NL)
- Corresponding author
- Bury, Simon M
- Venue
- Autism
- Publisher
- SAGE Publications
- Published
- 2024-01-19
- Volume
- 28
- Issue
- 9
- Pages
- 2322-2333
- ISSN
- 1362-3613 (ISSN-L)
- 1461-7005
- PMC
- PMC11403919
- OpenAlex
- W4391053323
- Cited by
- 52
- References
- 6
- Citations by year
- 2026: 32 · 2025: 14 · 2024: 6
- FWCI
- 21.55
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Autism (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- Figshare (submittedVersion, cc-by)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- ZonMw (60-63600-98-834)
- Topics
- Social Sciences › Safety Research › Disability Education and Employment
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Health Sciences › Health Professions › General Health Professions › Employment and Welfare Studies
- Keywords
- autistic adults, employment trajectories, employment effects, unemployment, job stability, autistic traits, co-occurring conditions, age at diagnosis, gender differences, educational attainment, predictors of employment, employment support programs, person-oriented analysis, latent class analysis, multinomial logistic regression, autistic women, employment retention
- MeSH terms
- Adolescent, Adult, Age Factors, Autistic Disorder, Educational Status, Employment, Female, Humans, Longitudinal Studies, Male, Middle Aged, Surveys and Questionnaires, Sex Factors, Unemployment, Young Adult
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