Away from the “fidgety boy”: Why our view of neurodiversity is often blind to gender and culture
When we talk about neurodiversity, many people still have a very specific image in their minds: the young student who disrupts class or the brilliant but socially awkward IT expert. These clichés are not only outdated, they are dangerous. They shape how we build simulations, how we design software, and who ultimately gets the support they need and who doesn’t.
In my research, I noticed that most tools that depict “sensory overload” focus on the visible, almost “loud” symptoms. We see someone covering their ears or closing their eyes. But what about those we don’t see?
A key reason for gender bias in diagnosis and design is what is known as masking (or camouflaging). FLINTA individuals in particular often learn at an early age to suppress their neurodivergent traits in order to meet social expectations.
Masking is not simply “pretending.” It is a highly complex, unconscious, and extremely exhausting process. You are constantly scanning your surroundings: Am I laughing at the right moment? Am I staring at the person I’m talking to for too long? Do I seem too absent-minded right now? While you appear completely calm and “functional” on the outside, your brain is racing at 200% in the background.
In terms of design, this means that if we only optimize for visible symptoms, we exclude the entire group of people who mask their symptoms perfectly. A study clearly shows that this camouflaging correlates directly with a higher rate of depression and burnout. So if an interface wants to be “barrier-free,” it can’t wait for a user to “look overwhelmed.” It must assume that stress often occurs internally.
Neurodiversity does not exist in a vacuum. It is inextricably linked to gender, but also to cultural and ethnic origin. Researchers often refer to this as the intersectional gap.
For example, a white child with ADHD symptoms is often seen as “in need of treatment” or “gifted but restless.” Statistically, the same symptoms are far more likely to be misinterpreted as “indiscipline” or “aggression” in Black children or children from marginalized communities. As a result, neurodivergent people from these groups are often diagnosed very late or not at all.
For us designers, this means that when we create personas or look for test groups for our products, we must not only represent “standard neurodivergence.” We have to ask ourselves: How does a person with ADHD use my app who also struggles with racist stereotypes in everyday life and therefore has an even greater need for security and predictability?
And in order to improve it, we first need to understand it better.
Conclusion: Inclusion requires diversity in the database
Accessibility is not an “add-on” that you slap onto a finished product. It is an attitude. Ultimately, greater inclusion helps everyone.
Neurodiversity does not exist in a vacuum. A woman with ADHD experiences barriers differently than a man, as racialized and gendered stereotypes complicate diagnosis and acceptance.
Sources & Links:
- Hull et al. (2017/2020): Sex/Gender Differences in Camouflaging in Autism. Link to Study (PMC)
- Hull‑Artikel (Journal)
Hull, L., Lai, M.-C., Baron-Cohen, S., Allison, C., Smith, P., Petrides, K. V., & Mandy, W. (2020). Gender differences in self-reported camouflaging in autistic and non-autistic adults. Autism, 24(8), 1–13. - John Innes Centre Blog (Webseite/Blog)
John Innes Centre. (2025, 5. August). Exploring neurodiversity through an intersectional lens. Abgerufen von https://www.jic.ac.uk/blog/exploring-neurodiversity-through-an-intersectional-lens/ - Tiimo App Blog (Webseite/Blog)
Tiimo. (2024, 12. Dezember). Masking in autistic women and girls: What it is and why it matters. Abgerufen von https://www.tiimoapp.com/de/resource-hub/masking-autistic-women-girls - Crenshaw‑Aufsatz (Original 1989)
Crenshaw, K. (1989). Demarginalizing the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics.
Note: This text was developed with the assistance of artificial intelligence for research purposes and to refine the linguistic clarity and flow of the final draft.
