Studies of autistic traits in the general population are not studies of autism.

Sasson et al. (2022) wrote a position paper. They looked at studies that measure “autistic traits” in college students or online volunteers. The authors asked: Are we wrongly calling these papers “autism research”?

They did not collect new data. They argued with logic and examples. Their goal was to get scientists and clinicians to stop saying trait scores tell us how autistic people think or feel.

The team found a big mix-up. Many papers claim that high trait scores in typical adults equal “mild autism.” The authors say this is like calling tall people “mildly pregnant.” The traits are not the disorder.

They warn that policy and therapy ideas built on trait studies may miss real autistic needs.

Fusar-Poli et al. (2017) reviewed sex differences in both diagnosed and non-diagnosed groups. They show core traits look alike across groups, backing the idea that traits alone are not autism.

Heald et al. (2020) ran an experiment on emotional face viewing in typical adults with high trait scores. They found no effect, exactly the kind of study J et al. say should be labeled “trait research,” not “autism research.”

Dissanayake et al. (2020) linked high parent traits to parenting stress. Again, the sample had no autism diagnosis. J et al. would flag this as useful parenting data, but not evidence about autistic parents.

Waterhouse (2022) also urges clearer labels, pushing for endophenotypes instead of the single word “autism.” Both papers agree: sloppy labels hide real differences and slow good treatment.

When you read a new article, flip to the participants table. If the group is “typical adults” and the measure is a trait scale, treat the findings as hints about the general public, not about your autistic clients. Share the paper with colleagues only after you add a sticky note: “Trait study—does not speak for autism.” This small habit keeps assessments, parent advice, and policy grounded in the right evidence.