Apparent increases in autism prevalence are largely an artifact: changes in who counts as autistic (DSM criteria), clinicians' incentives, and how administrative datasets are assembled (age of ascertainment, survival bias) produce a misleading upward trend that can’t be read as a simple rise in underlying incidence. Correct policy responses require separating diagnostic/reporting effects from true causal increases so services and research are targeted appropriately.
— If policymakers treat administrative diagnosis trends as raw incidence, they risk misallocating research funding and public services and pursuing wrong causal hypotheses.
2026.10.04
86% relevant
This article reviews the DSM‑5 change that collapsed Asperger’s disorder and related pervasive developmental disorder categories into a single autism spectrum disorder (ASD) diagnosis — exactly the kind of diagnostic‑definition change that produces 'diagnosis drift' and can inflate, shift, or reclassify prevalence and service demand; the piece explicitly notes concerns about boundary changes and prospective comparisons to prior criteria, tying the paper’s claims (actor: DSM‑5 task force; evidence: revised criteria) to the existing idea.
Matthew R Cooperberg
2026.09.29
72% relevant
Both pieces identify how changes in diagnostic labels and practices (here: applying the word 'cancer' to low‑risk cellular findings; there, expanding autism labels) inflate incidence figures and misdirect clinical and policy responses; Cooperberg’s case (prostate grade‑group 1, active surveillance vs immediate treatment) is a concrete example of the same mechanism of 'label → consequence' described by the existing idea.
2026.05.04
100% relevant
The article cites the California Department of Developmental Services cohort graph, highlights the DSM‑III (1980) criteria change, and notes RFK Jr.'s stated priority to 'figure out why' autism rates increased—concrete hooks tying data, institution, and policy interest.