Global Prevalence of Autism and Other Pervasive Developmental Disorders
Bibliographic record
Abstract
We provide a systematic review of epidemiological surveys of autistic disorder and pervasive developmental disorders (PDDs) worldwide. A secondary aim was to consider the possible impact of geographic, cultural/ethnic, and socioeconomic factors on prevalence estimates and on clinical presentation of PDD. Based on the evidence reviewed, the median of prevalence estimates of autism spectrum disorders was 62/10 000. While existing estimates are variable, the evidence reviewed does not support differences in PDD prevalence by geographic region nor of a strong impact of ethnic/cultural or socioeconomic factors. However, power to detect such effects is seriously limited in existing data sets, particularly in low-income countries. While it is clear that prevalence estimates have increased over time and these vary in different neighboring and distant regions, these findings most likely represent broadening of the diagnostic concets, diagnostic switching from other developmental disabilities to PDD, service availability, and awareness of autistic spectrum disorders in both the lay and professional public. The lack of evidence from the majority of the world's population suggests a critical need for further research and capacity building in low- and middle-income countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".