Immunization uptake in younger siblings of children with autism spectrum disorder
Bibliographic record
Abstract
BACKGROUND: Parental concerns persist that immunization increases the risk of autism spectrum disorder, resulting in the potential for reduced uptake by parents of younger siblings of children with autism spectrum disorder ("younger sibs"). OBJECTIVE: To compare immunization uptake by parents for their younger child relative to their older child with autism spectrum disorder ("proband") and controls. DESIGN: Immunization status was obtained for 98 "younger sibs," 98 "probands," and 65 controls. RESULTS: A significant group difference emerged for overall immunization status (Fisher's exact test = 62.70, p < .001). One or more immunizations in 59/98 younger sibs were delayed (47/98; 48%) or declined (12/98; 12.2%); immunizations were delayed in 16/98 probands (16.3%) and declined in only one. All controls were fully immunized, with only 6 (9.2%) delayed. Within the "younger sibs" group, 25/98 received an autism spectrum disorder diagnosis; 7 of whom (28%) were fully immunized. The rates of autism spectrum disorder diagnosis did not differ between immunized and nonimmunized younger sib groups, although small sample size limits interpretability of this result. CONCLUSION: Parents who already have one child with autism spectrum disorder may delay or decline immunization for their younger children, potentially placing them at increased risk of preventable infectious diseases.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".