Parental and Medical Classification of Neurodevelopment in Children Born Preterm
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The likelihood and severity of neurodevelopmental impairment (NDI) affects critical health care decisions. NDI definitions were developed without parental perspectives. We investigated the agreement between parental vs medical classification of NDI among children born preterm. METHODS: In this multicenter study, parents of children born preterm (<29 weeks) evaluated at 18 to 21 months corrected age (CA) were asked whether they considered their child as developing normally, having mild/moderate impairment, or having severe impairment. Medical categorization was based on hearing, vision, cerebral palsy status, and Bayley Scales of Infant and Toddler Development Third Edition (Bayley-III) scores. Agreement was analyzed using Cohen's weighted κ. Discrepancies in categorization by NDI components and parental demographics were examined using the Pearson χ2 test, Fisher exact test, or Wilcoxon signed-rank test. RESULTS: Children (n = 1098, gestational age 26.1 ± 1.5 weeks, birthweight 919 ± 247 g) were evaluated at 19.6 ± 2.6 months CA at 13 clinics. Agreement between parental and medical NDI classification was poor (κ = 0.30; 95% CI: 0.26-0.35). Parents described their child's development as normal or less impaired. Only 12% of parents of children classified as having a severe NDI according to the medical definition agreed. There were significant disagreements between classification for children based on Bayley-III cognitive, language, and motor scores but not for cerebral palsy. Discrepancies varied by parental education and ethnicity but not by single caregiver status. CONCLUSIONS: Parent perception of NDI differs from medical categorization, creating a risk of miscommunication. This indicates an overestimation of the impact of disability by clinicians, which may affect life-and-death decisions. Parental perspectives should be considered when reporting and discussing neurodevelopmental outcomes.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".