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Record W4402725573 · doi:10.1542/peds.2024-067811

Maternal Disability and Childhood Outcomes: Considerations for the Pediatrician

2024· letter· en· W4402725573 on OpenAlexaboutno aff
Luz Adriana Matiz

Bibliographic record

VenuePEDIATRICS · 2024
Typeletter
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePediatrics

Abstract

fetched live from OpenAlex

Maternal disability is a well-known risk factor for poor outcomes in children.1–3 In this issue of Pediatrics, Brown et al provide a comprehensive analysis of the association of maternal disability with outcomes in childhood up to 24 months of age.4 The analysis was based on nearly 108 000 mothers with disabilities and their newborns studied over the course of 7 years in Ontario, Canada. The authors compared these mother–child dyads to >700 000 mother–child dyads with no known maternal disability. The primary outcomes were receipt of the recommended number of well-child visits and routine immunization in the first 2 years of life. Secondary outcomes included receipt of an enhanced 18-month developmental assessment or any developmental screen.Although the receipt of well-child care, immunizations, and developmental screening was suboptimal for all children, children whose mothers had intellectual/developmental disability (IDD) had the lowest rates. Brown et al found that mothers with IDD were more likely to be younger, have lower incomes, have higher mental health needs, and have children with more complications at birth such as being preterm, having congenital anomalies, or being medically complex. These children were also more likely to have child protective services involvement at the time of newborn nursery discharge.The study by Brown et al has direct implications for the way we should provide care. As pediatricians, we need to recognize the importance of maternal IDD and screen for this as part of routine child health care. Once identified, we need to ensure full medical home services for the child. One solution is for medical homes to offer care coordination with community health workers, social workers, nurse home visit programs, or care managers for those children whose mothers have IDD.5 Through these supports, the medical home can also connect families to any needed resources such as clinic transportation to scheduled visits and appointment reminders.A second consideration is that we should strongly consider referrals for early intervention for all children of mothers with IDD. Ensuring comprehensive evaluations early on will help identify these at-risk children and support that they reach maximum development. Finally, more studies are needed to best understand questions not addressed in this study such as the role of fathers with IDD in childhood outcomes and the role that child protection services may play to help these children, as well.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.027
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.079
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.004
Science and technology studies0.0030.003
Scholarly communication0.0070.007
Open science0.0040.004
Research integrity0.0100.018
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.056
GPT teacher head0.356
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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