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Record W3003372641 · doi:10.1111/jir.12720

Health care utilisation in infants and young children born to women with intellectual and developmental disabilities: A systematic review and meta‐analysis

2020· review· en· W3003372641 on OpenAlexaff
Dinara Salaeva, Lesley A. Tarasoff, Hilary K. Brown

Bibliographic record

VenueJournal of Intellectual Disability Research · 2020
Typereview
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsThe Scarborough HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMeta-analysisDevelopmental psychologyIntellectual disabilityPsychologyMedicineGerontologyPediatricsPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Mothers with intellectual and developmental disabilities (IDD) experience socio-economic and health disparities which could impact their offspring's health care utilisation. We systematically reviewed evidence on health care utilisation in infants and young children of women with and without IDD. METHODS: MEDLINE, EMBASE, CINAHL, and PsycINFO were searched from inception to October 2019 for studies examining preventive care, immunisations, emergency department visits, and hospitalisations. Data extraction and quality assessment were performed using standardised tools. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were generated using random effects models for outcomes with data available from ≥3 studies. RESULTS: Four articles describing three cohort studies and one cross-sectional study met our criteria. Maternal IDD status was associated with increased neonatal intensive care unit admission rates (pooled OR 2.03; 95% CI 1.31, 3.13). There were no differences in immunisation rates or hospitalisations. CONCLUSIONS: Few studies have examined the impact of maternal IDD status on health care utilisation in their infants and young children. More high-quality studies are needed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0010.003
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.129
GPT teacher head0.448
Teacher spread0.319 · 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 teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreReview

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

Citations5
Published2020
Admission routes1
Has abstractyes

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