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Record W4200101943 · doi:10.1111/dmcn.15132

Mathematical performance in childhood and early adult outcomes after very preterm birth: an individual participant data meta‐analysis

2021· review· en· W4200101943 on OpenAlexafffund
Julia Jaekel, Peter J. Anderson, Peter Bartmann, Jeanie L.Y. Cheong, Lex W. Doyle, Maureen Hack, Samantha Johnson, Neil Marlow, Saroj Saigal, Louis A. Schmidt, Mary C. Sullivan, Dieter Wolke

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2021
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsMcMaster University
FundersNational Institute of Nursing ResearchMedical Research CouncilNational Institutes of HealthUniversity College LondonCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchHospital for Sick ChildrenDanish Cancer Society Research CenterDeutsche ForschungsgemeinschaftNational Health and Medical Research CouncilMcMaster University
KeywordsConfidence intervalEducational attainmentOdds ratioLogistic regressionGestational ageMedicineDemographyCohort studyYoung adultPregnancyPediatricsPsychologyGerontologyInternal medicine

Abstract

fetched live from OpenAlex

AIM: To investigate the strength of the independent associations of mathematics performance in children born very preterm (<32wks' gestation or <1500g birthweight) with attending postsecondary education and their current employment status in young adulthood. METHOD: We harmonized data from six very preterm birth cohorts from five different countries and carried out one-stage individual participant data meta-analyses (n=954, 52% female) using mixed effects logistic regression models. Mathematics scores at 8 to 11 years of age were z-standardized using contemporary cohort-specific controls. Outcomes included any postsecondary education, and employment/education status in young adulthood. All models were adjusted for year of birth, gestational age, sex, maternal education, and IQ in childhood. RESULTS: Higher mathematics performance in childhood was independently associated with having attended any postsecondary education (odds ratio [OR] per SD increase in mathematics z-score: 1.36 [95% confidence interval {CI}: 1.03, 1.79]) but not with current employment/education status (OR 1.14 per SD increase [95% CI: 0.87, 1.48]). INTERPRETATION: Among populations born very preterm, childhood mathematics performance is important for adult educational attainment, but not for employment status.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.113
GPT teacher head0.341
Teacher spread0.228 · 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 designObservational
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

Citations16
Published2021
Admission routes2
Has abstractyes

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