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Record W4411577359 · doi:10.1186/s12978-025-02043-9

Born Too Soon: Integration of intersectoral interventions for impact on preterm birth

2025· article· en· W4411577359 on OpenAlex
Étienne V Langlois, Maria El Bizri, Kelly Thompson, Amy Reid, Merette Khalil, Giulia Gasparri, Joy E Lawn, Teesta Dey, Judith Robb-McCord, Yousra-Imane Benaskeur, Ana Bonell, Amanuel Gidebo, Elaine Scudder, Sophie Marie Kostelecky, Patricia Machawira, Lars Gronseth, Rajnish Prasad, Dilip Sapkota, Priyen Pillay, Bina Valsangkar, Bo Jacobsson, Marleen Temmerman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReproductive Health · 2025
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsChildren's Hospital of Eastern Ontario
FundersUNICEFWorld Health Organization
KeywordsPsychological interventionAccountabilitySocial determinants of healthMedicineMillennium Development GoalsHealth equityEconomic growthEnvironmental healthReproductive healthHealth carePublic healthBusinessNursingPolitical scienceDeveloping countryPopulationEconomics

Abstract

fetched live from OpenAlex

PROGRESS: The last two decades have seen a growing focus on intersectoral interventions to improve maternal and newborn health and well-being outcomes, as reflected in efforts to achieve the Millennium Development Goals (MDGs) and advance the Sustainable Development Goals (SDGs). Preterm births are linked to cross-sectoral determinants that affect health outcomes and human capital across the life-course, necessitating an intersectoral approach that addresses these multifaceted challenges. PROGRAMMATIC PRIORITIES: Recognizing that social, biological and economic determinants significantly influence health outcomes, it is critical that robust health systems are reinforced by a comprehensive intersectoral approach. Evidence suggests that the factors influencing preterm birth, and the health of small and sick newborns are vast and varied, requiring interventions that address equity and rights, education, economic factors, environmental conditions, and emergency responses, i.e., a new framework entitled "five Es". PIVOTS: Improving outcomes for newborns, including preterm and small for gestational age babies, and preventing stillbirths, requires enhanced measurement and accountability within intersectoral programs across the 'five Es'. Investment in equity-focused, gender-transformative, and rights-based policies and programs across various sectors is crucial. Priority areas include ensuring equitable and inclusive education, particularly comprehensive sexual and reproductive health education; developing innovative financing schemes that protect and support families with complicated pregnancies and vulnerable infants; creating environmentally adaptive systems that prioritize maternal and newborn health; and implementing emergency response plans that guarantee the continuity of maternal and newborn health services. Evidence-based intersectoral interventions offer a promising pathway to reducing preterm births and improving health outcomes across generations. By addressing the five Es, intersectoral interventions can create a healthier future for preterm babies, children, adolescents, women, and society as a whole.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.425
Teacher spread0.375 · 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