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Record W3006540537 · doi:10.1111/nyas.14319

Interventions to increase adherence to micronutrient supplementation during pregnancy: a protocol for a systematic review

2020· review· en· W3006540537 on OpenAlexaff
Filomena Gomes, Gilles Bergeron, Megan W. Bourassa, Diana Dallmann, Jenna Golan, Kristen Hurley, Shannon King, Ana Carolina Feldenheimer da Silva, Saurabh Mehta

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2020
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsMcGill University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesBill and Melinda Gates FoundationNational Institutes of HealthNational Science Foundation
KeywordsMicronutrientMedicineCochrane LibraryPsychological interventionRandomized controlled trialPregnancyContext (archaeology)Meta-analysisProtocol (science)MEDLINEEnvironmental healthOdds ratioAlternative medicineInternal medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

Micronutrient supplementation during pregnancy has been shown to be a cost-effective method to reduce the risk of adverse pregnancy and birth outcomes. However, one of the main barriers to the successful implementation of a micronutrient supplementation program in pregnancy is poor adherence. Our review will assess the effectiveness of interventions designed to increase adherence to micronutrient supplements in pregnancy. Following the Cochrane Collaboration Methodology, we will start by conducting the literature searches on Medline (via PubMed), Embase, Scopus, Web of Science, and Cochrane Library, in addition to sources of gray literature, to retrieve all the available relevant studies. We will include randomized controlled trials and nonrandomized studies with a control group, where participants are pregnant women taking any micronutrient supplements in the context of antenatal care globally. We will include studies with targeted interventions designed to improve adherence to micronutrient supplementation in pregnant women compared with (1) usual care or no intervention or (2) other targeted micronutrient adherence intervention. Abstract selection, data extraction, and risk of bias assessment (according to the type of studies) will be conducted by two independent reviewers. The pooled results will be reported using the standardized mean differences for continuous data, and odds ratio or risk ratio for dichotomous data. We will assess sources of heterogeneity and publication bias. By following this protocol, we will systematically assess and synthesize the existing evidence about interventions designed to increase adherence to micronutrient supplementation in pregnant women. Understanding which strategies are more effective to increase the consumption of micronutrient supplements during this critical stage of life will have significant implications for clinicians and policymakers involved in the delivery of prenatal micronutrient supplementation interventions.

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)0.083
metaresearch head score (Gemma)0.103
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.083
Threshold uncertainty score0.438

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0830.103
Meta-epidemiology (narrow)0.0070.006
Meta-epidemiology (broad)0.0200.020
Bibliometrics0.0180.019
Science and technology studies0.0050.005
Scholarly communication0.0090.010
Open science0.0060.006
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0660.011

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 head0.214
GPT teacher head0.481
Teacher spread0.267 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations11
Published2020
Admission routes1
Has abstractyes

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