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Record W4225282860 · doi:10.1542/peds.2021-053852l

Delivery Strategies Supporting School-Age Child Health: A Systematic Review

2022· review· en· W4225282860 on OpenAlexaff
Naeha Sharma, Ayesha Asaf, Tyler Vaivada, Zulfiqar A Bhutta

Bibliographic record

VenuePEDIATRICS · 2022
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of TorontoSickKids Foundation
Fundersnot available
KeywordsMedicinePsychological interventionPsycINFOSystematic reviewMEDLINECochrane LibraryFamily medicineGerontologyMeta-analysisNursingPathology

Abstract

fetched live from OpenAlex

CONTEXT: School-aged children (SAC; 5-9 years) remain understudied in global efforts to examine intervention effectiveness and scale up evidence-based interventions. OBJECTIVE: This review summarizes the available evidence describing the effectiveness of key strategies to deliver school-age interventions. DATA SOURCES: We searched Medline, PsycINFO, Campbell Collaboration, and The Cochrane Library during November 2020. STUDY SELECTION: Systematic reviews and meta-analyses that: target SAC, examine effective delivery of well-established interventions, focus on low- and middle-income countries (LMICs), were published after 2010, and focus on generalizable, rather than special, populations. DATA EXTRACTION: Two reviewers conducted title and abstract screening, full-text screening, data extraction, and quality assessments. RESULTS: Sixty reviews met the selection criteria, with 35 containing evidence from LMICs. The outcomes assessed and the reported effectiveness of interventions varied within and across delivery strategies. Overall, community, school, and financial strategies improved several child health outcomes. The greatest evidence was found for the use of community-based interventions to improve infectious disease outcomes, such as malaria control and prevention. School-based interventions improved child development and infectious disease-related outcomes. Financial strategies improved school enrollment, food security, and dietary diversity. LIMITATIONS: Relatively few LMIC studies examined facility, digital, and self-management strategies. Additionally, we found considerable heterogeneity within and across delivery strategies and review authors reported methodological limitations within the studies. CONCLUSIONS: Despite limited research, available information suggests community-based strategies can be effective for the introduction of a range of interventions to support healthy growth and development in SAC. These also have the potential to reduce disparities and reach at-risk and marginalized populations.

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)0.010
metaresearch head score (Gemma)0.042
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: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.042
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.055
GPT teacher head0.360
Teacher spread0.306 · 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
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

Citations8
Published2022
Admission routes1
Has abstractyes

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