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Record W3126715386 · doi:10.1177/2333794x21991011

Pediatric Health Outcome Evaluation in Low-and Middle-Income Countries: A Scoping Review of NGO Practice

2021· review· en· W3126715386 on OpenAlexaff
Jennifer Taylor, Paula Forgeron, Amanda Vandyk, G. Allen Finley, Sophie Lightfoot

Bibliographic record

VenueGlobal Pediatric Health · 2021
Typereview
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsIzaak Walton Killam Health CentreDalhousie UniversityUniversity of Ottawa
Fundersnot available
KeywordsMedicineLow and middle income countriesOutcome (game theory)Low incomeEnvironmental healthFamily medicineEconomic growthDeveloping countrySocioeconomics

Abstract

fetched live from OpenAlex

Objective. The purpose of this study was to explore the research on the delivery and evaluation of pediatric health services by non-governmental organizations in low-and middle-income countries to better understand how they contribute to positive and sustainable health outcomes. Methods. A scoping review was completed using a 2-step study selection procedure. Results. Of the 5742 studies, 17 met criteria, including quantitative and mixed method designs, representing 10 different non-governmental organizations with programs in 33 low-and middle-income countries. Health outcomes were reported 89 times across the studies. A total of 56 different outcomes were identified in total, of which 24 were positive, 27 were negative, and 5 were unchanged. Conclusions. Widespread variation between non-governmental organizations exist, however, comprehensive pediatric health outcome evaluation is growing. Further emphasis should be given to adolescent specific research and robust measurement of quality of life.

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)0.046
metaresearch head score (Gemma)0.121
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 score0.046
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.121
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0180.020
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.164
GPT teacher head0.547
Teacher spread0.383 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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