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Record W3154244527 · doi:10.1371/journal.pone.0249638

Barriers and facilitators to implementation of oral rehydration therapy in low- and middle-income countries: A systematic review

2021· review· en· W3154244527 on OpenAlexaff
Obidimma Ezezika, Apira Ragunathan, Yasmine El-Bakri, Kathryn Barrett

Bibliographic record

VenuePLoS ONE · 2021
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsOntario Tech UniversityThe Scarborough HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsInclusion (mineral)ScopusMedicineLow and middle income countriesMEDLINEImplementation researchGeneral partnershipGlobal healthData extractionMillennium Development GoalsDeveloping countryFamily medicinePublic healthMedical educationNursingPolitical scienceEconomic growthPsychological interventionPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Oral rehydration therapy (ORT) is an effective and cheap treatment for diarrheal disease; globally, one of the leading causes of death in children under five. The World Health Organization launched a global campaign to improve ORT coverage in 1978, with activities such as educational campaigns, training health workers and the creation of designate programming. Despite these efforts, ORT coverage remains relatively low. The objective of this systematic review is to identify the barriers and facilitators to the implementation of oral rehydration therapy in low and middle-income countries. METHODS: A comprehensive search strategy comprised of relevant subject headings and keywords was executed in 5 databases including OVID Medline, OVID Embase, OVID HealthStar, Web of Science and Scopus. Eligible studies underwent quality assessment, and a directed content analysis approach to data extraction was conducted and aligned to the Consolidated Framework for Implementation Research (CFIR) to facilitate narrative synthesis. RESULTS: The search identified 1570 citations and following removal of duplicates as well as screening according to our inclusion/exclusion criteria, 55 articles were eligible for inclusion in the review. Twenty-three countries were represented in this review, with India, Bangladesh, Egypt, Nigeria, and South Africa having the most representation of available studies. Study dates ranged from 1981 to 2020. Overarching thematic areas spanning the barriers and facilitators that were identified included: availability and accessibility, knowledge, partnership engagement, and design and acceptability. CONCLUSION: A systematic review of studies on implementation of ORT in low- and middle-income countries (LMICs) highlights key activities that facilitate the development of successful implementation that include: (1) availability and accessibility of ORT, (2) awareness and education among communities, (3) strong partnership engagement strategies, and (4) adaptable design to enhance acceptability. The barriers and facilitators identified under the CIFR domains can be used to build knowledge on how to adapt ORT to national and local settings and contribute to a better understanding on the implementation and use of ORT in LMICs. The prospects for scaling and sustaining ORT (after years of low use) will increase if implementation research informs local applications, and implementers engage appropriate stakeholders and test assumptions around localized theories of change from interventions to expected outcomes. REGISTRATION: A protocol for this systematic review was developed and uploaded onto the PROSPERO international prospective register of systematic reviews database (Registration number: CRD420201695).

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)0.023
metaresearch head score (Gemma)0.096
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 score0.023
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.096
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0020.001
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 head0.058
GPT teacher head0.340
Teacher spread0.282 · 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

Citations31
Published2021
Admission routes1
Has abstractyes

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