Evidence map›Paper›PMID 38413928›Full record

ArticleBMC pediatrics2024

Drivers of success: improving implementation research tools for better health outcomes.

Quinhas Fernandes, Orvalho Augusto, Kenneth Sherr

Abstract read
In one paragraph

Article in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Quinhas FernandesNational Directorate of Public Health, Ministry of Health, Maputo, Mozambique. quinhasf@uw.edu.ORCID http://orcid.org/0000-0002-1539-0967
Orvalho AugustoDepartment of Global Health, University of Washington, Seattle, WA, USA.
Kenneth SherrDepartment of Global Health, University of Washington, Seattle, WA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A thorough examination of context, and how it influences implementation of evidence-based interventions, is a promising strategy for enhancing child survival initiatives. Spreading approaches that are identified as drivers of successful reduction in under-five mortality from 'exemplar' countries could be pivotal in leading to reductions in other settings facing stagnant mortality rates, in particular for low- and middle-income countries with high disease burden and insufficient programmatic capacity to effectively implement evidence-based interventions at scale. Yet there remains a lack of robust analytic methods to accurately assess mortality and describe the drivers of interventions' implementation success at both national and subnational levels. The field of implementation science and its defining targets and tools is well positioned to address this knowledge gap by integrating qualitative and quantitative research methods into an adaptable evaluation framework that can be tailored to meet the specific needs across varying country contexts. These tools enhance the measurement of population health outcomes and provide crucial evidence on implementation barriers and facilitators that can inform policies that can be adjusted for diverse contexts. This commentary aims to emphasize the role of implementation research in understanding how exemplar countries achieved significant improvements in child survival and in identifying replicable lessons for other settings. Ultimately, all manuscripts underscore the relevance of implementation research in bolstering the reduction of under-five mortality.

Indexed as

Outcome Assessment, Health CareChildHumansEPIASExemplar countriesImplementation scienceLow- and middle-income countriesUnder-five mortality

Identifiers

PMID38413928
PMCPMC10900546

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.