Evidence map›Paper›PMID 35168672›Full record

ArticleImplementation science communications2022

The "case" for case studies: why we need high-quality examples of global implementation research.

Blythe Beecroft, Rachel Sturke, Gila Neta, Rohit Ramaswamy

Abstract readLetter
In one paragraph

Article in Implementation science communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

4 authors.

Blythe BeecroftFogarty International Center, US National Institutes of Health, Bethesda, USA. Blythe.Beecroft@nih.gov.ORCID http://orcid.org/0000-0002-6254-421X
Rachel SturkeFogarty International Center, US National Institutes of Health, Bethesda, USA.
Gila NetaNational Cancer Institute, US National Institutes of Health, Bethesda, USA.
Rohit RamaswamyCincinnati Children's Hospital Medical Center, Cincinnati, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rigorous and systematic documented examples of implementation research in global contexts can be a valuable resource and help build research capacity. In the context of low- and middle-income countries (LMICs), there is a need for practical examples of how to conduct implementation studies. To address this gap, Fogarty's Center for Global Health Studies in collaboration with the Cincinnati Children's Hospital Medical Center and the National Cancer Institute is commissioning a collection of implementation science case studies in LMICs that describe key components of conducting implementation research, including how to select, adapt, and apply implementation science models, theories, and frameworks to these settings; develop and test implementation strategies; and evaluate implementation processes and outcomes. The case studies describe implementation research in various disease areas in LMICs around the world. This commentary highlights the value of case study methods commonly used in law and business schools as a source of "thick" (i.e., context-rich) description and a teaching tool for global implementation researchers. It addresses the independent merit of case studies as an evaluation approach for disseminating high-quality research in a format that is useful to a broad range of stakeholders. This commentary finally describes an approach for developing high-quality case studies of global implementation research, in order to be of value to a broad audience of researchers and practitioners.

Indexed as

Case studiesGlobal implementation scienceLMICs

Identifiers

PMID35168672
PMCPMC8848686

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.