Evidence map›Paper›PMID 34045837›Full record

ArticleEthnicity & disease2021

Recommendations for Addressing Structural Racism in Implementation Science: A Call to the Field.

Rachel C Shelton, Prajakta Adsul, April Oh

Abstract read
In one paragraph

Article in Ethnicity & disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers.

0numbers the graph read from it
0cells of the map it votes in
96citing 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

96 citing papers in PubMed.

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36 more citing papers are in PubMed but not listed here.

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.

Rachel C SheltonDepartment of Sociomedical Sciences, Columbia University Mailman School of Public Health, New York, NY.
Prajakta AdsulDepartment of Medicine, University of New Mexico, Albuquerque, NM.
April OhNational Cancer Institute, Division of Cancer Control and Population Sciences, Rockville, MD.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Implementation science (IS) has emerged in response to a striking research-to-practice gap, with the goal of accelerating and addressing the development, translation, and widespread uptake of evidence-based interventions (EBIs). Despite the promise of IS, critical gaps and opportunities remain within the field to explicitly facilitate health equity, particularly as they relate to the role of social determinants of health and structural racism. In this commentary, we propose recommendations for the field of IS to include structural racism as a more explicit focus of our work. First, we make the case for including structural racism as a construct and promote its measurement as a determinant within existing IS frameworks/models, laying the foundation for an empirical evidence base on mechanisms through which such factors influence inequitable adoption, implementation, and sustainability of EBIs. Second, we suggest considerations for both EBIs and implementation strategies that directly or indirectly address structural racism and impact health equity. Finally, we call for use of methods and approaches within IS that may be more appropriate for addressing structural racism at multiple ecological levels and clinical and community settings in which we conduct IS, including community-based participatory research and stakeholder engagement. We see these as opportunities to advance the focus on health equity within IS and conclude with a charge to the field to consider making structural racism and the dismantling of racism an explicit part of the IS research agenda.

Indexed as

Health EquityRacismHumansImplementation ScienceStakeholder ParticipationHealth DisparitiesHealth EquityImplementation ScienceRacismStructural Racism

Identifiers

PMID34045837
PMCPMC8143847

What OpenQuestion holds

Textmetadata
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Registered trials

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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.