Evidence map›Paper›PMID 31652610›Full record

ReviewInternational journal of environmental research and public health2019

Adapting Translational Research Methods to Water, Sanitation, and Hygiene.

Karen Setty, Ryan Cronk, Shannan George, Darcy Anderson, Għanja O'Flaherty, Jamie Bartram

Abstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Water and health seminar and special issue highlight ideas that will change the field.International journal of hygiene and environmental health · 2020
    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

6 authors.

Karen SettyThe Water Institute at UNC and Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 166 Rosenau Hall, CB #7431 Chapel Hill, NC 27599-7431, USA. ksetty@live.unc.edu.ORCID 0000-0002-5591-9693
Ryan CronkThe Water Institute at UNC and Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 166 Rosenau Hall, CB #7431 Chapel Hill, NC 27599-7431, USA. rcronk@live.unc.edu.ORCID 0000-0003-0157-4447
Shannan GeorgeThe Water Institute at UNC and Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 166 Rosenau Hall, CB #7431 Chapel Hill, NC 27599-7431, USA. swgeorge@email.unc.edu.
Darcy AndersonThe Water Institute at UNC and Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 166 Rosenau Hall, CB #7431 Chapel Hill, NC 27599-7431, USA. darcy.anderson@unc.edu.ORCID 0000-0002-2129-7662
Għanja O'FlahertyThe Water Institute at UNC and Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 166 Rosenau Hall, CB #7431 Chapel Hill, NC 27599-7431, USA. ghanja@live.unc.edu.
Jamie BartramThe Water Institute at UNC and Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 166 Rosenau Hall, CB #7431 Chapel Hill, NC 27599-7431, USA. jbartram@email.unc.edu.ORCID 0000-0002-6542-6315

Funding

Biostatstics for Research in Environmental HealthT32ES007018 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Stephanie Engel, Rebecca Fry · 1985 to 2026
$31.3M
NIEHS NIH HHS T32 ES007018NIEHS NIH HHS T32ES007018
6 · The paper itself

Abstract

Translational research applies scientific techniques to achieve practical outcomes, connecting pure research and pure practice. Many translational research types have arisen since the mid-1900s, reflecting the need to better integrate scientific advancement with policy and practice. Water, sanitation, and hygiene (WaSH) development efforts have aimed to reduce morbidity and mortality and improve service delivery; thus, associated research has a strong orientation toward applied studies that use diverse methods to support decision-making. Drawing from knowledge that emerged to support other professional fields, such as manufacturing and clinical healthcare, we characterize different types of translational research and clarify nomenclature and principles. We describe study approaches relevant to translational research questions, and offer overarching recommendations, specific examples, and resources for further study as practical advice to professionals who seek to apply translational methods to WaSH problems. To enhance collective outcomes, professionals should mindfully align projects within the translational spectrum. We further recommend overarching good practices such as documenting intervention adaptations, overtly considering contextual factors, and better distinguishing efficacy from effectiveness research by replicating studies in different contexts. By consciously improving the compatibility and linkages between WaSH science and practice, this guide can accelerate urgently needed progress toward global development goals.

Indexed as

HygieneSanitationTranslational Research, BiomedicalWater SupplyHumansWaterWaterdisseminationevidence-based practiceimplementation scienceknowledge translationparticipatory researchquality improvementresearch design

Identifiers

PMID31652610
PMCPMC6843932

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.