Evidence map›Paper›PMID 29594154›Full record

ArticleFrontiers in veterinary science2018

A Systems Approach to Evaluate One Health Initiatives.

Simon R Rüegg, Liza Rosenbaum Nielsen, Sandra C Buttigieg, Mijalche Santa, Maurizio Aragrande, Massimo Canali, Timothy Ehlinger, Ilias Chantziaras, Elena Boriani, Miroslav Radeski and 3 more

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 2 pooled it
–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

88 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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28 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

13 authors.

Simon R RüeggVetsuisse Faculty, University of Zurich, Zurich, Switzerland.
Liza Rosenbaum NielsenFaculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Sandra C ButtigiegFaculty of Health Sciences, University of Malta, Msida, Malta.
Mijalche SantaFaculty of Economics-Skopje, Saints Cyril and Methodius University of Skopje, Skopje, Macedonia.
Maurizio AragrandeDepartment of Agricultural and Food Sciences, University of Bologna, Bologna, Italy.
Massimo CanaliDepartment of Agricultural and Food Sciences, University of Bologna, Bologna, Italy.
Timothy EhlingerCenter for Global Health Equity, University of Wisconsin Milwaukee, Milwaukee, WI, United States.
Ilias ChantziarasFaculty of Veterinary Medicine, Ghent University, Ghent, Belgium.
Elena BorianiGlobal Decision Support Initiative (GDSI), Technical University of Denmark, Kongens Lyngby, Denmark.
Miroslav RadeskiFaculty of Veterinary Medicine, Saints Cyril and Methodius University of Skopje, Skopje, Macedonia.
Mieghan BruceSchool of Veterinary and Life Science, Murdoch University, Perth, WA, Australia.
Kevin QueenanRoyal Veterinary College, London, United Kingdom.
Barbara HäslerRoyal Veterinary College, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Challenges calling for integrated approaches to health, such as the One Health (OH) approach, typically arise from the intertwined spheres of humans, animals, and ecosystems constituting their environment. Initiatives addressing such wicked problems commonly consist of complex structures and dynamics. As a result of the EU COST Action (TD 1404) "Network for Evaluation of One Health" (NEOH), we propose an evaluation framework anchored in systems theory to address the intrinsic complexity of OH initiatives and regard them as subsystems of the context within which they operate. Typically, they intend to influence a system with a view to improve human, animal, and environmental health. The NEOH evaluation framework consists of four overarching elements, namely: (1) the definition of the initiative and its context, (2) the description of the theory of change with an assessment of expected and unexpected outcomes, (3) the process evaluation of operational and supporting infrastructures (the "OH-ness"), and (4) an assessment of the association(s) between the process evaluation and the outcomes produced. It relies on a mixed methods approach by combining a descriptive and qualitative assessment with a semi-quantitative scoring for the evaluation of the degree and structural balance of "OH-ness" (summarised in an OH-index and OH-ratio, respectively) and conventional metrics for different outcomes in a multi-criteria-decision-analysis. Here, we focus on the methodology for Elements (1) and (3) including ready-to-use Microsoft Excel spreadsheets for the assessment of the "OH-ness". We also provide an overview of Element (2), and refer to the NEOH handbook for further details, also regarding Element (4) (http://neoh.onehealthglobal.net). The presented approach helps researchers, practitioners, and evaluators to conceptualise and conduct evaluations of integrated approaches to health and facilitates comparison and learning across different OH activities thereby facilitating decisions on resource allocation. The application of the framework has been described in eight case studies in the same Frontiers research topic and provides first data on OH-index and OH-ratio, which is an important step towards their validation and the creation of a dataset for future benchmarking, and to demonstrate under which circumstances OH initiatives provide added value compared to disciplinary or conventional health initiatives.

Indexed as

evaluation frameworkintegrated approaches to healthone healthone health indexone health ratiotransdisciplinary

Identifiers

PMID29594154
PMCPMC5854661

What OpenQuestion holds

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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.