Evidence map›Paper›PMID 28298233›Full record

ArticleGlobalization and health2017

Developing consensus measures for global programs: lessons from the Global Alliance for Chronic Diseases Hypertension research program.

Michaela A Riddell, Nancy Edwards, Simon R Thompson, Antonio Bernabe-Ortiz, Devarsetty Praveen, Claire Johnson, Andre P Kengne, Peter Liu, Tara McCready, Eleanor Ng and 8 more

Abstract read
In one paragraph

Article in Globalization and health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 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

18 authors.

Michaela A RiddellDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia. Michaela.riddell@monash.edu.
Nancy EdwardsSchool of Nursing, Faculty of Health Science, University of Ottawa, Ottawa, Canada.
Simon R ThompsonQueen Mary University of London, London, UK.
Antonio Bernabe-OrtizUniversidad Peruana Cayetano Heredia, Lima, Peru.
Devarsetty PraveenThe George Institute for Global Health - India, Hyderabad, India.
Claire JohnsonThe George Institute for Global Health - Sydney, Sydney, Australia.
Andre P KengneSouth African Medical Research Council, Cape Town, South Africa.
Peter LiuUniversity of Ottawa Heart Institute, Toronto, Canada.
Tara McCreadyPopulation Health Research Institute, Hamilton, Canada.
Eleanor NgPopulation Health Research Institute, Hamilton, Canada.
Robby NieuwlaatPopulation Health Research Institute, Hamilton, Canada.
Bruce OvbiageleMedical University of South Carolina, Charleston, USA.
Mayowa OwolabiDepartment of Medicine, University of Ibadan, Ibadan, Nigeria.
David PeirisThe George Institute for Global Health, University of Sydney, Sydney, Australia.
Amanda G ThriftDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
Sheldon TobeSunnybrook Health Sciences Center, Toronto, Canada.
Khalid YusoffUniversitiTeknologi MARA, Selangor, Malaysia.
GACD Hypertension Research Programme

Funding

CIHRMedical Research CouncilWellcome TrustWellcome Trust 103994/Z/14/Z
6 · The paper itself

Abstract

backgroundThe imperative to improve global health has prompted transnational research partnerships to investigate common health issues on a larger scale. The Global Alliance for Chronic Diseases (GACD) is an alliance of national research funding agencies. To enhance research funded by GACD members, this study aimed to standardise data collection methods across the 15 GACD hypertension research teams and evaluate the uptake of these standardised measurements. Furthermore we describe concerns and difficulties associated with the data harmonisation process highlighted and debated during annual meetings of the GACD funded investigators. With these concerns and issues in mind, a working group comprising representatives from the 15 studies iteratively identified and proposed a set of common measures for inclusion in each of the teams' data collection plans. One year later all teams were asked which consensus measures had been implemented.

resultsImportant issues were identified during the data harmonisation process relating to data ownership, sharing methodologies and ethical concerns. Measures were assessed across eight domains; demographic; dietary; clinical and anthropometric; medical history; hypertension knowledge; physical activity; behavioural (smoking and alcohol); and biochemical domains. Identifying validated measures relevant across a variety of settings presented some difficulties. The resulting GACD hypertension data dictionary comprises 67 consensus measures. Of the 14 responding teams, only two teams were including more than 50 consensus variables, five teams were including between 25 and 50 consensus variables and four teams were including between 6 and 24 consensus variables, one team did not provide details of the variables collected and two teams did not include any of the consensus variables as the project had already commenced or the measures were not relevant to their study.

conclusionsDeriving consensus measures across diverse research projects and contexts was challenging. The major barrier to their implementation was related to the time taken to develop and present these measures. Inclusion of consensus measures into future funding announcements would facilitate researchers integrating these measures within application protocols. We suggest that adoption of consensus measures developed here, across the field of hypertension, would help advance the science in this area, allowing for more comparable data sets and generalizable inferences.

Indexed as

ConsensusGlobal HealthChronic DiseaseCooperative BehaviorHumansHypertensionResearch PersonnelConsensus MeasuresHypertensionImplementationImplementation ContextLow and middle income countries

Identifiers

PMID28298233
PMCPMC5353794

What OpenQuestion holds

Textmetadata
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.