Evidence map›Paper›PMID 30820318›Full record

ArticleJournal of global health2019

Exploring individual and demographic characteristics and their relation to CHNRI Criteria from an international public stakeholder group: an analysis using random intercept and logistic regression modelling.

Kerri Wazny, Niall Anderson, Diego G Bassani, John Ravenscroft, Kit Yee Chan, Igor Rudan

Abstract read
In one paragraph

Article in Journal of global health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Kerri WaznyCentre for Global Health Research, Usher Institute of Informatics and Population Health Sciences, University of Edinburgh, Edinburgh, UK.
Niall AndersonCentre of Population Health Sciences, Usher Institute of Informatics and Population Health Sciences, University of Edinburgh, Edinburgh, UK.
Diego G BassaniDepartment of Pediatrics, Hospital for Sick Children and University of Toronto, Toronto, ON, Canada.
John RavenscroftMoray House School of Education, University of Edinburgh, Edinburgh, UK.
Kit Yee ChanCentre for Global Health Research, Usher Institute of Informatics and Population Health Sciences, University of Edinburgh, Edinburgh, UK.
Igor RudanCentre for Global Health Research, Usher Institute of Informatics and Population Health Sciences, University of Edinburgh, Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe Child Health and Nutrition Research Initiative (CHNRI) method for health research prioritisation relies on stakeholders weighting criteria used to assess research options. These weights in turn impact on the final scores and ranks assigned to research options. Three quarters of CHNRI studies published to date have not involved stakeholders in criteria weighting. Of those that have, few incorporated members of the public into stakeholder groups. Those that have compared different stakeholder groups, such as donors, researchers, or policy makers, showed that different groups place different values upon CHNRI criteria. When choosing the composition of a stakeholder group, it may be important to understand factors that may influence weighting. Drawing upon a group of international public stakeholders, this study explores some of the effects of individual and demographic characteristics has on the weights assigned to the most commonly used CHNRI criteria, with the aim of informing future researchers on avoiding future biases.

methodsIndividual and demographic information and 5-point Likert scale responses to questions about the importance of 15 CHNRI criteria were collected from 1031 "Turkers" (Amazon Mechanical Turk workers) via Amazon Mechanical Turk (AMT), which is an online crowdsourcing platform. Thirteen of the fifteen criteria were analysed using random-intercept models and the remaining two were analysed through logistic regression.

resultsSelf-reported health status explained most of the variability in participants' responses across criteria (11/15 criteria), followed by being female (10/15), ethnicity (9/15), employment (8/15), and religion (7/15). Differences across criteria indicate that when choosing stakeholder groups, researchers need to consider these factors to minimise bias.

conclusionResearchers should collect and report more detailed information from stakeholders, including individual and demographic characteristics, and ensure participation from both genders, multiple ethnicities, religious beliefs, and people with differing health statuses to be transparent regarding possible biases in health research prioritisation. Our analyses indicate that these factors do influence the relative importance of these values, even when the data appears fairly homogeneous.

Indexed as

Biomedical ResearchHealth PrioritiesStakeholder ParticipationAdolescentAdultAgedChild HealthDemographyFemaleGlobal HealthHumansIndividualityLogistic ModelsMaleMiddle AgedModels, Statistical

Identifiers

PMID30820318
PMCPMC6377795

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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.