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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

INTRODUCTION: The 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 CHN...

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Autores principales: Wazny, Kerri, Anderson, Niall, Bassani, Diego G, Ravenscroft, John, Chan, Kit Yee, Rudan, Igor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Edinburgh University Global Health Society 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377795/
https://www.ncbi.nlm.nih.gov/pubmed/30820318
http://dx.doi.org/10.7189/jogh.09.010701
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author Wazny, Kerri
Anderson, Niall
Bassani, Diego G
Ravenscroft, John
Chan, Kit Yee
Rudan, Igor
author_facet Wazny, Kerri
Anderson, Niall
Bassani, Diego G
Ravenscroft, John
Chan, Kit Yee
Rudan, Igor
author_sort Wazny, Kerri
collection PubMed
description INTRODUCTION: The 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. METHODS: Individual 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. RESULTS: Self-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. CONCLUSION: Researchers 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.
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spelling pubmed-63777952019-02-28 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 Wazny, Kerri Anderson, Niall Bassani, Diego G Ravenscroft, John Chan, Kit Yee Rudan, Igor J Glob Health Research Theme 3: Global Health Research Priorities INTRODUCTION: The 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. METHODS: Individual 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. RESULTS: Self-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. CONCLUSION: Researchers 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. Edinburgh University Global Health Society 2019-06 2019-02-15 /pmc/articles/PMC6377795/ /pubmed/30820318 http://dx.doi.org/10.7189/jogh.09.010701 Text en Copyright © 2019 by the Journal of Global Health. All rights reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Research Theme 3: Global Health Research Priorities
Wazny, Kerri
Anderson, Niall
Bassani, Diego G
Ravenscroft, John
Chan, Kit Yee
Rudan, Igor
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Research Theme 3: Global Health Research Priorities
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377795/
https://www.ncbi.nlm.nih.gov/pubmed/30820318
http://dx.doi.org/10.7189/jogh.09.010701
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