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Design and implementation of a web-based, respondent-driven sampling solution

BACKGROUND: Respondent-driven sampling (RDS) refers both to a chain-referral sampling method and an analytical model for analysing sampled data. Web-based respondent-driven sampling (webRDS) uses internet-based recruitment coupled with an electronic survey to carry out RDS studies; there is currentl...

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Autores principales: McGowan, Catherine R., Ekoriko, Promise, Alhaffar, Mervat, Cassidy-Seyoum, Sarah, Whitbread, Steven, Rogers, Phil, Bell, Lucy, Checchi, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320937/
https://www.ncbi.nlm.nih.gov/pubmed/37407971
http://dx.doi.org/10.1186/s12911-023-02217-0
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author McGowan, Catherine R.
Ekoriko, Promise
Alhaffar, Mervat
Cassidy-Seyoum, Sarah
Whitbread, Steven
Rogers, Phil
Bell, Lucy
Checchi, Francesco
author_facet McGowan, Catherine R.
Ekoriko, Promise
Alhaffar, Mervat
Cassidy-Seyoum, Sarah
Whitbread, Steven
Rogers, Phil
Bell, Lucy
Checchi, Francesco
author_sort McGowan, Catherine R.
collection PubMed
description BACKGROUND: Respondent-driven sampling (RDS) refers both to a chain-referral sampling method and an analytical model for analysing sampled data. Web-based respondent-driven sampling (webRDS) uses internet-based recruitment coupled with an electronic survey to carry out RDS studies; there is currently no commercially available webRDS solution. We designed and developed a webRDS solution to support a research study aimed at estimating conflict-attributable mortality in Yemen. Our webRDS solution is composed of an existing survey platform (i.e. ODK) and a bespoke RDS system. The RDS system is designed to administer and manage an RDS survey cascade and includes: (1) an application programming interface, (2) a study participant client, and (3) an administrator interface. We report here on the design of the webRDS solution and its implementation. RESULTS: We consulted members of the Yemeni diaspora throughout the development of the solution. Technical obstacles were largely the result of: WhatsApp’s policies on bulk messaging and automated messaging behaviour, the inherent constraints of SMS messaging, and SMS filtering behaviour. Language support was straight-forward yet time consuming. Survey uptake was lower than expected. Factors which may have impacted uptake include: our use of consumable survey links, low interest amongst the diaspora population, lack of material incentives, and the length and subject matter of the survey itself. The SMS/WhatsApp messaging integration was relatively complex and limited the information we could send potential participants. CONCLUSION: Despite lower-than expected survey uptake we believe our webRDS solution provides efficient and flexible means to survey a globally diverse population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02217-0.
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spelling pubmed-103209372023-07-06 Design and implementation of a web-based, respondent-driven sampling solution McGowan, Catherine R. Ekoriko, Promise Alhaffar, Mervat Cassidy-Seyoum, Sarah Whitbread, Steven Rogers, Phil Bell, Lucy Checchi, Francesco BMC Med Inform Decis Mak Software BACKGROUND: Respondent-driven sampling (RDS) refers both to a chain-referral sampling method and an analytical model for analysing sampled data. Web-based respondent-driven sampling (webRDS) uses internet-based recruitment coupled with an electronic survey to carry out RDS studies; there is currently no commercially available webRDS solution. We designed and developed a webRDS solution to support a research study aimed at estimating conflict-attributable mortality in Yemen. Our webRDS solution is composed of an existing survey platform (i.e. ODK) and a bespoke RDS system. The RDS system is designed to administer and manage an RDS survey cascade and includes: (1) an application programming interface, (2) a study participant client, and (3) an administrator interface. We report here on the design of the webRDS solution and its implementation. RESULTS: We consulted members of the Yemeni diaspora throughout the development of the solution. Technical obstacles were largely the result of: WhatsApp’s policies on bulk messaging and automated messaging behaviour, the inherent constraints of SMS messaging, and SMS filtering behaviour. Language support was straight-forward yet time consuming. Survey uptake was lower than expected. Factors which may have impacted uptake include: our use of consumable survey links, low interest amongst the diaspora population, lack of material incentives, and the length and subject matter of the survey itself. The SMS/WhatsApp messaging integration was relatively complex and limited the information we could send potential participants. CONCLUSION: Despite lower-than expected survey uptake we believe our webRDS solution provides efficient and flexible means to survey a globally diverse population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02217-0. BioMed Central 2023-07-05 /pmc/articles/PMC10320937/ /pubmed/37407971 http://dx.doi.org/10.1186/s12911-023-02217-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
McGowan, Catherine R.
Ekoriko, Promise
Alhaffar, Mervat
Cassidy-Seyoum, Sarah
Whitbread, Steven
Rogers, Phil
Bell, Lucy
Checchi, Francesco
Design and implementation of a web-based, respondent-driven sampling solution
title Design and implementation of a web-based, respondent-driven sampling solution
title_full Design and implementation of a web-based, respondent-driven sampling solution
title_fullStr Design and implementation of a web-based, respondent-driven sampling solution
title_full_unstemmed Design and implementation of a web-based, respondent-driven sampling solution
title_short Design and implementation of a web-based, respondent-driven sampling solution
title_sort design and implementation of a web-based, respondent-driven sampling solution
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320937/
https://www.ncbi.nlm.nih.gov/pubmed/37407971
http://dx.doi.org/10.1186/s12911-023-02217-0
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