Shirin Jabbarzadeh, Lindsay M Jaacks, Amy Lovvorn, Yunyun Chen, Jiantong Wang, Lisa Elon, Azhar Nizam, Vigneswari Aravindalochanan, Jean de Dieu Ntivuguruzwa, Kendra N Willams, Alexander Ramirez, Michael A Johnson, Ajay Pillarisetti, Thangavel Gurusamy, Ghislaine Rosa, Anaité Diaz-Artiga, Juan C Romero, Kalpana Balakrishnan, William Checkley, Jennifer L Peel, Thomas F Clasen, Lance A Waller
{"title":"Data management plan and REDCap mobile data capture for a multi-country Household Air Pollution Intervention Network (HAPIN) trial.","authors":"Shirin Jabbarzadeh, Lindsay M Jaacks, Amy Lovvorn, Yunyun Chen, Jiantong Wang, Lisa Elon, Azhar Nizam, Vigneswari Aravindalochanan, Jean de Dieu Ntivuguruzwa, Kendra N Willams, Alexander Ramirez, Michael A Johnson, Ajay Pillarisetti, Thangavel Gurusamy, Ghislaine Rosa, Anaité Diaz-Artiga, Juan C Romero, Kalpana Balakrishnan, William Checkley, Jennifer L Peel, Thomas F Clasen, Lance A Waller","doi":"10.1177/20552076241274217","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Household air pollution (HAP) is a leading environmental risk factor accounting for about 1.6 million premature deaths mainly in low- and middle-income countries (LMICs). However, no multicounty randomized controlled trials have assessed the effect of liquefied petroleum gas (LPG) stove intervention on HAP and maternal and child health outcomes. The Household Air Pollution Intervention Network (HAPIN) was the first to assess this by implementing a common protocol in four LMICs.</p><p><strong>Objective: </strong>This manuscript describes the implementation of the HAPIN data management protocol via Research Electronic Data Capture (REDCap) used to collect over 50 million data points in more than 4000 variables from 80 case report forms (CRFs).</p><p><strong>Methods: </strong>We recruited 800 pregnant women in each study country (Guatemala, India, Peru, and Rwanda) who used biomass fuels in their households. Households were randomly assigned to receive LPG stoves and 18 months of free LPG supply (intervention) or to continue using biomass fuels (control). Households were followed for 18 months and assessed for primary health outcomes: low birth weight, severe pneumonia, and stunting. The HAPIN Data Management Core (DMC) implemented identical REDCap projects for each study site using shared variable names and timelines in local languages. Field staff collected data offline using tablets on the REDCap Mobile Application.</p><p><strong>Results: </strong>Utilizing the REDCap application allowed the HAPIN DMC to collect and store data securely, access data (near real-time), create reports, perform quality control, update questionnaires, and provide timely feedback to local data management teams. Additional REDCap functionalities (e.g. scheduling, data validation, and barcode scanning) supported the study.</p><p><strong>Conclusions: </strong>While the HAPIN trial experienced some challenges, REDCap effectively met HAPIN study goals, including quality data collection and timely reporting and analysis on this important global health trial, and supported more than 40 peer-reviewed scientific publications to date.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11342436/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DIGITAL HEALTH","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20552076241274217","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Household air pollution (HAP) is a leading environmental risk factor accounting for about 1.6 million premature deaths mainly in low- and middle-income countries (LMICs). However, no multicounty randomized controlled trials have assessed the effect of liquefied petroleum gas (LPG) stove intervention on HAP and maternal and child health outcomes. The Household Air Pollution Intervention Network (HAPIN) was the first to assess this by implementing a common protocol in four LMICs.
Objective: This manuscript describes the implementation of the HAPIN data management protocol via Research Electronic Data Capture (REDCap) used to collect over 50 million data points in more than 4000 variables from 80 case report forms (CRFs).
Methods: We recruited 800 pregnant women in each study country (Guatemala, India, Peru, and Rwanda) who used biomass fuels in their households. Households were randomly assigned to receive LPG stoves and 18 months of free LPG supply (intervention) or to continue using biomass fuels (control). Households were followed for 18 months and assessed for primary health outcomes: low birth weight, severe pneumonia, and stunting. The HAPIN Data Management Core (DMC) implemented identical REDCap projects for each study site using shared variable names and timelines in local languages. Field staff collected data offline using tablets on the REDCap Mobile Application.
Results: Utilizing the REDCap application allowed the HAPIN DMC to collect and store data securely, access data (near real-time), create reports, perform quality control, update questionnaires, and provide timely feedback to local data management teams. Additional REDCap functionalities (e.g. scheduling, data validation, and barcode scanning) supported the study.
Conclusions: While the HAPIN trial experienced some challenges, REDCap effectively met HAPIN study goals, including quality data collection and timely reporting and analysis on this important global health trial, and supported more than 40 peer-reviewed scientific publications to date.
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