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ARS Home » Southeast Area » Little Rock, Arkansas » Arkansas Children's Nutrition Center » Research » Publications at this Location » Publication #369221

Research Project: Impact of Maternal Influence and Early Dietary Factors on Child Growth, Development, and Metabolic Health

Location: Arkansas Children's Nutrition Center

Title: Interactive and dynamic statistical reports using R shiny apps integrated with REDCap: Example from Arkansas Active Kids study

item HU, ZHUOPEI - University Arkansas For Medical Sciences (UAMS)
item NICK, JULIE - Arkansas Children'S Nutrition Research Center (ACNC)
item GOUDIE, ANTHONY - University Arkansas For Medical Sciences (UAMS)
item BOSHEIM, ELISABET - University Arkansas For Medical Sciences (UAMS)
item WEBER, JUDITH - University Arkansas For Medical Sciences (UAMS)
item BAI, SHASHA - The Ohio State University

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 9/27/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: R Shiny combines the power of R computing and JAVA visualization to build interactive web apps. REDCap (Research Electronic Data Capture) is a well-established secure data collection tool for managing surveys and database. Arkansas Active Kids (AAK) study is a study aims to investigate the relationship between physical activity, physical fitness, diet and metabolic factors in prepubertal children. We use AAK study as an example to demonstrate the periodic and repeated generation of interactive statistical reports to showcase the progress of recruitment and lab visit. One longitudinal REDCap project with multiple events was created to conduct data collection which includes screening, lab visit, surveys, daily logs, and lab measurements. An API token was used to load all the data into the R environment. A dynamic Shiny App containing multiple webpages showcases a comprehensive report of recruitment figures, study progress figures and other analysis tables. By using R Shiny integrated with REDCap, we created a streamlined way to show the recruitment progress to investigators while increasing programming efficiency and maintaining reproducibility.