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A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management
Capturing high-quality survey data is an arduous process for large-scale and extensive interventional studies. This paper presents the architecture, interface design, and an innovative form generation engine of a system called RE- Form: Refactorized Electronic Web Forms. REForm provides researchers...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Informatics Association
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543388/ https://www.ncbi.nlm.nih.gov/pubmed/28815142 |
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author | Tao, Shiqiang Zeng, Ningzhou Wu, Xi Li, Xiaojin Zhu, Wei Cui, Licong Zhang, GQ |
author_facet | Tao, Shiqiang Zeng, Ningzhou Wu, Xi Li, Xiaojin Zhu, Wei Cui, Licong Zhang, GQ |
author_sort | Tao, Shiqiang |
collection | PubMed |
description | Capturing high-quality survey data is an arduous process for large-scale and extensive interventional studies. This paper presents the architecture, interface design, and an innovative form generation engine of a system called RE- Form: Refactorized Electronic Web Forms. REForm provides researchers the capability to design and manage surveys and the flexibility to organize them in a customizable workflow. REForm has been designed, implemented, pilot-tested and deployed for an NCI-funded interventional study IMPACT. It enables IMPACT to design and conduct a baseline survey of 95 questions with 662 options, a post-intervention survey of 82 questions with 574 options, six Ecological Momentary Assessment (EMA) surveys including four questions and 26 options each, and a follow-up survey con- taining 15 questions and 125 options. Feedback designed in the post-intervention survey showed that more than 94 percent of IMPACT participants highly endorsed the design and usability of the surveys created using REForm. |
format | Online Article Text |
id | pubmed-5543388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | American Medical Informatics Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-55433882017-08-16 A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management Tao, Shiqiang Zeng, Ningzhou Wu, Xi Li, Xiaojin Zhu, Wei Cui, Licong Zhang, GQ AMIA Jt Summits Transl Sci Proc Articles Capturing high-quality survey data is an arduous process for large-scale and extensive interventional studies. This paper presents the architecture, interface design, and an innovative form generation engine of a system called RE- Form: Refactorized Electronic Web Forms. REForm provides researchers the capability to design and manage surveys and the flexibility to organize them in a customizable workflow. REForm has been designed, implemented, pilot-tested and deployed for an NCI-funded interventional study IMPACT. It enables IMPACT to design and conduct a baseline survey of 95 questions with 662 options, a post-intervention survey of 82 questions with 574 options, six Ecological Momentary Assessment (EMA) surveys including four questions and 26 options each, and a follow-up survey con- taining 15 questions and 125 options. Feedback designed in the post-intervention survey showed that more than 94 percent of IMPACT participants highly endorsed the design and usability of the surveys created using REForm. American Medical Informatics Association 2017-07-26 /pmc/articles/PMC5543388/ /pubmed/28815142 Text en ©2017 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose |
spellingShingle | Articles Tao, Shiqiang Zeng, Ningzhou Wu, Xi Li, Xiaojin Zhu, Wei Cui, Licong Zhang, GQ A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management |
title | A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management |
title_full | A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management |
title_fullStr | A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management |
title_full_unstemmed | A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management |
title_short | A Data Capture Framework for Large-scale Interventional Studies with Survey Workflow Management |
title_sort | data capture framework for large-scale interventional studies with survey workflow management |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543388/ https://www.ncbi.nlm.nih.gov/pubmed/28815142 |
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