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Methods for Evaluating Respondent Attrition in Web-Based Surveys

BACKGROUND: Electronic surveys are convenient, cost effective, and increasingly popular tools for collecting information. While the online platform allows researchers to recruit and enroll more participants, there is an increased risk of participant dropout in Web-based research. Often, these dropou...

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Detalles Bibliográficos
Autores principales: Hochheimer, Camille J, Sabo, Roy T, Krist, Alex H, Day, Teresa, Cyrus, John, Woolf, Steven H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5141338/
https://www.ncbi.nlm.nih.gov/pubmed/27876687
http://dx.doi.org/10.2196/jmir.6342
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author Hochheimer, Camille J
Sabo, Roy T
Krist, Alex H
Day, Teresa
Cyrus, John
Woolf, Steven H
author_facet Hochheimer, Camille J
Sabo, Roy T
Krist, Alex H
Day, Teresa
Cyrus, John
Woolf, Steven H
author_sort Hochheimer, Camille J
collection PubMed
description BACKGROUND: Electronic surveys are convenient, cost effective, and increasingly popular tools for collecting information. While the online platform allows researchers to recruit and enroll more participants, there is an increased risk of participant dropout in Web-based research. Often, these dropout trends are simply reported, adjusted for, or ignored altogether. OBJECTIVE: To propose a conceptual framework that analyzes respondent attrition and demonstrates the utility of these methods with existing survey data. METHODS: First, we suggest visualization of attrition trends using bar charts and survival curves. Next, we propose a generalized linear mixed model (GLMM) to detect or confirm significant attrition points. Finally, we suggest applications of existing statistical methods to investigate the effect of internal survey characteristics and patient characteristics on dropout. In order to apply this framework, we conducted a case study; a seventeen-item Informed Decision-Making (IDM) module addressing how and why patients make decisions about cancer screening. RESULTS: Using the framework, we were able to find significant attrition points at Questions 4, 6, 7, and 9, and were also able to identify participant responses and characteristics associated with dropout at these points and overall. CONCLUSIONS: When these methods were applied to survey data, significant attrition trends were revealed, both visually and empirically, that can inspire researchers to investigate the factors associated with survey dropout, address whether survey completion is associated with health outcomes, and compare attrition patterns between groups. The framework can be used to extract information beyond simple responses, can be useful during survey development, and can help determine the external validity of survey results.
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spelling pubmed-51413382016-12-12 Methods for Evaluating Respondent Attrition in Web-Based Surveys Hochheimer, Camille J Sabo, Roy T Krist, Alex H Day, Teresa Cyrus, John Woolf, Steven H J Med Internet Res Original Paper BACKGROUND: Electronic surveys are convenient, cost effective, and increasingly popular tools for collecting information. While the online platform allows researchers to recruit and enroll more participants, there is an increased risk of participant dropout in Web-based research. Often, these dropout trends are simply reported, adjusted for, or ignored altogether. OBJECTIVE: To propose a conceptual framework that analyzes respondent attrition and demonstrates the utility of these methods with existing survey data. METHODS: First, we suggest visualization of attrition trends using bar charts and survival curves. Next, we propose a generalized linear mixed model (GLMM) to detect or confirm significant attrition points. Finally, we suggest applications of existing statistical methods to investigate the effect of internal survey characteristics and patient characteristics on dropout. In order to apply this framework, we conducted a case study; a seventeen-item Informed Decision-Making (IDM) module addressing how and why patients make decisions about cancer screening. RESULTS: Using the framework, we were able to find significant attrition points at Questions 4, 6, 7, and 9, and were also able to identify participant responses and characteristics associated with dropout at these points and overall. CONCLUSIONS: When these methods were applied to survey data, significant attrition trends were revealed, both visually and empirically, that can inspire researchers to investigate the factors associated with survey dropout, address whether survey completion is associated with health outcomes, and compare attrition patterns between groups. The framework can be used to extract information beyond simple responses, can be useful during survey development, and can help determine the external validity of survey results. JMIR Publications 2016-11-22 /pmc/articles/PMC5141338/ /pubmed/27876687 http://dx.doi.org/10.2196/jmir.6342 Text en ©Camille J Hochheimer, Roy T Sabo, Alex H Krist, Teresa Day, John Cyrus, Steven H Woolf. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.11.2016. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Hochheimer, Camille J
Sabo, Roy T
Krist, Alex H
Day, Teresa
Cyrus, John
Woolf, Steven H
Methods for Evaluating Respondent Attrition in Web-Based Surveys
title Methods for Evaluating Respondent Attrition in Web-Based Surveys
title_full Methods for Evaluating Respondent Attrition in Web-Based Surveys
title_fullStr Methods for Evaluating Respondent Attrition in Web-Based Surveys
title_full_unstemmed Methods for Evaluating Respondent Attrition in Web-Based Surveys
title_short Methods for Evaluating Respondent Attrition in Web-Based Surveys
title_sort methods for evaluating respondent attrition in web-based surveys
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5141338/
https://www.ncbi.nlm.nih.gov/pubmed/27876687
http://dx.doi.org/10.2196/jmir.6342
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