Document Type
Article
Original Publication Date
2019
Journal/Book/Conference Title
Journal of Medical Internet Research
Volume
21
Issue
8:e12811
First Page
1
Last Page
9
DOI of Original Publication
10.2196/12811
Date of Submission
October 2019
Abstract
Background: Although Web-based questionnaires are an efficient, increasingly popular mode of data collection, their utility is often challenged by high participant dropout. Researchers can gain insight into potential causes of high participant dropout by analyzing the dropout patterns.
Objective: This study proposed the application of and assessed the use of user-specified and existing hypothesis testing methods in a novel setting—survey dropout data—to identify phases of higher or lower survey dropout.
Methods: First, we proposed the application of user-specified thresholds to identify abrupt differences in the dropout rate. Second, we proposed the application of 2 existing hypothesis testing methods to detect significant differences in participant dropout. We assessed these methods through a simulation study and through application to a case study, featuring a questionnaire addressing decision-making surrounding cancer screening.
Results: The user-specified method set to a low threshold performed best at accurately detecting phases of high attrition in both the simulation study and test case application, although all proposed methods were too sensitive.
Conclusions: The user-specified method set to a low threshold correctly identified the attrition phases. Hypothesis testing methods, although sensitive at times, were unable to accurately identify the attrition phases. These results strengthen the case for further development of and research surrounding the science of attrition.
Rights
© Camille J Hochheimer, Roy T Sabo, Robert A Perera, Nitai Mukhopadhyay, Alex H Krist. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The complete bibliographic information, a link to the original publication, as well as this copyright and license information must be included.
Is Part Of
VCU Biostatistics Publications
Comments
Originally published at https://doi.org/10.2196/12811
Funded in part by the VCU Libraries Open Access Publishing Fund.