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Methods for Evaluating Respondent Attrition in Web-Based Surveys.

Camille J Hochheimer1, Roy T Sabo1, Alex H Krist2

  • 1Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, United States.

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|November 24, 2016
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Summary
This summary is machine-generated.

This study introduces a framework to analyze participant dropout in electronic surveys, identifying key attrition points and influencing factors. This helps researchers understand and mitigate survey attrition for more reliable data.

Keywords:
electronic health recordspatient dropoutssurveys and questionnaires

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Area of Science:

  • Health research methodology
  • Survey methodology
  • Statistical analysis

Background:

  • Electronic surveys offer convenience and cost-effectiveness but face challenges with participant attrition.
  • High dropout rates in web-based research can compromise data integrity.
  • Current practices often involve simply reporting or ignoring attrition trends.

Purpose of the Study:

  • To propose a conceptual framework for analyzing respondent attrition in electronic surveys.
  • To demonstrate the utility of this framework using existing survey data.
  • To identify significant attrition points and associated participant characteristics.

Main Methods:

  • Utilized visualization techniques like bar charts and survival curves to display attrition trends.
  • Employed a generalized linear mixed model (GLMM) to detect significant attrition points.
  • Applied statistical methods to investigate the impact of survey and patient characteristics on dropout.

Main Results:

  • Identified significant attrition points at specific questions (4, 6, 7, and 9) within the survey module.
  • Determined participant responses and characteristics linked to dropout at these points and overall.
  • Revealed significant attrition trends visually and empirically.

Conclusions:

  • The proposed framework enhances the understanding of survey dropout.
  • It aids in investigating factors influencing attrition and their impact on health outcomes.
  • The framework is valuable for survey development and assessing the external validity of findings.