Doing a Time Use Survey on Smartphones Only: What Factors Predict Nonresponse at Different Stages of the Survey Process?

Authors

  • Anne Elevelt Utrecht University
  • Peter Lugtig Utrecht University
  • Vera Toepoel Utrecht University

DOI:

https://doi.org/10.18148/srm/2019.v13i2.7385

Keywords:

Smartphone survey, nonresponse, sensor data, nonresponse bias, consent bias, time use research

Abstract

The increasing use of smartphones opens up opportunities for novel ways of survey data collection, but also poses new challenges. Collecting more and different types of data means that studies can become increasingly intrusive. We risk over-asking participants, leading to nonresponse. This study documents nonresponse and nonresponse bias in a smartphone-only version of the Dutch Time Use Survey (TUS). Respondents from the Dutch LISS panel were asked to perform five sets of tasks to complete the whole TUS: 1) accept an invitation to participate in the study and install an app, 2) fill out a questionnaire on the web, 3) participate in the smartphone time use diary on their smartphone, 4) answer pop-up questions and 5) give permission to record sensor data (GPS locations and call data). Results show that 42.9% of invited panel members responded positively to the invitation to participate in a smartphone survey. However, only 28.9% of these willing panel members completed all stages of the study. Predictors of nonresponse are somewhat different at every stage. In addition, respondents who complete all smartphone tasks are different from groups who do not participate at some or any stage of the study. By using data collected in previous waves we show that nonresponse leads to nonresponse bias in estimates of time use. We conclude by discussing implications for using smartphone apps in survey research.

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Published

2019-04-11

How to Cite

Elevelt, A., Lugtig, P., & Toepoel, V. (2019). Doing a Time Use Survey on Smartphones Only: What Factors Predict Nonresponse at Different Stages of the Survey Process?. Survey Research Methods, 13(2), 195–213. https://doi.org/10.18148/srm/2019.v13i2.7385

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