Do respondents using smartphones produce lower quality data? Evidence from the UK Understanding Society mixed-device survey
Maslovskaya, Olga and Smith, Peter and Durrant, Gabriele (2024) Do respondents using smartphones produce lower quality data? Evidence from the UK Understanding Society mixed-device survey. International Journal of Social Research Methodology, 1-14. ISSN 1464-5300 (electronic) 1364-5579 (paper)
Full text not available from this repository.Abstract
Some social surveys in the UK have either transitioned to online data collection or are in the process of transitioning. The COVID-19 pandemic forced rapid moves to online data collection for some surveys. There are still some concerns regarding the quality of data produced by respondents using smartphones for survey questionnaire completion.
This paper uses the first available in the UK, large-scale mixed-device survey, Understanding Society Wave 8, where 40% of the sample were assigned to an online mode of data collection. It allows comparison of data quality between different devices. Different data quality and differential reporting indicators are assessed.
The results suggest that even when the questionnaire is not optimised for a smartphone, we should not be concerned about respondents using smartphones in social surveys, even for longer surveys, such as Understanding Society, as break-off rates are very low and data quality between devices is not very different.
Item Type: | Article |
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Uncontrolled Keywords: | Cross-sectional context, data quality, data quality indicators, mixed-device online surveys, online survey |
Subjects: | 1. Frameworks for Research and Research Designs > 1.6 Survey Research 1. Frameworks for Research and Research Designs > 1.7 Cross-Sectional Research 1. Frameworks for Research and Research Designs > 1.20 Secondary Analysis 1. Frameworks for Research and Research Designs > 1.24 Frameworks for Research and Research Designs (other) 2. Data Collection > 2.11 Online Data Collection 5. Quantitative Data Handling and Data Analysis > 5.5 Regression Methods 5. Quantitative Data Handling and Data Analysis > 5.5 Regression Methods > 5.5.1 Ordinary least squares (OLS) 5. Quantitative Data Handling and Data Analysis > 5.5 Regression Methods > 5.5.2 Generalized liner model (GLM) |
Depositing User: | NCRM users |
Date Deposited: | 15 Sep 2021 09:15 |
Last Modified: | 18 Nov 2024 10:34 |
URI: | https://eprints.ncrm.ac.uk/id/eprint/4438 |