Challenges and Consequences of Switching Face-to-Face Population Surveys to Self-Completion (Mixed-Mode) Designs 1
|Coordinator 1||Dr Joss Roßmann (GESIS - Leibniz Institute for the Social Sciences, Germany)|
|Coordinator 2||Mr Michael Blohm (GESIS - Leibniz Institute for the Social Sciences, Germany)|
|Coordinator 3||Ms Caroline Hahn (GESIS - Leibniz Institute for the Social Sciences, Germany)|
|Coordinator 4||Dr Oshrat Hochman (GESIS - Leibniz Institute for the Social Sciences, Germany)|
|Coordinator 5||Dr Jan-Lucas Schanze (GESIS - Leibniz Institute for the Social Sciences, Germany)|
The public health regulations that were introduced across Europe (and beyond) since Spring 2020 due to the Corona pandemic impeded the realization of personal face-to-face survey data collection or made it even temporarily impossible – potentially with long ranging consequences for this data collection method. For this reason, surveys of the general population, or important subgroups of the population such as voters, chose to switch from face-to-face interviewing to a mix of self-completion survey modes to secure survey responses from all groups of the target population (e.g., respondents without Internet access or those unwilling to respond in a certain mode).
The Corona pandemic, thus, strongly accelerated a continuing trend of moving surveys from interviewer-administration to self-completion modes. With respect to the general trend and the sustained consequences of the Coronavirus in particular, we welcome submissions that present insights on the methodological and practical challenges of switching population surveys from face-to-face to (mixes of) self-completion modes, and on the effects of doing so on the quality of the data.
Contributions may cover but are not limited to the following research topics:
- Approaches to overcome methodological and practical challenges of switching modes (e.g., regarding sampling and coverage)
- Conception and implementation of self-completion mixed-mode designs for general population surveys (e.g., adaptations in questionnaire design)
- Experimental testing of survey designs to maintain or enhance response and quality of measurement (e.g., use of conditional and unconditional incentives, split questionnaire designs)
- Consequences of switches to self-completion on data quality and total survey error
- Implications of mixing self-completion data collection modes on measurement invariance and possible remedies
- Impact of switching data collection modes on time series in repeated cross-section and panel population surveys