Time: Tuesday, 01/Apr/2025: 3:45pm - 4:45pm Session Chair: Georg-Christoph Haas, Institute for Employment Research, Germany |
Location: Hörsaal B |
Knock-to-nudge methods to improve survey participation in the UK
University of Southampton, United Kingdom
Relevance & Research Question
The knock-to-nudge is an innovative method of household contact, first introduced during the COVID-19 pandemic when face-to-face interviewing was not possible. In this approach, interviewers visit households and encourage sampled units to participate in a survey through a remote survey mode (either web or telephone) at a later date. Interviewers may also collect contact information, such as telephone numbers or email addressed, or conduct within-household selection of individuals on the doorstep. This approach continued to be used post-pandemic, but there remains a knowledge gap regarding its advantages and disadvantages. It is still unclear whether knock-to-nudge approach leads to improvements in sample composition and data quality.
Methods & Data
We analyse data from three UK surveys: the National Survey for Wales (NSW), the Transformed Labour Force Survey (TLFS), and the National Readership Survey (PAMCo), each of which employed different versions of the knock-to-nudge approach. Our goal is to assess whether this method improves sample composition across these three surveys. We begin with descriptive analysis and then apply logistic regression models to investigate the composition of subsamples that received different recruitment treatments. Finally, we compare the sample composition at various stages of the recruitment process.
Results
Our findings suggest that the knock-to-nudge approach is effective in improving sample composition, while also reducing costs compared to traditional face-to-face interviews.
Added Value
This study contributes to the under-researched area of knock-to-nudge methods. The results indicate that, when carefully designed and implemented, this approach can enhance recruitment efforts and improve sample composition of the resulting samples in surveys.
Recruitment incentive experiment of the probability-based panel Health in Germany: results on outcome rates, non-response bias and panel case costs
1Robert Koch-Institut, Germany; 2infas Institut für angewandte Sozialwissenschaft GmbH
Relevance & Research Question
The Robert Koch Institute (RKI) set up a probability-based panel infrastructure focused on public health research (‘Health in Germany’) (registered active panelists about 47.000). Due to declining response rates in recent decades, incentives have become increasingly important. Incentive experiments are therefore often carried out in order to achieve high data quality with a lower use of resources. Therefore, for the first recruitment study of the panel Health in Germany the RKI conducted an incentive experiment with a random sub-sample in order to test the effectiveness of different incentive schemes. The central questions of the incentive experiment are: Differentiated by incentive group (a) the response rate for panel registration, (b) the possible distortion due to non-response bias and (c) the panel case costs.
Methods & Data
The study population comprises all persons aged 16 and over living in Germany. Around 170,000 addresses of the residents' registration offices were used as a random sample. The field period ran from January to May 2024. Some of the target persons were randomly selected for an incentive experiment with four groups of 1440 individuals each. The incentives were either paid unconditionally beforehand (‘before’) or were linked to registration for the panel (‘after’). The incentive schemes of the groups were: (1) €5 before, €10 after, in cash; (2) €10 after, in cash; (3) €5 before, €10 after, as a voucher; (4) no incentive at all (control group).
Results
The incentive experiment replicates existing incentive experiment studies. The use of cash instead of vouchers and the unconditional payment (‘in advance’) of €5 substantially increases the willingness to participate (about 12 percentage points difference). Particularly in the hard-to-reach population group of people with a low level of education, a less biased sample composition can be observed in comparison to all other incentive groups.
Added Value
The results of the incentive experiment provide insights into how high data quality can be achieved with fewer resources. In view of the large number of cases and probabilistic sampling, the findings can be transferred to similar epidemiological research projects.