Understanding and improving data linkage consent in surveys
This research programme builds on findings from in-depth interviews that explored how people decide whether or not to give consent to link government administrative data to their responses in the Understanding Society survey:
- Beninger, Digby, Dillon, and MacGregor “Understanding Society: how people decide whether to give consent to link their administrative and survey data” Understanding Society Working Paper 2017-13. Colchester: University of Essex.
We have expanded and written up the initial analyses that motivated this project: on how (in)consistent people’s consent decisions are between domains and over time, how the mode of data collection affects consent, and insights on these findings from the qualitative interviews:
- Jäckle, Beninger, Burton, and Couper “Understanding data linkage consent in longitudinal surveys”, Understanding Society Working Paper 2018-07. Colchester: University of Essex.
One of the most promising avenues for empirical social science research involves linking administrative or process generated data with survey data. Administrative data (whether held by government or private entities) are useful on their own, but will be much more useful if we can use surveys to “fill the gaps”. Sometimes the gaps will be specific types of information (e.g. administrative data do not contain information on expectations or subjective wellbeing), and sometimes it will be to provide a suitable frame to allow inference to the general population (especially in the UK where there is not an appropriate individual identifier, or register, to provide a frame).
In the UK, survey data can only be linked to administrative or other process generated data, if survey respondents give informed consent to the linkage. Previous research suggests that people do not have strong fixed views on consent and that the decision to consent can be influenced.
The overall aim of this project is to maximise truly informed consent to data linkage. The specific aims are to:
Understand how respondents process requests for data linkage: which factors influence their understanding of data linkage, which factors influence their decision to consent, and why respondents change their mind about consent.
Develop and test methods of maximising consent in web surveys, by understanding why web respondents are less likely to give consent than face-to-face respondents.
Develop and test methods of maximising consent with requests for linkage to multiple data sets, by understanding how respondents process multiple requests.
We will design survey question experiments to test whether different features of the consent request are effective for different types of people, to measure the respondent decision-making process, to ascertain how informed the consent decision is, whether and how informed consent varies with the experimental treatments and respondent characteristics, and how it differs between face-to-face interviews and self-completion web surveys.
Professor of Survey Methodology - ISER, University of Essex
Professor of Economics - University of Essex
Associate Director, Surveys - ISER, University of Essex
Research Professor - Survey Research Centre, University of Michigan
PhD student in Survey Methodology - ISER, University of Essex
Ms Sina Chen
Placement student - ISER, University of Essex