Designed big data: Augmenting surveys with sensors, apps, wearables, and data donation

Abstract

Traditional surveys are not well-equipped to measure certain concepts of interest such as expenditures, time use or travel behaviour due to high burden placed on participants.

Facts or behaviours that are difficult to measure through self-report can be measured using new technologies: smartphone apps, sensors, and wearables.

For example, accelerometers in smartphones and fitness bracelets can objectively measure physical activity, screen time apps can measure (social) media use.

Another possibility is to augment surveys with administrative data or data from digital platforms such as Google, YouTube, Instagram that participants can provide to researchers through data donation, or consent to data linkage.

However, to ensure representation, participants have to be willing and able to use their devices to perform such tasks.

If participants differ from nonparticipants in key outcomes, research results can be biased.

In this webinar, Bella Struminskaya (Utrecht University) will present the results of several randomized experiments on the mechanisms of willingness and consent to collect data using smartphone sensors, apps, and wearables in general population surveys.

The presentation will cover the extent of nonparticipation bias assessed by linkage of survey data to sensor and administrative data.

It will also focus on how these mechanisms translate to data donation of digital trace data, what opportunities and challenges such novel data collection methods hold for the social sciences and official statistics.