Publication type
Understanding Society Working Paper Series
Series Number
2025-07
Series
Understanding Society Working Paper Series
Authors
Publication date
June 13, 2025
Abstract:
Digital trace data — including from smartphone apps — are increasingly considered for research use, either as adjuncts to survey data or on their own. Understanding selection of smartphone app usage is therefore important in considering the potential of the data they generate for research purposes. We use data from the Understanding Society COVID study, which asked about uptake of the UK COVID contact tracing apps, to investigate (1) selection rates across stages of using the app, including smartphone ownership, smartphone compatibility with the app, app installation, and app use, (2) associated selection biases, and (3) reasons for not installing the app. To examine selection rates, we report population estimates of the percentages who reach various stages. Bias is analyzed by examining differences between characteristics of the overall sample and the sub-samples at the different stages of app use. We report population estimates of reasons for not installing the app. We find multiple contributions to substantial overall losses to selection, with only 36% consistently using the app. Biases by socio-demographic and health groups are generally moderate, with the largest biases in app downloads being around 10-11 percentage points for certain categories of age, education, and a measure of digital use. The most common reported reasons for not using the app are that they were taking precautions (33%) or privacy/trust concerns (24%). While derived from survey data about COVID tracing apps, these findings provide broader insights into likely issues of selection and bias when considering smartphone digital trace data for research.
Subjects
#588649