| Abstract: |
Smartphones are now ubiquitous in daily life, requiring the development of
accurate methodologies to study their impact on various aspects of human
experience. A promising approach to collect mobile log data is to ask
participants to donate, in the context of online surveys, the data that is
already available to them through features such as iOS Screen Time and Android
Digital Wellbeing. This approach grants participants control over the data
they share while providing researchers with valuable observational insights
into their mobile and app behaviours. However, the active involvement required
from participants poses challenges, leading to low compliance rates and
potential biases in the final sample of donors. This study investigates
whether the method used to collect data donations, and the incentives
provided, have an impact on compliance rates, and the subsequent composition
of the sample. Specifically, we implemented a 2 x 3 between-subject web survey
experiment (N = 872) in a research-led probability-based panel in Switzerland.
Participants were randomly asked to capture and share their data through
screenshots, video recordings, and by manual imputation (which we call
enhanced recall). Results show that, while compliance rates are very low when
using screenshots and video recordings as data donation methods, almost two
thirds of participants donated their data by manually imputing their log data.
The methods also differ in terms of sample composition, with enhanced recall
introducing fewer biases. Overall, our study sheds light on maximizing
compliance in data donation studies, offering insights for researchers
studying mobile and app usage. |