| Abstract |
Sleep insufficiency is known to have serious negative consequences for
people's health and well-being, as it puts people at risk for developing
diabetes, obesity, cancer, cardiovascular disease and neuropsychiatric
diseases. Recent studies in the social sciences (e.g., Kroese et al.,
2014) have shown that sleep insufficiency in the general population is
due in part to _bedtime procrastination_, which has been defined as
"needlessly and voluntarily delaying going to bed, despite foreseeably
being worse off as a result" (Kroese et al., 2016). In my first WAI
talk, my aim is to give an overview of the domain of bedtime
procrastination and present some ideas for gaining more insight into the
phenomenon and possible interventions using techniques from machine
learning, for example to distinguish different types of bedtime
procrastinators and to identify temporal patterns of behavior that are
predictive of bedtime procrastination. My hope is to stimulate
discussion about these ideas and to start a conversation about possible
collaborations within this domain. |