Hello everyone. I'm joonyoung, a PhD student at KAIST. Today I'll introduce my research
GoldenTime. This is a study on digital well-being. Digital well-being is about personal well-being
relate to healthy use of digital technology. To promote healthy device usage prior studies
on digital wellbeing tried to design systems helping users regulate the devices.
And among many studies on digital well-being, this study is about smartphone usage regulation.
Even though the smartphone itself provides many conveniences to us
prior studies highlighted the negative impacts on our daily life. To deal with this there has
been approaches that associate problematic phone usage with the lack of time management skills.
One of represent study is PomodoLock. It utilizes timeboxing, one of time management
techniques to manage self-interruption for digital devices. It was designed with
user-driven timeboxing that can be enforced and stopped by user. Such user-driven tool
offers autonomy to users but the authors warned the lack of user engagement over time. Because
user-driven timeboxing can be only started by user so if there's no user's internal trigger
or they forget to use it, it will not be used anymore. So, in this study, we considered
system-driven time boxing automatically enforced by system. By this operation
it can continuously providing trigger to users so that they can easily track usage behaviors.
Under this timeboxing we also utilized financial incentives as motivator. We considered design
providing rewards for successful timebox. This approach is aligned with BJ FOGG behavior model.
By using these two features together, we designed a system that helps users
easily and continuously track usage behaviors as well as reinforce motivation for the regulation.
Through this, we try to make them realize the monetary value of their phone usage time. So we
called our system GoldenTime. First, we explored the system design. Our system-driven timeboxing
automatically enforce the timebox every hour on the hour with a 10 minutes use limit.
And if users use their phone, it measures their usage time in each time box. Based on
the measurement the timeboxing determines the regulation success or failure. And the system
informs the results through the notification bar so that users can easily track their behaviors.
Under the timeboxing, we design two incentive payment framing, gain,
and loss. In the game frame, users get 500 gold for each successful timebox. In the loss frame,
if users fail to regulate for each timebox, the same incentives are deducted.
We built an intervention system delivering a warning message for regulation failure.
In each time box if accumulated usage time exceeds 9 minutes, the message is sent to the user.
In this process, the message for each incentive group additionally includes warnings related
to the incentive. We hypothesized that the last frame would be more effective in sustaining phone
regulation based on the endowment effect and loss aversion of behavioral economics.
We evaluate our system through the user study. We compared how the daily average
of usage time was changed. In the baseline, no significant differences between three groups.
But during the intervention periods, there were significant differences between the loss and other
groups. We further investigate how two different incentive framings influence usage regulation
over time. In the gain group, usage regulation success influenced increasing the monetary value
of the regulation. But when they failed in the regulation, they tend to rationalize themselves.
This phenomenon results from perceiving the micro-incentive as an infinite opportunity.
As a result, such experiences influence decreasing the monetary value of regulation,
thereby causing devaluation over time. However, in the lost group,
when they failed in the regulation, they tend to reflect their problematic usage behavior. Because
through this process they realized the cost of the behavior and wasted time. As a result, the process
influenced increasing the monetary value of the regulation, thereby causing revaluation over time.
If you're interested in further details, please refer to our paper. Thank you for your attention.