Unknown: Hello everyone, today we'll present to you the paper
understanding users' perception of personalisation, autonomy and
data sharing in a mental wellbeing application. My name
is Svenja Pieritz. This work was in collaboration with Mohammed
Khwaja, who equally contributed to his research. We also work
together with Aldo Faisal and Aleksandar Matic.
Digital mental wellbeing interventions are aiming to
reduce the global shortage of mental health care professionals
and a cost effective and scalable manner. The covid 19
pandemic and its impact on mental health has accelerated
research and development of new interventions and content in the
digital mental health sector. The increasing amount of content
made recommender systems more and more relevant and popular,
although personalised recommendations are very helpful
for users in terms of choice overload, delivering those
recommendations entails two main challenges. Firstly, how to
balance autonomy and guidance. In a traditional setting for the
selection of the right interventions, autonomy is
secondary to the expertise of the medical professionals.
However, in digital experiences, autonomy was shown to be an
essential design criterion to create engagement. The second
challenge is the way of data sharing. Personalising the user
experience typically requires personal data to be shared,
which may impact the manner in which users interact with the
app.
We decided to look at these two challenges in our study and
formulate two research questions each. In terms of data, we
decided to look at both preferences and also app
behaviours that we found in user logs. So firstly, for the degree
of autonomy, do users prefer an autonomous or guided experience?
And then does any of these two experiences impact in behaviours
of users? Then for data sharing, we decided to go with a
personality based recommender system. So our preference
question was, do users prefer to get personality traits inferred
from mobile data? Or do they prefer to fill out a
questionnaire themselves? And then secondly, for behaviour do
those two different ways of data sharing impact in app
behaviours?
We were really lucky that we have the possibility to work
with a real world commercial app. foundations is an evidence
based mental health platform designed to improve users
resilience and decrease stress levels. At the time of the
study, the version of the app incorporated 10 modules with 102
activities in total.
The homescreen contains a section called other activities
for you, which has a recommendation of two activities
at a time, you can see that on the left. In our study, these
recommendations were random. So actually not personalised, even
though we told our subjects that they were personalised based on
their personality traits.
Here you can see our experimental design. Our study
consisted of three main parts. Firstly, the onboarding
questionnaire, which was followed by in app usage for
seven days with daily reminders, and finally an exit
questionnaire. As the goal was to investigate the effect of the
two variables autonomy and preferred way of data sharing,
we designed a two factor factorial experiment with two
levels of data sharing being questionnaire and data modality
selection, and two levels of priming for an either primarily
autonomous or primarily guided experience. All this led to four
experimental groups plus one control group that could be
combined according to the variables that they have in
common. We had a total of 218 participants with over 40 per
group.
However, when analysing the actual app usage, we found no
impact of the data source and how people interact with the
app.
Interestingly, the time taken for completing a personality
questionnaire, which, which had 10 items, was comparable to the
duration of completing a form to obtain consent for the usage of
what smartphone data. So this shows that a questionnaire could
be a valid option for the personalization of mental health
applications in the future. That was it. Thank you very much.