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Svenja Pieritz

dblp:284/0565 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 77% Human-AI interaction · 23%
Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies › mental health technology
mental health apps
0.512021
Personalised Recommendations in Mental Health Apps: The Impact of Autonomy and Data Sharing · CHI 2021

Methods — techniques the papers use, named apart from their topics

user study · 1.0
YearPublicationVenuePosition
2021 Personalised Recommendations in Mental Health Apps: The Impact of Autonomy and Data Sharing
Svenja Pieritz, Mohammed Khwaja, A. Aldo Faisal, Aleksandar Matic
CHI1
2021 Personality and Engagement with Digital Mental Health Interventions
abstract
Personalisation is key to creating successful digital health applications. Recent evidence links personality and preference for digital experience — suggesting that psychometric traits can be a promising basis for personalisation of digital mental health services. However, there is still little quantitative evidence from actual app usage. In this study, we explore how different personality types engage with different intervention content in a commercial mental health application. Specifically, we collected the Big Five personality traits alongside the app usage data of 126 participants using a mobile mental health app for seven days. We found that personality traits significantly correlate with the engagement and user ratings of different intervention content. These findings open a promising research avenue that can inform the personalised delivery of digital mental health content and the creation of recommender systems, ultimately improving the effectiveness of mental health interventions.
Mohammed Khwaja, Svenja Pieritz, A. Aldo Faisal, Aleksandar Matic
UMAP2