TY - GEN
T1 - Wearable-Based Mental Health Monitoring Platforms
T2 - 16th International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, DHM 2025, held as part of the 27th HCI International Conference, HCII 2025
AU - Kittelmann, Luca
AU - Reindl-Spanner, Philipp
AU - Prommegger, Barbara
AU - Gensichen, Jochen
AU - Krcmar, Helmut
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - The increasing adoption of wearable-based mental health monitoring platforms offers significant potential to enhance patient care and support general practitioners. Because mental health platforms rely on continuous data collection and clinician adoption, effective onboarding is crucial for ensuring long-term adherence and usability. However, onboarding remains a challenge due to the diverse technological proficiencies of users, the complexity of integrating patient-generated health data into clinical workflows, and the necessity of sustaining user engagement. This study develops an onboarding concept for wearable-based mental health monitoring platforms and iteratively derives principles for designing such a concept, focusing on modularity, flexibility, and seamless integration into clinical practice. The resulting design principles highlight (1) modular onboarding to address varying user needs, (2) a hybrid approach to optimize flexibility and resource efficiency, and (3) supervised experimentation to build user confidence through structured hands-on learning. These principles provide actionable insights for designing scalable, user-centered onboarding frameworks in mental health monitoring.
AB - The increasing adoption of wearable-based mental health monitoring platforms offers significant potential to enhance patient care and support general practitioners. Because mental health platforms rely on continuous data collection and clinician adoption, effective onboarding is crucial for ensuring long-term adherence and usability. However, onboarding remains a challenge due to the diverse technological proficiencies of users, the complexity of integrating patient-generated health data into clinical workflows, and the necessity of sustaining user engagement. This study develops an onboarding concept for wearable-based mental health monitoring platforms and iteratively derives principles for designing such a concept, focusing on modularity, flexibility, and seamless integration into clinical practice. The resulting design principles highlight (1) modular onboarding to address varying user needs, (2) a hybrid approach to optimize flexibility and resource efficiency, and (3) supervised experimentation to build user confidence through structured hands-on learning. These principles provide actionable insights for designing scalable, user-centered onboarding frameworks in mental health monitoring.
KW - Mental Health Monitoring Platform
KW - Onboarding
KW - Patient Generated Health Data
KW - Wearables
UR - https://www.scopus.com/pages/publications/105007842212
U2 - 10.1007/978-3-031-93505-3_13
DO - 10.1007/978-3-031-93505-3_13
M3 - Conference contribution
AN - SCOPUS:105007842212
SN - 9783031935046
T3 - Lecture Notes in Computer Science
SP - 192
EP - 209
BT - Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management - 16th International Conference, DHM 2025, Held as Part of the 27th HCI International Conference, HCII 2025, Proceedings
A2 - Duffy, Vincent G.
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 22 June 2025 through 27 June 2025
ER -