Mental health issues affect a significant portion of the world's population and can result in debilitating and life-threatening outcomes. To address this increasingly pressing healthcare challenge, there is a need to research novel approaches for early detection and prevention. Toward this, ubiquitous systems can play a central role in revealing and tracking clinically relevant behaviors, contexts, and symptoms. Further, such systems can passively detect relapse onset and enable the opportune delivery of effective intervention strategies.
However, despite their clear potential, the uptake of ubiquitous technologies into clinical mental healthcare is rare, and a number of challenges still face the overall efficacy of such technology-based solutions. The goal of this workshop is to bring together researchers interested in identifying, articulating, and addressing such issues and opportunities. Following the success of past workshops, we aim to continue facilitating the UbiComp community in developing novel approaches for sensing and intervention in the context of mental health.
We invite submissions in the areas and intersections of mental health, well-being, ubiquitous computing, and human-centered design, including but not limited to:
Design and implementation of computational platforms (e.g., mobile phones, instrumented homes, skin-patch sensors) to collect health and well-being data.
Investigating new methodologies for intervention (e.g., conversational agents, AR and VR applications).
Automated inference from sensor data of high-level contexts (e.g., environmental, social) indicative of mental health status.
Design and implementation of feedback (e.g., reports, visualizations, proactive behavioral interventions, subtle or subconscious interventions) for both patients and caregivers.
Development of robust behavioral models that can handle data sparsity and mislabeling issues.
Integration of multimodal data from different sensor streams for personalized predictive modeling.
Methods for sustaining user adherence and engagement over long periods of time.
Devising privacy-preserving strategies for data collection, analysis, and management.
Algorithms to detect and predict psychiatric symptoms or support systems for degenerative and developmental disorders.
Deployment in low-income communities and countries.
Identifying ways to better integrate ubiquitous technologies into existing healthcare infrastructures and government policy.
Submission deadline: July 8th, 2019 (11:59 PM PDT)
Decisions to authors: July 10th, 2019
Camera-ready deadline: July 12th, 2019
Regular (up to 9 pages) or short (up to 5 pages) paper using SIGCHI format. Papers should be in PDF format and not anonymized.
https://new.precisionconference.com/user/login Please select SIGCHI→UBICOMP2019→Ubicomp 2019 Workshop Mental Health S&I
All accepted papers will be included in the ACM Digital Library as part of the UbiComp conference supplemental proceedings. Papers will be reviewed by the workshop's technical program committee according to criteria regarding a submission's quality, relevance to the workshop's topics, and, foremost, its potential to spark discussions about directions, insights, and solutions in the context of mental health, sensing, and intervention. Research papers, case studies, and position papers are all welcome.
In particular, we encourage authors to keep the following options in mind when preparing submissions:
Works-In-Progress: To facilitate sharing of thought-provoking ideas and high-potential though preliminary research, authors are welcome to make submissions describing early-stage, in-progress, and/or exploratory work in order to elicit feedback, discover collaboration opportunities, and generally spark discussion.
Challenge Papers: We are also soliciting challenge papers, in which authors describe a specific challenge they would like to pitch and have discussed at the workshop.
Assistant Professor, Rice University.
Assistant Professor, Penn State.
Professor, Technical University of Denmark.
Research Associate, University of Cambridge.
Postdoctoral Scholar, Stanford University.
Associate Professor, Cornell University.