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IEEE Pervasive <[log in to unmask]>
Tue, 1 Jun 2021 18:51:05 -0400
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[Apology for cross-posting]

Call for Papers : Special Issue on Mental Health, Mood, and Emotion
Akane Sano, Mirco Musolesi, Gavin Doherty, Thomas Vaessen

Title and abstracts due: 17 June 2021 (email to [log in to unmask])
Full manuscripts due: 1 July 2021 (via submission site)
Publication: April-June 2022

Mental health is one of the most challenging issues facing our society due
to the high prevalence of mental illness and the devastating effects it has
on the individual and society. For instance, in 2020, one individual died
by suicide every 40 seconds; by 2030, death by suicide will be the #1
disease burden. Common risk factors for poor mental health and wellbeing
are high levels of stress and anxiety, sleep deprivation, and loneliness.
These factors are relevant to prevention, early intervention, and the
support of treatment. Also, chronic mental illnesses such as bipolar
disorder, schizophrenia, and substance abuse require long-term
self-management and monitoring to avoid deterioration of an individual’s
mental health and wellbeing. This has led, in recent years, to an increase
in the interest and exploration of the use of pervasive technologies such
as mobile computing and sensors with machine learning for detecting
symptoms, assisting in the diagnosis of mental health problems, and for
improving access to, engagement with, and the outcomes of therapeutic
treatment. They promise to offer new routes for improving the
identification of risk factors, the prediction of disease progression, and
the development of personalized health interventions.

Despite great potential, the realization of effective pervasive
technologies for mental health remains extremely challenging. How can
pervasive computing help diagnosis, treatment, and management for mental
health? What are the gaps between technological innovations, and what is
needed in clinical settings? How should we develop and evaluate pervasive
technologies to help decision-making and ensure safety, accuracy, and
fairness? How can we develop privacy-preserving pervasive computing systems
for mental health?

This special issue seeks to discuss novel approaches, opportunities, and
challenges for developing effective, ethical, and trustworthy pervasive
computing technology for mental health. The guest editors invite original
and high-quality submissions addressing any aspect of the role of pervasive
computing in supporting mental health. Ethical dimensions of the research
should be considered in all submissions. Review or summary articles—for
example, critical evaluations of the state of the art, or an insightful
analysis of established and upcoming technologies—may be accepted if they
demonstrate academic rigor and relevance.

Topics of interest include, but are not limited to:

Sensing, signal processing, and machine learning algorithms and
applications for detecting and predicting mental health risks, diagnosing
mental illness, discovering patient subtypes, or intervening in mental
health and wellbeing
Design and implementation of privacy-preserving pervasive computing
platforms to collect, analyze, and manage human biobehavioral data
Investigating new methodologies for intervention (such as conversational
agents, smartphone app-based therapy, and augmented/virtual reality)
Evaluation of pervasive computing technology to better understand factors
related to mental health disorders and treatment efficacy
Development of robust models that can handle sparsity of physiological,
behavioral, and social data; handle label uncertainty; and infer mental
health status and related biobehavioral markers
Methods for sustaining user adherence and engagement over long periods of
Technology deployment in low-income communities/countries
Design interfaces, interactions, and feedback that incorporate pervasive
computing for patients and other stakeholders
Development of human-in-the-loop pervasive computing technology to support
clinical decision-making
Challenges in conducting pervasive computing and mental health research in
real-world settings or integrating pervasive computing technologies into
existing healthcare infrastructures and government policy
Evaluation of ethics, fairness, and bias aspects in developing pervasive
computing technologies for mental health

Submission Guidelines
Articles submitted to IEEE Pervasive Computing should not exceed 6,000
words, including all text, abstract, keywords, bibliography, biographies,
and table text. The word count must include 250 words for each table and
figure. References should be limited to at most 20 citations (40 for survey
papers). Authors are encouraged, but not required, to use a template for
submission (accepted articles will ultimately be typeset by magazine staff
for publication). You can read the full Author Guidelines here. In
addition, for this special issue, we invite submissions of 300-word case
studies. These should describe timely projects, systems, and activities
that are relevant to this special issue. Case studies should describe the
motivation and objectives of the work, highlight the deployment
characteristics, and summarize any preliminary findings or results if
available. We are happy to receive case studies for ongoing work. The
accepted case studies will be curated and combined into a single report
that will be published in this special issue. Case studies should be
submitted using the same process as abstracts, and they should include an
in-text reference or link that provides more information about the case
study or project.

Manuscripts should not be published or currently submitted for publication
elsewhere. When you are ready to submit, please go to

Guest Editors
Contact the guest editors at [log in to unmask]

Akane Sano (Rice University, USA)
Mirco Musolesi (University College London, United Kingdom)
Gavin Doherty (Trinity College Dublin, Ireland)
Thomas Vaessen (KU Leuven, Belgium)

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