Workshop on Emerging Technology and Data Analytics for Behavioral Health
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Abstract
Wearable and portable digital devices can support self-monitoring for patients with chronic medical conditions, individuals seeking to reduce stress, and people seeking to modify health-related behaviors such as substance use or overeating. The resulting data may be used directly by a consumer, or shared with a clinician for treatment, a caregiver for assistance, or a health coach for support. The data can also be used by researchers to develop and evaluate just-in-time interventions that leverage mobile technology to help individuals manage their symptoms and behavior in real time and as needed. Such wearable systems have huge potential for promoting delivery of anywhere-anytime health care, improving public health, and enhancing the quality of life for many people. The Center for Technology and Behavioral Health at Dartmouth College, a P30 "Center of Excellence" supported by the National Institute on Drug Abuse at the National Institutes of Health, conducted a workshop in February 2017 on innovations in emerging technology, user-centered design, and data analytics for behavioral health, with presentations by a diverse range of experts in the field. The workshop focused on wearable and mobile technologies being used in clinical and research contexts, with an emphasis on applications in mental health, addiction, and health behavior change. In this paper, we summarize the workshop panels on mobile sensing, user experience design, statistics and machine learning, and privacy and security, and conclude with suggested research directions for this important and emerging field of applying digital approaches to behavioral health. Workshop insights yielded four key directions for future research: (1) a need for behavioral health researchers to work iteratively with experts in emerging technology and data analytics, (2) a need for research into optimal user-interface design for behavioral health technologies, (3) a need for privacy-oriented design from the beginning of a novel technology, and (4) the need to develop new analytical methods that can scale to thousands of individuals and billions of data points.
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The application of analytics is an emerging approach to study and interpret engagement with mobile health interventions.
“The application of analytics, defined as the use of data to generate new insights [18], is an emerging approach to study and interpret engagement with mHealth interventions [19].”
From A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review (2019) · cites this paper as [19]
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- Authors
- Kotz, D., Lord, S. E., O'Malley, A. J., Stark, L., & Marsch, L. A.
- Affiliations
- Dartmouth College (US)
- Venue
- JMIR Research Protocols
- Publisher
- JMIR Publications Inc.
- Published
- 2018-06-20
- Volume
- 7
- Issue
- 6
- Pages
- e158
- ISSN
- 1929-0748 (ISSN-L)
- PMC
- PMC6031897
- OpenAlex
- W2803194235
- Cited by
- 14
- References
- 10
- Citations by year
- 2026: 1 · 2024: 1 · 2022: 3 · 2021: 2 · 2020: 3 · 2019: 4
- FWCI
- 3.44
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Research Protocols (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute on Drug Abuse (P30DA029926)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- wearable devices, mobile health, behavioral health, self-monitoring, mobile sensing, user experience design, user-centered design, machine learning, data analytics, privacy and security, mental health, addiction, health behavior change, just-in-time interventions, user interface design
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