The Center for Digital Mental Health conducts research and build digital tools to enhance mental health, especially amongst underserved groups and young people. The Center for Digital Mental Health aims to partner with and empower users by providing them. The work focuses on using mobile and wearable devices, and social media, to unobtrusively track and analyze behavior. We aim to use these data to detect mental health needs and provide adaptive, personalized interventions exactly when users need them. The mission of the Centre of Digital Mental Health is to translate knowledge from basic neuroscience and apply it to improve well-being, promote resilience, and mitigate the effects of early adverse experiences.
The Center brings together experts in mental health, behavioral science, intervention, mobile sensing, signal processing, affective computing, artificial intelligence, biomedical engineering, data mining, computer networks, and machine learning to provide the tools, collaborations and expertise to solve critical problems, solutions that have the potential to significantly lift the burden associated with mental disorders. These approaches leverage the latest developments in technology, quantitative analysis, and behavior change techniques to empower innovative, timely interventions and place them into the hands (and pockets) of people who need them.
Automatic Multimodal Affect Detection During Interpersonal Interactions (MULTI-MODAL) uses observational methods of measuring affective behavior have provided critical insights into emotion, socio-emotional development, and psychopathology. A persistent barrier to their wide application is that they are labor-intensive to learn and to use. Our interdisciplinary team of behavioral and computer scientists will develop and validate a fully automated system for measuring affective behavior from multimodal (face, gaze, body, voice, and speech) input for research and clinical use.
​
Country
United States of America
BIG DATA is a project studying relationships and patterns among online behaviors to identify a set of critical metrics that mark important differences among users; to identify and create metrics based on online behavior that are reliable and valid markers of important mental-health variables; and conduct a proof-of-concept study where use our newly identified metrics of online behavior to study community responses to a particularly devastating category of mass trauma events, mass shootings.(NIMH R21 Grant, PI: Sanjay Srivastava)
Country
United States of America
EASE is investigating the role of mobile sensing using smart phones in detecting changes in stressful life experiences, using an academic stress paradigm. Ease uses data derived from naturalistic phone use including:
- Natural language use
- Facial expression
- Acoustic voice and
- Geographic movement.
Country
United States of America
Geolocating Movement and Psychopathology (G-MAP) is a project that is examining how geographical movement and location relate to mental and physical health outcomes using passive sensing technology on smartphone devices. Researchers have previously examined the effects of fixed geographical location on health outcomes, but there are few studies that integrate variation in day-to-day geographical location into a comprehensive predictive health model.
Country
United States of America
Integrating mobile sensing into personalized adaptive sleep Interventions (SENSE+) is building on our previous work developing effective sleep enhancement interventions for adolescents, the SENSE + project is integrating individualized assessment of sleep patterns using wearable devices in order to provide adaptive personalized sleep improvement that incorporates just-in-time nudges delivered via mobile devices to enhance behavior change.
Country
United States of America
Mobile Quit - Type of device to deliver smoking cessation intervention is a study that compares the efficacy and participant engagement of two versions of the same evidence-based core for smoking cessation:
- A smartphone delivered program
- A desktop/laptop delivered program.
Country
United States of America
MomMoodBooster (MMB) (Web-based Intervention for Postpartum Depression) is a project that includes the delivery and ongoing evaluation of a full-featured Web-based eHealth cognitive behavioral therapy intervention targeting postpartum depression. MMB is being implemented in practical settings by the Veterans Health Administration Office of Rural Health and the Southern New Jersey Perinatal Cooperative. It is also being expanded to become a perinatal depression intervention that is delivered across devices, including smartphones. Data and experience derived from this project will provide an important guide for how digital treatment programs can bridge the divide between research and implementation.
Country
United States of America
The PROM study is developing a social media intervention to promote mental health by enhancing healthy sexual and romantic relationships in teenagers. Using an instructional design approach to behavior change, the intervention will target 4 phases of romantic relationships:
- Choosing a partner
- Maintaining a relationship
- Choosing whether and when to end a relationship
- Dealing with breakups
Online methods including video modelling and text based practice and coaching will promote teens using decision making, self care, and relationships skills.
Country
United States of America
Psychological Risk In Social Media (PRISM) are examining automated methods to detect social media accounts (Twitter, Instagram) the are associated with high levels of psychological stress and mental health risk. These accounts are then characterized in terms of their patterns of network connectivity, and which of these characteristics predict persistent versus transient psychological distress. These studies will provide a foundation for building social network based interventions.
Country
United States of America
The Effect of Screen Time on Sleep (F.LUX) is a project that examines the effects of automated diurnal variation in electronic screen temperature (i.e., automatically filtering blue light on screens in the evening) on sleep quality using a blinded, randomized controlled design.
Country
United States of America
Organisation
Address: Straub Hall, University of Oregon, Eugene, OR 97403
Country: United States of America
Email: c4dmh@uoregon.edu
