Digital Interventions & Intelligence Group (DiiG)
DiiG is a collaborative initiative led by Dr. Venkat Bhat (Psychiatry-UHT-St. Michael’s) and Dr. Sri Krishnan (Biomedical Engineering-Ryerson University)
Digital intervention projects revolve around digital interventions and intelligence. DiiG deploys various digital modalities including: Virtual Reality (VR), wearables, and mobile-based components. Our multidisciplinary team is at the intersection of engineering, advanced data analytics and psychology, and uses digital platforms, such as wearables and smartphones, to learn and assess user mental health. Through this, we aim to create personalized mobile and digital interventions to manage and prevent potential harm.
One example of our digital platforms is the novel DiiG (Digital Intelligence and Interventions Group) app, available on the Apple store and Google Play store. The initial version of DiiG used a customized version of the open-source LAMP platform, built [https://www.digitalpsych.org/lamp.html as a collaboration with the Digital Psychiatry Program at Harvard Medical School.
This platform is fully compliant with patient/participant confidentiality standards such as the US HIPPA and corresponding Canadian PHIPA/PIPEDA privacy laws. Images of our mobile app and its functionalities can be seen in the Mobile App section.
Functionalities of our DiiG app can be seen below.
Study Coordinator: Walter Sim (Walter.Sim@unityhealth.to)
Overview: This study will collect digital phenotyping data to assess mental health via DiiG, a novel mobile application that we have developed in-house. The aims of the study are:
Eligibility:
Intervention Protocol:
Study Coordinator: Walter Sim (Walter.Sim@unityhealth.to)
Overview: Digital intervention projects revolve around digital interventions and intelligence. There are three components to this study: Virtual Reality (VR), wearable, and mobile components. These components are explained in further detail below.
This study involves the use of VR to simulate the ICU environment during the COVID-19 pandemic. The simulation would place the participants in a morally distressing situation. During this time, physiological signals such as heart rate, respiration, pulse oximeter, and skin conductance will be collected to see correlations with the VR simulation. At the end, users will be prompted with a Moral Injury Educational Video that will summarize potential interventions.
The expected outcome will focus on important findings and dissemination of the results. We expect there to be an indicator in the physiological signals that will reflect moral distress. We will use this data to pursue novel research in signal processing and classification for short- and long-term results. We will use the physiological signals and the VR scenarios to identify features that correlate to moral distress and we will use passive data collected from the mobile app to determine fluctuations in individuals.
Eligibility:
Intervention Protocol: