Digital Therapeutics

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.

Ongoing Studies

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:

  • To better understand the factors influencing mental distress among Unity Health staff during the ongoing COVID-19 pandemic,
  • To reduce the debilitating effects of key distress factors and maintain distress levels within an acceptable range by providing personalized mobile-based feedback (e.g. exercise, mindfulness tips) based on active/passive data, and
  • To streamline the availability of mental health resources such as cognitive behavioural therapy (CBT) where automated mobile-based feedback is insufficient.

Eligibility:

  • UHT Employee
  • 18 years or older
  • Owns a mobile phone (Android phones with OS version 8.0 and above, iPhone 6 with iOS 11 and above)

Intervention Protocol:

  • The study coordinator will provide login access after the participant installs the application on their mobile device.
  • The platform allows for collection of various forms of active data (data collected while the participant is using the app, e.g. surveys assessing anxiety or mood), and passive data (data collected whether or not the user is actively using the app, e.g. accelerometer data).
  • Participants who are (1) unable to manage stress with daily mobile monitoring/feedback and (2) meeting threshold scores for moderate to severe anxiety and depression based on the active (survey data) will have links to access internet-based cognitive behavioural therapy (iCBT).
  • Participants will automatically be randomized to receive or not receive personalized automated alerts (e.g. to practice bibliotherapy, exercise, etc.) for 4 weeks. These alerts are based on their active and passive data, with the objective of adjusting the active and passive parameters to remain within an acceptably low level of distress.
  • This notification feature will be made available to all participants after 4 weeks.
  • The anticipated duration for the study is 1 year.

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:

  • UHT Employee
  • 18 years or older
  • Owns a mobile phone (Android phones with OS version 8.0 and above, iPhone 6 with iOS 11 and above)

Intervention Protocol:

  • The VR component involves a 30-minute simulated scenario in which participants will face a morally distressing situation within a virtual COVID-19 ICU environment. During this VR session, we will educate the users of potential moral injury interventions with our Moral Injury Educational Video. Images of the VR experiment can be seen in VR Experimental Images (below).
  • The wearable components are sensors that will monitor various signals (physiological and environmental) throughout the simulation.
  • The mobile component involves DiiG, a customized version of an open-source mobile-based platform, LAMP [https://www.digitalpsych.org/lamp.html]. This platform is fully compliant with patient/participant confidentiality standards such as the US HIPPA and corresponding Canadian PHIPA/PIPEDA privacy laws. This application is available on the Google Play Store and Apple App store, and login access will be provided after completion of the VR simulation.
  • The DiiG application will have built-in mental health surveys governed by DSM, which are considered as active data. This application will also collect passive data (such as accelerometer activity) regardless of whether the participant is using the app.
  • The analysis of active and passive data will give rise to digital phenotyping for identification of mental health.
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