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- Toronto Metropolitan University)
DiiG deploys various digital modalities including: Virtual reality (VR), wearable devices, and web-based interventions. Our multidisciplinary team is at the intersection of engineering, advanced data analytics and psychiatry, and uses digital platforms to learn about and assess a person’s mental health and well-being. Through this, we aim to create personalized interventions to manage and prevent relapse.
Our platforms are fully compliant with patient/participant confidentiality standards such as the US HIPPA and corresponding Canadian PHIPA/PIPEDA privacy laws.
In particular, digital mental health interventions (DMHIs) leverage digital tools (e.g., virtual reality, wearable smart devices, web-based surveys) to prevent, screen, treat, and/or monitor mental health concerns (e.g,. depression, anxiety, stress, sleep) in the real world. These tools have the unique potential to capture active and passive data about a patient’s behaviour, self-reported mental health symptoms, and biometrics (e.g., heart rate, sleep, activity) in near-real time.
Our digital suite includes custom-made virtual reality (VR) simulations and psychoeducational interventions delivered using an Oculus Meta Quest 2 headset.
Passive biometric data (e.g,. heart rate variability, sleep, activity) captured by sensors embedded in wearable devices, such as smart rings (e.g., Oura Ring) or smart watches (e.g., Empatica Embrace) can be leveraged to understand patients’ mental health and well-being based on their physiological responses over time.
To regularly capture patients’ self-reports of mood, sleep, and/or activity, we administer brief web-based surveys (a.k.a. ecological momentary assessments, EMAs) using the Greenspace or REDCap platforms.
Study contact: PA.TRD@unityhealth.to
Overview:
Physical activity (PA) has been associated with improvements in mood and mental health in both clinical and non-clinical populations. Recent research suggests that low doses and enjoyability of PA underlie its protective effect on mental health and well-being. As a result, in this study, we seek to explore the impact of a 4-week remotely delivered individualized one-on-one PA programme in addition to treatment as usual (TAU) on depressive symptoms of participants with treatment-resistant depression (TRD). At this time, we aim to conduct a pilot study with 30 participants wherein 20 will be randomized to the PA group and 10 will be in the control group.
Inclusion Criteria:
Exclusion Criteria:
Treatment Description
Interested in participating in our study? Find out if you are eligible
If you would like to know more about this study, please access our Informed Consent Form
Stress, anxiety, distress, and depression are high among healthcare workers, and were further exacerbated by the COVID-19 pandemic. Moreover, healthcare workers can also face moral distress, a complex phenomenon that can result from situations where someone knows the right thing to do, but is unable to act on it. Current understanding of factors underlying distress and resilience in complex moral contexts is limited, and there are no evidence-based interventions for moral distress.
The purpose of this study was to use a suite of digital interventions to understand and reduce the experiences of stress and moral distress faced by healthcare workers. In Phase 1 of our study, we demonstrated the feasibility of our VR simulation and psychoeducational intervention in a group of 15 healthcare professionals. In Phase 2 of the study, we recruited 100 nursing professionals to complete a VR simulation depicting a morally complex healthcare scenario as well as a psychoeducational intervention to help equip nurses with coping strategies. Additionally, we longitudinally monitored their mental health outcomes for 12 weeks using a wearable device and a web-based platform, where participants completed questionnaires.
The results of our pilot Phase 1 study are published. We found that VR was an effective method of simulating a stressful, morally challenging scenario. Additionally, we successfully created a “digital phenotype profile” of participants to predict their distress levels from physiological signals. Analysis of the Phase 2 study is currently underway.
Publications:
https://pubmed.ncbi.nlm.nih.gov/34871178/
https://pubmed.ncbi.nlm.nih.gov/38194247/