NCT Number: NCT06732089
The goal of this observational study is to learn about remote mental health monitoring technology for adults with treatment-resistant depression. The main question it aims to answer is: are digital mental health monitoring tools (an electronic data capture platform and wearable device (e.g., smartwatch or smart-ring)) feasible to implement alongside clinical treatment for depression? The secondary aim of this study is to inform preliminary clinical parameters for larger, definitive studies.
Participants receiving neuropsychiatric treatment (repetitive transcranial magnetic stimulation, intravenous ketamine, or electroconvulsive therapy) as part of their regular medical care for treatment-resistant depression in the Interventional Psychiatry Program will have their clinical assessment data entered into a digital platform and will wear an accessory-based wearable device for the duration of treatment.
Interested in participating?
Request Info18 year and older
All sexes
Observational
Toronto, Ontario, M5B 1W8, Canada
Location status: Recruiting
Dr. Alice Rueda, Ph.D.
CONTACT
Dr. Karisa Parkington, Ph.D.
CONTACT
416-360-4000 ext. 76228
Dr. Perry Menzies, M.D., F.R.C.P.C.
CONTACT
Dr. Reinhard Janssen Aguilar, M.D.
CONTACT
Dr. Venkat Bhat, M.D., F.R.C.P.C.
CONTACT
416-360-4000 ext. 76404
Fathima Adamsahib, B.Sc., P.A.-C.
CONTACT
Gyu Hee Lee, B.Sc.
CONTACT
This observational study with retrospective data analysis is conducted in patients with treatment-resistant depression (TRD) undergoing neuropsychiatric clinical treatment (rTMS, IVK, or ECT) in the Interventional Psychiatry Program (IPP) at St. Michael's Hospital. Participants will have scores from a self-report assessment of anxiety (GAD-7) and a self-report (PHQ-9) or clinician-administered (MADRS) assessment of depression completed as part of clinical care entered into the Research Electronic Database Capture (REDCap) web-based platform after each treatment session. This will facilitate retrospective analysis of mental health symptom change and treatment response over the course of treatment. Participants will also have the opportunity to wear an accessory-based wearable device (e.g., smartwatch or ring) throughout the course of treatment to passively capture physiological biometrics of physical and mental health (e.g., heart rate, temperature, sleep, activity). This two-year pilot study aims to recruit a total of 200 participants with TRD to retrospectively assess the feasibility and efficacy of integrating remote health sensing and monitoring platforms in psychiatric clinical care.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: From Screening and Baseline Visit (Day 0) to last treatment day (approximately 2-8 weeks depending on treatment group)
To determine the feasibility of using a web-based digital platform and wearable devices to collect active and passive data, respectively, among adults receiving clinical treatment for treatment-resistant depression. This will be measured by: number of recruitments (minimum threshold of 6-7 participants/month), recruitment rates (relative to invited patient-participants; minimum threshold of 80%), dropout rates (maximum threshold of 30%), reasons for dropout (qualitative), and data completion/adherence rates (minimum threshold of 70%).
Time frame: From Screening and Baseline Visit (Day 0) to last treatment day (approximately 2-8 weeks depending on treatment group)
To quantify changes in active (clinical symptoms) and passive (physiological) measures of physical (activity) and mental health (depression, anxiety, sleep) over time. Active data will focus on anxiety and depression symptoms across treatment, as reported on the GAD-7, PHQ-9, and MADRS. Passive data will focus on physiological biometrics (e.g., heart rate, respiration, step count, metabolic equivalency, body temperature, sleep staging, skin conductance response) captured by the wearable devices.
Time frame: From Screening and Baseline Visit (Day 0) to last treatment day (approximately 2-8 weeks depending on treatment group)
To model and predict the likelihood of a patient achieving anxiety/depression treatment response (reduction greater than or equal to 50% on clinical assessment), remission (assessment score less than clinical threshold), and relapse (assessment score greater than clinical threshold after achieving remission) captured through active self-/clinician-administered assessments, based on longitudinal active and passive data.
Time frame: From Screening and Baseline Visit (Day 0) to last treatment day (approximately 2-8 weeks depending on treatment group)
To construct pDPPs (a.k.a. digital fingerprints) for each participant based on longitudinal active and passive data. This will be achieved using machine learning (ML), artificial intelligence (AI), and advanced data analytic principles.
Contact information is provided by the study sponsor or research team.
Dr. Karisa Parkington, Ph.D.
CONTACT
416-360-4000 ext. 76228
Dr. Venkat Bhat, M.D., F.R.C.P.C.
CONTACT
416-360-4000 ext. 76404
Unity Health Toronto
Other
Determining the Feasibility of Digital Interventions for Adults with Treatment-Resistant Depression
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