Service Engagement in Early Psychosis Intervention Following the Transition to Virtual Care
- Funded by Canadian Institutes of Health Research (CIHR)
- Total publications:0 publications
Grant number: 202012GSM
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$459,459Funder
Canadian Institutes of Health Research (CIHR)Principal Investigator
N/A
Research Location
CanadaLead Research Institution
University of TorontoResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Indirect health impacts
Special Interest Tags
Digital Health
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Repercussions of the COVID-19 pandemic are expected to be particularly detrimental for youth with serious mental illness, especially persons with psychosis. Access to services is critical for this population, as early identification and treatment in the form of specialized early psychosis intervention (EPI) can significantly improve illness trajectories. The pandemic has disrupted service delivery, urging EPI programs to rapidly adopt models of virtual care; however, little is known of the quality or effectiveness of psychosis services delivered virtually. Historically, one-third of early psychosis patients dropout from services prematurely, though the effect of a transition to virtual care on disengagement is unknown. The present study aims to investigate factors associated with disengagement from a virtual model of EPI as compared to traditional, in-person services. To meet this objective, this project will leverage data collected on an evaluation of the implementation effectiveness of e-NAVIGATE, a structured, virtually-delivered EPI program at the Centre for Addiction and Mental Health, funded by CIHR, the Ontario Ministry of Health, and the University of Toronto. Routinely collected demographic, clinical and service use information will be extracted from electronic health records. Using prior data on in-person EPI, time to disengagement will be compared between the virtual and in-person models, examining factors that predict traditional service disengagement (namely, substance use and lack of family involvement), as well as additional health equity factors thought to impact the uptake of virtual care. Findings from this study may help to inform further development of virtual models, facilitating ongoing delivery of high-quality EPI during the pandemic and beyond.