Goals | D3SM

About Us

The D3SM fosters implementation of innovations in mental health. Members of the D3SM are responsible for liaising between research and clinical teams, training health care professionals in novel approaches for interventions or on validated MBC tools and procedures, and are responsible for successfully integrating research protocols into clinical or community-based services. This initiative is responsible for supporting the local deployment of innovative projects with the potential for sustainable implementation, with a long-term goal of developing the expertise, tools, required relationships, and strategies to ensure that successful implementation can be executed anywhere.

Our main goals

The Douglas Digital and Data Science for Mental Health Initiative, know as D3SM, has an overarching goal of transforming research and care in mental health through innovative digital approaches and robust neuroinformatic infrastructures for research.

Digital Mental Health

Measurement-Based Care (MBC)

Instate MBC in various clinical services to track symptoms, function, satisfaction, etc.

Interventions Accessibility

Improve the accessibility of psychosocial interventions by reaching patients where they are.

Implementation

Use implementation science strategies to promote the uptake of innovative approaches to mental health care.

Data Science

Data Access

Discoverability

Management

Make stringent guidelines to ensure legitimate access of data.

Making available data discoverable to researchers.

Data valorization to improve its structure for later efficient use.

Open Science

Open research outputs

Openly share FAIR research outputs at all stages of research projects.

Open science from research to organizations

Enable Open Science in mental health from individual research projects to institute-wide initiatives.

Data and knowledge reuse

Facilitate the use of shared research outputs for educational, health, and societal impact.

Neuroinformatics Platform

Capacity

Develop capacity for data capture and storage

Big Data Analysis

Increase expertise in big data analyses including neuroinformatics and machine learning

Data Curation

Improve access to data with Open Science-based tools and by leveraging HBHL-resources.