GIM, a dataset for predicting patient deterioration in the General Internal Medicine ward v1.0.0 - required training

TCPS 2: CORE 2022

The Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS 2) provides ethics guidance that applies to all research involving human participants – including their data and/or biological materials – conducted under the auspices of an institution eligible for funding by the federal Agencies (CIHR, NSERC, SSHRC).

The online tutorial CORE-2022 (Course on Research Ethics) is an introduction to the TCPS 2 for the research community. It focuses on the TCPS 2 ethics guidance that is applicable to all research involving human participants, regardless of discipline or methodology.

CORE-2022 consists of nine modules and a knowledge consolidation exercise:
Module A1 – Introduction
Module A2 – Scope of TCPS 2
Module A3 – Risks and Benefits
Module A4 – Consent
Module A5 – Fairness and Equity
Module A6 – Privacy and Confidentiality
Module A7 – Conflicts of Interest
Module A8 – Research Ethics Board Review
Module A9 – Research Involving Indigenous Peoples
Knowledge Consolidation Exercise

Health Data Nexus Data User Code of Conduct Training

In order to access datasets on the platform, you will need to demonstrate that you have read and understood your obligations under the Code of Conduct. Please view the following video:

Once you have completed the video, please take a screenshot of the certificate at the end of the video and upload it below.

ISED Cybersecurity Training for Researchers

Researchers must complete the following training module in Cybersecurity for Researchers from Innovation, Science, and Economic Development Canada (ISED). The link to the training can be found here:

In order to access the training, you may either sign in through a Sign-in Partner (your bank or other online platform) or by creating a GCKey. Select your preferred options and follow the steps listed on the website.

Once you have logged in and completed the training, please upload the training certificate with your name listed.

Back to GIM, a dataset for predicting patient deterioration in the General Internal Medicine ward v1.0.0