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Mental Illness and Addictions

  • Information for Health Professionals
    This series of documents provides information to health professionals about substance use and abuse. The documents are substance-specific and include information about methods of ingestion, effects on the body, dependence and withdrawal, and applicable laws.
  • An Introduction to Artificial Intelligence and Machine Learning in Addictions & Mental Health
    This summary examines artificial intelligence and machine learning and how they are being used to help predict addiction and mental health concerns such as suicide attempts, schizophrenia, depression, and opioid addiction.

  • Machine Learning
    This infographic provides a summary of machine learning.

  • The Relationship Between Cannabis and Cancer in Men
    In Canada, men report nearly double the use of cannabis compared to women. This document summarizes the relationship between cannabis and cancer in men.
  • Constant Observation in Psychiatric Inpatient Settings
    This document provides an overview of the use of constant observation in psychiatric inpatient settings. It includes information about what constant observation is and why it might be used, as well as key therapeutic considerations and alternative strategies.
  • Telehealth in Substance Abuse and Addictions
    The Institute for Health Economics has produced a literature review of the role of telehealth in alcohol, smoking, drug abuse, and gambling.
  • Mental Illness and Addictions Environmental Scan
    This environmental scan focuses on Alberta research in the area of mental illness and addictions. It includes information about individuals and organizations involved in this work and their specific areas of research, as well as funding opportunities.

Trends

Substances or chemicals that are misused or abused may have little information readily available about them. These backgrounders describe some trending substances. They outline what the chemicals are, why they are dangerous, how they are used, and their legal status.