Bioethics Blogs

Analytics and the Prevention of Suicide

Greg Horne describes how data on social media can be used to identify and concentrate resources on groups who are at risk of suicide.


Suicide is the second leading cause of death among youth in Canada. According to Statistics Canada, in 2011, it accounted for approximately 20% of the deaths of people under the age of 25. The Canadian Mental Health Association claims that among 15 – 24-year-olds the percentage of deaths caused by suicide is even higher, a frightening 24%– the third highest in the industrialized world. Recent reports also suggest that the suicide rates for First Nations and Inuit youth in Canada are from five to eleven times higher than the National average. Yet, despite these disturbing statistics, it is difficult, if not impossible, for health care providers (or friends and family) to identify whether a young person plans to injure themselves or die by suicide.

The warning signs leading up to a suicide can be easy to miss. For example, consider the recent spate of suicides at the University of Guelph. Was there a possibility of identifying the warning signs of increasing mental health issues at the University? Were there indications of a potential spike in suicides?

Some warning signs may be found online. Many people use social platforms like Facebook and Twitter to post detailed personal information about their health and their mental wellbeing. This information could help to identify groups who are at risk of self-harm or suicide.

SAS Canada, a data management, software development, and analytics company, is using a new artificial intelligence software solution to identify social groups that are at increased risk of suicide.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.