One in five seniors lives with some form of mental illness.  Lack of attention and support for mental illness not only harms the person, but also costs the healthcare system and economy billions.

Our challenge is to identify:

  1. What seniors believe is good mental health
  2. Factors that make and keep a person mentally healthy.

Our objectives are to:

  1. Understand seniors’ definitions of good mental health
  2. Identify who is more likely to be at risk and/or showing early signs of poor mental health
  3. Link people with help and support specific to their needs.

Our project will use detailed information about the lives of thousands of people, collected in large study of aging, and advanced computer programming, such as machine learning. Rather than using traditional statistics that are only able to determine how a few variables are related to another, we will use machine learning to determine how many variables interact and relate to mental health. This will lead to the development of an “early-warning system” identifying seniors at risk and connecting them to personalized pathways for better mental health.