Protecting the Most Vulnerable: Seniors, AI & Mental Health
Co-authored by Yvonne Wang and Yusuf Baig
My grandmother lost the glimmer in her eye. I cannot pinpoint the exact moment it happened, but I remember looking into her eyes as she laid on her nursing home bed and not seeing the same person I had once known. My grandmother was the life of the party. Always laughing, always telling stories– she probably had more friends than I did. With her in the house, there was never a dull moment. So when she stopped doing the things she used to love and started talking to family less, I knew something was wrong, even though she would never admit it herself.
In 2013, my grandmother (who was living at our home at the time) fell going down the stairs. No one was home except for my older brother who was in the shower. Her fall was quite serious, as she hit her head on the edge of the stair resulting in the need for 10 stitches on her head. After this scare, my family began to reevaluate how safe it was for my grandmother to be living at our home. Her mobility after the fall was severely limited, and she now needed to use a walker and could not go up or down stairs. Along with this, all of us had places to go everyday: both of my parents to work and my brother and I to school. We did not want to risk our grandmother getting seriously hurt while no one was there to help her.
I was around 8 when the idea arose to send my grandmother to a nursing home, so I was not very involved in the conversation. I did, however, notice a change in my grandmother around this time. She was a lot less cheerful than she used to be and stayed quiet more. My family did end up sending her to a nursing home so she could receive the custodial care and extra assistance she needed. Despite this extra help, sending her away took a large toll on her mental health. She no longer had the daily family interactions she had become used to, was constantly worried about falling and hurting herself again and did not have many friends. The bright and lively grandmother I once knew, had become only a shell of who she used to be.
At the nursing home my grandmother lived in, there were countless resources dedicated to making sure residents were physically healthy, but there were close to no resources for mental health. This is an unseen reality of many nursing homes across Canada. Several studies have shown that nursing homes lack access to quality mental health services for residents, something that simply cannot be overlooked. Seniors are at a high risk suffering from mental illnesses, and society should arguably do more for seniors’ mental health rather than less.
Studies show that seniors are more reluctant to seek out help for their mental health, due to stigmas that surrounded them when they were younger. In a joint research paper between Indiana and Columbia University titled “Public Conceptions about Mental Health”, it states, “In the 1950s, fearful and rejecting attitudes towards mental health were common”. They grew up in a society where mental illness was disregarded, and those who suffered from it were merely told to cope. This mentality is often still ingrained within many seniors, making it difficult for them to reach out for help when they need it. The prevalence of mental health problems within the elderly population is 30%, and the neglect of their mental health is a real problem. In a sample of nearly 50,000 seniors living in residential care facilities in five Canadian jurisdictions, nearly half had a diagnosis and/or symptoms of depression and few were actively receiving treatment.
So, how do we address this problem? How do we make sure that the mental health of the elderly is not neglected? What resources can be devoted to helping seniors with mental illnesses get the support they need? Well, there is this great thing called AI! Artificial Intelligence, a powerful emerging technology, can be used to predict mental illnesses in seniors, helping them get the assistance they need sooner.
AI, more specifically machine learning, is a tool that can be trained to recognize patterns within a dataset.
Machine learning can help clinicians predict who may be at risk of a particular illness. What makes machine learning so useful is that the understanding of diagnoses in the past were always based on statistics and group averages within a population.
“For decades, we’ve been working on group averages and statistics that apply to populations who may have the same diagnosis but don’t translate as well to an individual patient.”
— David Benrimoh, MD, CM, a psychiatry resident at McGill University
Machine learning addresses the need for personalization in psychiatry, allowing individuals to get a personalized prediction in a way that was hardly possible before.
Machine learning is helping to treat mental health in 1 key way:
Recognizing biomarkers and developing treatment plans.
There is a trial and error process today when diagnosing patients to achieve the correct dosage of medication and choosing the correct treatment plan. However, this process overlooks reality. The reality is, every patient’s symptoms will vary for the same mental health disorder.
Machine learning algorithms can help identify behavioural markers (that are often missed) to help mental health professionals determine if a patient is at risk of having a mental illness; the algorithms can also assist in tracking the effectiveness of a treatment plan.
We must move beyond the age of reactive medicine. Recognizing patient patterns before a mental health crisis occurs will lead to significant improvements in treatment and care. This will also put less stress on the individual themselves to reach out after symptoms arise, curbing the hesitation among seniors to get the help they need.
Mental illnesses affect us all, and we should not be treating the mental health of seniors as a second priority. In the 21st century, society has done an excellent job of dispelling fears and stigmas surrounding mental health that used to be intertwined in the social fabrics of our elders. However, more work needs to be done. Stories like the one mentioned in the beginning aren’t anomalies. They are common realities. The more we incorporate artificial intelligence into psychiatric care, the more we are ensuring that all citizens’ mental health is being cared for.
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