Clinicians, therapists and researchers are increasingly embracing the potential in artificial intelligence, also known as AI, as a powerful tool in the provision of mental healthcare.
In mental health care, many psychiatrists, psychologists and social workers believe that AI has the potential to be highly beneficial when it comes to predicting mental health issues, creating personalised treatment plans and ensuring compliance on an individualistic basis.
A United Kingdom-based clinical psychologist, Dr Ebiere Dagogo, in an interview with Sunday PUNCH noted that a growing body of evidence suggests that AI can help with diagnosing conditions, developing therapies and enabling more personalised approaches and treatments.
Since the outbreak of the Covid-19 pandemic three years ago, Forbes in an article on AI and healthcare noted that more people than ever have been seeking help for mental health problems, including depression and anxiety.
In Nigeria, for instance, in 2022, the Nigerian Medical Association noted that nearly 60 million out of the country’s over 200 million population suffered from different mental health issues, ranging from mild to severe.
The World Health Organisation also said suicide was the fourth leading cause of death among 15 to 29-year-olds worldwide.
This is inevitably leading to growing pressure on already stretched healthcare and therapeutic services, which have become increasingly difficult for many to access. In Nigeria, doctors and other healthcare providers are leaving in droves for more advanced economies for better pay, working conditions and growth. This has left the country’s health sector in a terrible state.
Could smart, machine learning-powered technology be a part of the solution – possibly reducing the need for patients to be given medication or to have their freedoms restricted by confinement in mental health hospitals?
In several developed economies, AI chatbots can provide a non-judgmental listening ear and offer advice based on evidence-based therapies. They can also provide emotional support and companionship for people struggling with mental health issues.
Dagogo added that AI was already being used to change lives and improve patient outcomes for a variety of mental health conditions.
She said, “The potential for AI to transform mental healthcare is huge. In addition to the applications, AI could also be used to develop new treatments and therapies, or even to diagnose mental health conditions earlier.”
AI therapists
Research has shown that some people feel more comfortable talking to a robot than a human being when it comes to unloading their deep, personal feelings.
A senior psychologist with the Remz Institute, Uyo, Akwa Ibom State, Mr Usen Essien, said humans are naturally judgmental, adding that if there was a way mental health patients could relate to a ‘tool’ they were sure would not judge them, they would take it.
He added, “The way human psychology is built is in such a way that they feel the need to ‘perform’ or ‘cover-up’, not say everything for some self-preservation. But with the coming of AI in mental healthcare – even if it is sure that physical psychologists and social workers would still work on and interpret the data brought forward by AI – many people can unburden their fears and concerns in their own safe space.
“There are also the issues of timeliness and availability. Since the AI tool is readily available than driving a long distance to see a doctor who may not be available at the time, it would be a gamechanger in the interim – just like first aid – till the doctor is available and can help in full.”
Chatbots are increasingly being used to offer advice and a line of communication for mental health patients during their treatment. They can help with coping with symptoms as well as look out for keywords that could trigger a referral and direct contact with a human mental healthcare professional.
One example of a therapeutic chatbot like this is Woebot, a chatbot that learns to adapt to its users’ personalities and is capable of talking them through a number of therapies and talking exercises commonly used to help patients learn to cope with a variety of conditions.
According to the research put forward by a peer-reviewed study conducted by the American Psychiatric Organisation, there are several real life instances of how AI is already being utilised to improve mental health care.
For instance, Woebot has been shown to be effective in reducing symptoms of depression and anxiety.
In one of the studies, patients who used Woebot reported a significant decrease in symptoms after two weeks of use.
Another example is the app, BetterHelp, which uses AI to match users with a therapist that is a good fit for their needs.
This app has been shown to be effective in improving mental health outcomes.
Another chatbot, Tess, offers free 24/7 on-demand emotional support and can be used to help cope with anxiety and panic attacks whenever they occur.
Wearables
Rather than waiting for a user to interact with them via an app, some AI mental health solutions function as wearables that can interpret bodily signals using sensors. They can also step in to offer help when it’s needed.
Biobeat, according to an online resource, Well That is Interesting Tech, is said to collect information on sleeping patterns, physical activity and variations in heart rate and rhythm that are used to assess the user’s mood and cognitive state.
This data is compared with aggregated and anonymised data from other users to provide predictive warnings when intervention may be necessary.
Users can then make adjustments to their behaviour or seek assistance from healthcare services when they feel it’s necessary.
For a country as multi-structured like Nigeria, what can AI do to improve the country’s mental healthcare subsection?
Diagnosing, predicting patient outcomes
AI can also be used to analyse patient medical data, behavioural data, voice recordings collected from telephone calls to intervention services, and numerous other data sources, using machine learning to flag warning signs of mental problems before they progress to an acute stage.
An aggregated review of studies where AI was used to parse various data sources, carried out by IBM and the University of California, published on E-Scholarship, found that machine learning could predict and classify mental health problems, including suicidal thoughts, depression and schizophrenia, with “high accuracy.”
Data sources used in the 28 studies reviewed included electronic health records, brain imaging data, data taken from smartphone and video monitoring systems, and social media data.
Additionally, researchers at Vanderbilt University Medical Center found that hospital admission data, demographic data, and clinical data could be parsed with machine learning to predict whether a person would take their own life with 80 per cent accuracy.
Another project focused on using AI to predict mental health issues is underway at the Alan Turing Institute. Researchers, here, are looking into ways of using large-scale datasets from individuals who have not shown symptoms of mental health issues to predict which of them are likely to develop symptoms during their lifetime.
AI has also been used to predict cases where patients are more likely to respond to cognitive behavioural therapy, also known as CBT, and therefore be less likely to require medication. As antidepressant and antipsychotic medications can have side effects that are in themselves life-limiting, this has the potential to hugely improve patient outcomes for some patients.
JAMA Psychology in a recent report found that deep learning can be used to validate the effectiveness of CBT as a method of treatment, potentially reducing the need to prescribe medication to some patients.
Improving patient compliance
Dagogo said, “One of the biggest challenges in treating mental health conditions is making sure that patients comply with the treatments prescribed for them, including taking medication and attending therapy sessions.
“AI can be used to predict when a patient is likely to slip into non-compliance and either issue reminders or alert their healthcare providers to enable manual interventions. This can be done via chatbots like those mentioned previously or via SMS, automated telephone calls and emails. Algorithms can also identify patterns of behaviour or occurrences in patients’ lives that are likely to trigger non-compliance.”
According to her, this information can then be passed to healthcare workers who can work with the patient to develop methods of avoiding or countering these obstacles.
Dagogo noted further that one exciting area of research involves leveraging AI to create personalised treatments for a number of mental health conditions.
She said, “AI has been used to monitor symptoms and reactions to treatment to provide insights that can be used to adjust individual treatment plans.
“The University of California, Davis, US, in a research focused on creating personalised treatment plans for children suffering from schizophrenia based on computer vision analysis of brain images. An important element of the research is the focus on “explainable AI” – the algorithms need to be understandable by doctors who are not AI professionals.”
Downsides
While there are many potential benefits to using AI in mental healthcare, there are also some potential downside that need to be considered.
One concern is that AI may not be able to fully replace the human element of therapy.
Essien said, “There is something about the connection between a therapist and a patient that cannot be replicated by a computer programme. Another concern is that AI may not be able to provide the same level of empathy and understanding that the human therapist can.”
Additionally, some worry that AI could be used to collect and exploit personal data, or even to replace human therapists entirely.
