The costs of mental illness – in the form of disability, loss of productivity, and premature death – are often underestimated. Addressing the global mental-health challenge requires not just building up traditional mental health-care capacities, but also taking advantage of cutting-edge technologies like artificial intelligence.
A few years ago, toward the end of his life, my father battled severe depression. As a physician and professor, he did not lack access to mental-health care. But he had grown up in a society that stigmatized mental illness, and he was unwilling to seek professional help. As a son, it was devastating to watch my father suffer. As a public-health researcher, I gained a new awareness of the myriad systemic failures in the provision of care.
Scientists from around the world are now seeking to address the problems with “Countdown Global Mental Health 2030,” a “multi-stakeholder monitoring and accountability collaboration for mental health” launched in February. But, while this initiative is a positive step, it neglects a key element of an effective solution: advanced technology, especially artificial intelligence (AI).
Globally, the supply of psychiatrists and clinical psychologists is nowhere near sufficient. For example, in Zimbabwe, there are just 25 mental-health professionals for a population of over 16 million. While the country has produced some innovative and useful community-led initiatives, such as the “Friendship Bench,” their scalability is limited.
Lack of access to mental-health care is hardly a developing-country problem. In the United States, almost half of the population is unable to access comprehensive mental-health care, often owing to financial constraints.
Beyond access, there is the stigma issue, exemplified by my father’s experience. Clinical evidence indicates that stigma takes two forms. People who seek mental-health care may face public stigma in the form of discrimination and exclusion, owing to endemic misconceptions about mental illness. When those beliefs are internalized, sufferers may also struggle with self-stigma: low self-esteem, low self-efficacy, and unwillingness to pursue productive opportunities.
The consequences of failing to provide adequate care have been severely underestimated. According to one study, mental-health issues are responsible for 32.4% of years lived with disability and 13% of disability-adjusted life years (DALYs) – years of “healthy” life lost due to disease, disability, or untimely death.
The economic costs are enormous. According to a 2015 analysis, in the US alone, the total economic burden from mental health exceeds $210 billion annually. More than half of that is attributed to workplace absenteeism and productivity losses; another 5% is attributed to suicide-related costs. Companies’ efforts to circumvent the need for mental-health care by reminding workers to practice mindfulness are probably not as helpful as proponents claim.
What could help are AI-based solutions, such as chatbots. By mimicking natural language to sustain a conversation with a human user, these software systems could act as virtual therapists, providing guidance and support to those who have no alternatives. A randomized control trial reported by clinical psychologists from Stanford University showed that chatbots were significantly better at reducing the symptoms of depression than an information-only approach.
The sort of provisional mental-health care provided by chatbots would be particularly useful in communities with an inadequate supply of trained professionals. At a time of unprecedented access to smartphones in developing economies, Internet-based solutions would amount to a boon for mental-health accessibility.
Chatbots could also help overcome the stigma problem, because they can engage people who are otherwise reluctant to seek mental-health care. A recent study found that up to 70% of patients are interested in using mobile applications to self-monitor and self-manage their mental health. Once people initiate contact with a chatbot, another study indicates, they tend to express themselves more freely than they would with a human therapist, underscoring the priority people place on maintaining privacy and avoiding judgment when seeking to address a mental-health issue.
It is now up to clinicians, such as psychologists, to collaborate more extensively with AI developers. Several US universities have already launched programs that connect experts from clinical sciences with software engineers. These partnerships should be expanded to include universities, especially in countries with a large unmet need for mental-health care, in order to support the development of linguistically and culturally appropriate virtual therapists.
Involving more diverse actors in the development of algorithms would also help to address the issue of racial and gender discrimination that has cropped up in AI research. Researchers should use fully representative test groups, while taking care to adhere to stringent privacy and accountability protocols.
Of course, such initiatives cost money. Venture capital companies now spend$3.2 billion annually on global health research and development. They should expand the scope of their investments to include AI-enabled technologies for mental-health-care delivery. They could also fund competitions among socially conscious technology entrepreneurs, in order to spur further innovation in this area.
To be sure, AI-enabled mental-health interventions would not – and should not – replace human psychologists or psychiatrists. A chatbot cannot, after all, project real empathy. What it can do is screen for high-risk individuals, such as those with suicidal ideation, and potentially avert destructive behavior in the short term.
Demand and need often drive innovation. Unfortunately, that has not been true of mental-health care. It is time to invest in long-term, cost-effective, and scalable solutions that build mental-health care capacity. That effort must include expanded support for traditional services. But it should also take advantage of cutting-edge technologies like AI.
Junaid Nabi is a public health researcher at Brigham and Women’s Hospital and Harvard Medical School, Boston.
Read the original article on project-syndicate.org.
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