Artificial Intelligence (AI) in Mental Health Care: The Future is Now
Mental health challenges have been on the rise globally in recent years. With the COVID-19 pandemic, there has been an unprecedented increase in the burden of mental health issues. People have had to adjust to abrupt changes in work, school, and social life, leading to anxiety, depression, and other negative emotional states. Although many people seek help and advice, mental health professionals and resources remain underfunded, limited, and inaccessible. However, AI is changing the game, from diagnosing mental disorders to personalizing treatment plans, and making mental health care more accessible to patients worldwide.
AI in Diagnosing Mental Disorders
Diagnosis is the first step towards effective treatment. However, current diagnostic processes are subjective, based on clinician’s evaluation, and cross-referencing symptoms in the Diagnostic and Statistical Manual of Mental Disorders (DSM). In addition, mental health evaluations can be time-consuming, prohibitively expensive, and not always accurate. AI tools are being developed to offer a more objective, affordable, and automated means of diagnosis.
One such tool is the World Health Organization (WHO) guideline on the use of digital and AI solutions for mental health care. This guideline sets a framework for evaluating AI technologies for mental health diagnosis. For example, the guideline suggests that AI algorithms need to be validated both internally and externally to ensure accuracy across different data sources. AI algorithms could also be combined with traditional assessment tools to provide a more comprehensive diagnostic evaluation. For example, AI-powered chatbots could be used to conduct initial assessments, followed by a clinician’s review, or AI algorithms could analyze electronic health records and patient histories to predict the likelihood of specific mental health disorders.
Overall, AI can significantly enhance and complement mental health diagnosis by making it more objective, accurate, and affordable. AI-enabled diagnosis could also reduce the stigma around mental health and improve patient access to care.
AI in Personalized Treatment Plans
Once a diagnosis is established, selecting the most appropriate personalized treatment plan is critical. However, treatment plans that work best for one patient may not be effective for another. In addition, traditional psychotherapy is limited by geographical, financial, and cultural barriers. AI tools can personalize treatment plans, optimize psychotherapy, and reduce the limitations of traditional methods.
One such tool is an AI-powered cognitive-behavioral therapy (CBT) application developed by Woebot. Woebot uses natural language processing and machine learning to mimic a human clinician’s conversation and provide personalized therapeutic recommendations. Woebot is available 24/7 and can be used remotely, which makes it accessible to patients worldwide. Preliminary studies show that Woebot is as effective as human therapists in treating anxiety and depression and can also offer early interventions to prevent relapse.
Another AI tool in personalized treatment planning is the use of electroencephalogram (EEG) technology to optimize neuromodulation therapy. Neuromodulation is a non-invasive brain stimulation therapy that improves symptoms in treatment-resistant depression, anxiety, and post-traumatic stress disorder. However, the current neuromodulation method is trial-and-error. EEG technology can analyze patients’ neural activity and personalize neuromodulation therapy by targeting specific brain regions that correlate with symptom improvement.
AI in Accessible Mental Health Care
AI tools are not only improving diagnosis and treatment planning, but they are also increasing accessibility to mental health care. The WHO guideline on AI for mental health care emphasizes the need for digital and AI solutions to reach underserved populations, including those in low-and middle-income countries, rural areas, and refugee camps.
One example of how AI is increasing accessibility is the use of mobile-phone-based psychological interventions. In low-and middle-income countries with limited access to mental health care, mobile phone interventions offer a low-cost, scalable, and effective option. For example, a randomized-controlled study on mobile phone-based CBT showed that it significantly reduced symptoms of depression and anxiety in women living in low-resource settings in India.
Another example is the incorporation of AI-powered chatbots in mental health interventions. Chatbots can offer immediate support and counseling in real-time and deal with mental health-related queries without the need for human therapists. For example, the CoApt AI-powered chatbot, available on Facebook Messenger, can provide information, self-help exercises, and emotional support to students worldwide.
Overall, AI tools are transforming mental health care by improving diagnosis, personalization of treatment, and accessibility. Although AI tools’ potential is vast, there are still ethical considerations around privacy, data sharing, and reliability of these technologies. Nevertheless, AI technologies are undoubtedly the future of mental health care, paving the way for more accessible, affordable, and effective treatments.