Publication

Abstract : Recent statistics by the World Health Organization (WHO) show that one in eight individuals has a mental health challenge. Anxiety and depressive disorders contribute most to these challenges, and the condition has worsened due to the COVID-19 pandemic and the serious impact it caused. Even though proper diagnosis and treatment options exist, most affected people will have limited access to effective care. The prominent reason would be the limited availability and access to healthcare providers, but there are other grounds, such as social stigma and discrimination. Natural language processing (NLP) is the study of making computers intelligent by teaching human language. It is going leaps and bounds, impacting every walk of human life, from astronomy to agriculture and healthcare to human resources. The role of NLP is well studied in healthcare, and innovative healthcare applications at scale are introduced daily, which can save millions of lives globally. Healthcare researchers and practitioners recently realized the need for initiatives and technologies to address the mental health challenges imposed by lifestyles, health issues, and other reasons such as the pandemic. As a result, the number of research papers published on the theme “Natural Language Processing for mental health” and added to the digital repositories significantly increased. The widespread adoption of digital technologies paved the way for unprecedented data growth, often called “digital footprints.” The applications of such digital technologies include social media platforms such as Facebook and Instagram, where people share their thoughts and feelings. These platforms may contain invaluable information that can be unearthed to analyze an individual's mental health and can give appropriate care if needed. There are several studies conducted on using the immense potential of artificial intelligence to analyze such data, but there are still a lot of avenues to be explored and studied. In this connection, this chapter analyzes and critically reviews the already-reported studies on the role of artificial intelligence in general but natural language in digital well-being and mental health. This chapter also discusses the challenges of using artificial intelligence and natural language processing to monitor and analyze individuals’ mental health. It also proposes future research dimensions on better harnessing the power of artificial intelligence in the context of mental health.