How to Make Mental Healthcare More Accessible: The AI Therapy of Headspace

Introduction

Mental healthcare is becoming one of the most important fields to be taken into consideration by many governments around the world (World Health Organization, 2021). People and countries are realizing the need for proper programs and interest in mental health care, and that there are still a lot of needs that have not been satisfied yet (Andrade et al., 2022). According to recent surveys, mental health is considered more important than physical health (Elfein 2022). However, the importance of recovery in the scope of mental health has been addressed seriously only in recent years (Bauer, Wistow, Hyànek, Figueroa & Sandford 2018; Senneseth et al., 2022). In this regard, existing literature has highlighted many barriers to mental health access (George, Daniels & Fioratou 2018). They include financial, communication, and cultural barriers (Kohn et al., 2022; Nester et al., 2022).

Despite the persistent challenges, contemporary research has begun to unveil the potential breakthroughs in overcoming barriers to mental health services (Appio et al., 2023). This discernible shift is attributed to the technological advancements and artificial intelligence (AI) innovations that have been introduced during the unprecedented circumstances of the COVID-19 pandemic (Aleem et al., 2023). These developments offer novel and distinctive avenues for the delivery of mental health services, suggesting a transformative impact on the traditional constraints previously encountered in this domain. Despite this recent progress, we still lack studies that provide an in-depth analysis of how mental healthcare can be more accessible using AI (Appio et al., 2023). This issue has become particularly important in the crisis context (Aleem et al., 2023). Therefore, in this book chapter, I aim to examine the following research question: “How can AI make mental healthcare more accessible during an emergency or a crisis such as the COVID-19 pandemic?

To answer this research question, I will perform an in-depth analysis of a single case (Eisenhardt & Graebner, 2007; Siggelkow, 2007), that is Headspace, a company that has found a very innovative and unique way to deliver mental health services through AI technologies and making them available everywhere and at any time. Two reasons have driven me to conduct a single case study. First, the exploration of a single case study epitomizes a distinctive and critical case in challenging a well-formulated theory (Ravenswood, 2011; Yin, 2009). Second, since only limited theoretical understanding subsists about how companies can make more accessible mental healthcare during an emergency crisis such as COVID-19, the benefits of extracting many details in a particular case (Eisenhardt & Graebner, 2007) allow theory to emerge from the data can be a valuable starting point (Ravenswood, 2011; Siggelkow, 2007). Therefore, it seems that AI literature can benefit from the conduction of a single case as a revelatory case of how firms can make more accessible mental healthcare through the use of AI therapy.

This study underscores three key findings. Firstly, it illuminates a shift within organizations from profit-oriented to human-centered orientations, with a particular focus on the transformative role of social innovation in reshaping contemporary priorities, especially in the context of artificial intelligence (Berretta et al., 2023). The emphasis lies on the compelling need for enterprises to move beyond conventional profit-centric motives, advocating instead for a holistic commitment to enhancing the general welfare (Ferrigno and Cucino, 2021). This transition holds theoretical significance by revealing the evolving ethos of modern corporations and emphasizes the crucial importance of societal impact alongside economic success (George et al., 2023).