We are living through an era of technological revolution. The number of smartphone users worldwide has been exponentially increasing over the last few years, especially in emerging economies such as India. This has opened up a world of opportunities across many commercial industries. However, applications aiming to improve mental health remain largely untapped. Here, technological innovations in smart medical devices and online platforms could improve access to mental health services, as well as identify warning signs and provide interventions. Thus, if we approach these technologies with responsibility, it could help us bring mental healthcare to people who need it most. Although data-driven services also carry concerns with privacy and confidentiality, emerging research indicates that these technologies are a useful supplement to traditional therapeutic practices. We have countless exciting opportunities waiting to be developed, and we have barely scratched the surface.
The first major asset that technology brings is the ability to provide treatment at scale. Traditional mental healthcare services remain out-of-reach for many, but online services and platforms could provide new delivery models that can reach significantly more people. Such platforms can offer similar styles of therapy provided by mental health practitioners while allowing patients to bypass social taboos or discomfort about visiting a therapist or psychiatrist in a physical location. These models can also improve education and validation of mental health goals among the population.
Mental healthcare technologies could potentially open up opportunities to detect the early onset of psychological symptoms. We have been developing increasingly intimate connections with our devices, allowing devices to examine individual activity patterns closely. This gives them the power to detect patterns that we are unaware of ourselves, and commercial industries use this information to sell commodities.
However, they may also detect and predict the onset of mental health issues early in their development, and alert people to take small steps in rectifying irregularities. These interventions can be personalised to the user, which overcomes the limitations of a generalised and un-relatable public education of mental health. Unfortunately, this potential remains mostly undeveloped and clinical research has yet to test any reliably effective techniques.
Researchers in digital phenotyping learn how data from technology users can detect, record, and predict health diagnoses. For example, the symptoms of depression often include changes in appetite, energy, sleep, and activity – a lot of which phones and wearable can directly detect. Our research has shown that we can use apps to track depression and anxiety levels (Curtis, Pai, Cao, Moukaddam, & Sabharwal, 2019) and the worsening of symptoms carries a specific digital “signature”. Devices that detect significant variations in these patterns could conceivably trigger an alert to the user. This is taken further with the field of digital therapeutics, which aims to provide personalised, data-driven therapy to technology users and can include recommendations to change a routine, like exercising or mindfulness. Such apps could also help people become more aware of their mental state and understand how their symptoms relate to mental health.
Of course, the use of technology has its concerns; privacy and confidentiality being the most obvious ones. This is magnified when collected data is shared with other entities. We also don’t have a physiological definition for ‘normal usage of technology’, so features such as comparing one’s patterns to ‘normal’ or ‘average’ groups in aggregate and anonymised forms becomes problematic. Another concern about the use of technology is related to the underlying nature of mental health conditions. For instance, people that are depressed tend to lack motivation or energy to improve their state, so there is no guarantee that they will utilise their technology as prescribed. In other cases, constant alerts and recommendations may even worsen symptoms to the point where a person needs closer treatment. These are just two of several examples that indicate the need for clinical research to examine data-driven therapies with the same rigour that it tests and develops other modes of treatment.
Technology can help us identify and predict the early onset of symptoms and even provide personalised treatment. Digital phenotyping and digital therapeutics are intense areas of research with exciting and frequent developments. Yet even with these possibilities, technology will always have its limits. With what we know today, digital phenotyping and therapeutics are best used to support a formal treatment plan. Here, feedback between the patient and their symptoms can increase the clarity of their diagnosis, their awareness of physical patterns and triggers, and treatment adherence. We have a chance to work with the mental health community, to experiment, to learn, and to use the power of technology to create breakthroughs that the field so desperately needs.