The lockdown imposed to curb COVID-19 has had a profound impact on how we live and communicate with each other. During this lockdown, interpersonal communications, content consumption and digital workplaces have necessitated an overreliance on screens that may have adverse effects on our mental health. With people spending more time in front of screens during the lockdown, understanding the maladaptive patterns of Internet and screen use — that may adversely affect mental health — is crucial. Analysing mood fluctuations in response to computer use can be one such way of measuring and tracking mental health. Mood refers to an affective state that can either have a positive or negative valence. Thus, in context of the pandemic and the unique mental health challenges it poses, examining the efficacy of technological solutions that aid in self-management of mood is a policy imperative that must be examined.
Mood tracking applications lie at the intersection of Artificial Intelligence (AI) and mental health, and have been attracting enormous interest from big tech companies like Amazon and Google. The flagship service provider in this domain that monitors cognitive functioning through AI is called “Mindstrong”. This application has already secured a Series C funding of US$ 100 million, with one of the key investors being from Jeff Bezos’s VC firm. Thus, with Silicon Valley having shown interest in this burgeoning field and with the perceived importance of such applications heightened in context to COVID-19, examining its potential benefits and dangers is key.
Mood tracking applications have been built with a consensus that creating technological solutions to help self-management of mental health is an important undertaking. Preliminary research has indicated that self-tracking mood apps have enabled proactive self-regulation of mental wellbeing, which is an important step towards improved mental health outcomes. Most of these applications rely on user’s self-reporting, as one would do while keeping mood journals to aid in the therapeutic process. Such apps generally require users to report on their mood through the day and the regularity of mood updates determines the reliability and accuracy of the data. Such mood tracking applications have been devised both in service of general mental health care and specific disorders.
The other kind of mood tracking apps use machine learning to track moods and do not require users to self-report on how they feel. Strategies like micro-facial expression analysis, examining human-machine interactions — like swiping and clicking patterns — are some biomarkers used to predict and provide mental health assessments. Thus, automated mood trackers capture one’s mood as it evolves through the day in response to sustained laptop use and provides users with quantifiable assessments on their mood and what shapes it. Research on the efficacy of such automated mood detection applications is at a nascent stage. Nonetheless, researchers in the field are optimistic about its prospects thereby reiterating the importance of examining the benefits and vulnerabilities of such technological solutions to aid mental health care.
One of the biggest benefits of such apps is its ability to make people self-reliant in monitoring their own mental health. Apps that notify users on how their patterns of Internet use shapes their mental wellbeing can allow them to be more cognizant of maladaptive usage patterns and in turn, forge necessary changes that help improve mental wellbeing outcomes. However, monitoring mood through self-reporting requires diligence and regular updates over a sustained period to prove effective, and such automated apps can help those that are unable to devote time and energy in monitoring their mental health. User testimonials of one such mood tracking application has also indicated how tracking mood helped users feel more in control of their wellbeing and allowed them to make informed decisions on how to better their happiness levels. Along with promoting self-management of mental health, such apps can also be leveraged by therapists. Therapists often require their clients to monitor their moods, and therapists have found such applications to greatly aid in improving care and complimenting the therapy process.
In countries like India wherein mental health is often deemed to be a taboo subject, such applications can especially help democratize mental health care to some degree. Since many people in India resist the idea of therapy due to social stigma, apps that aid self-management of mood and forge self-awareness of mental wellbeing can greatly aid in reaching more citizens that may have otherwise been skeptical of seeking psychological care. Compounded by the fact that access to therapy is far more exclusive than access to a smartphone, the prospect of such applications helping the overburdened mental health care infrastructure in India surely warrants further probing. It must be noted that such apps cannot replace therapy and as iterated earlier, are extremely effective in conjunction with therapy. That being said, for those that are averse to seeking care due to stigma and social disapproval, the benefits of an app that at the very least allows one to monitor the effects of online behaviour on mood levels can greatly contribute to improving mental health outcomes.
With scandals involving data breaches coming to the fore in recent years, an immediate red flag for many skeptics correspond to privacy issues. While some applications in this domain are working towards better privacy standards, other apps raise doubts about transparency and consent issues. Thus, the privacy question is garnering attention, but there are also some relatively underexplored vulnerabilities of such applications that may impede its effectiveness and must be addressed.
One such concern corresponds to the Hawthorne effect, which refers to the tendency of human beings to alter their behaviour when made aware that they are being monitored. An innate and often subconscious desire to perform when made aware that an application may be monitoring one's facial expressions or emotional reactions may influence an individual's authenticity in experiencing their emotions organically.
Mood trackers also suffer from an innate lack of representativeness characterising their functioning that may impede their widespread applicability. Research has shown wide socio-cultural differences in how emotions are expressed and while there may be some universalities in emotional expression, subtler nuances are culturally sensitive. Thus, for mood trackers to gain global appeal across different socio-demographic contexts, the emotion detection algorithms need to be fed with a pool of culturally diverse data points. Since research in this domain is at a nascent stage, it is unclear whether such applications will be able to account for cultural variance in how mood manifests.
The increased emphasis on digital communications due to the COVID-19 pandemic has certainly raised fears of the ill-effects of increased screen time. This has increased the buzz surrounding mood trackers and the potential benefits it can have in the post-COVID world. However, at the heart of this dilemma on the efficacy of such applications is a bitter-sweet irony. Should we be using technological solutions to help alleviate mental distress when an overreliance on machines has also contributed to the problem? Is technology both the source and solution to a mental health crisis? These are difficult questions to answer. Nonetheless, the impact of mood trackers in forging self-reliance in addressing mental wellbeing surely seems to restore a ray of optimism regarding a better future for mental health — hopefully aided rather than worsened by technology.
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Prithvi Iyer was a Research Assistant at Observer Research Foundation Mumbai. His research interests include understanding the mental health implications of political conflict the role ...
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