Can technology address gaps in mental wellbeing?

The World Health Organisation (2001) defines health as a state of physical, mental, and social well-being and not merely the absence of disease. Mental health goes beyond just the mere absence of mental disorder. It is more about realizing one’s ability, coping with day-to-day stressors, becoming productive, and making a contribution to society.

Mental health and physical health are strongly linked, i.e impact on one leads to an impact on the other. Mental health can have a significant impact on your productivity and functioning. If this is the case then why don’t people seek out help for mental health? What are the challenges in the area of mental health?

The challenges in mental health can be seen at macro and micro levels.

Macro challenges include lack of awareness, stigma, and cultural biases. Micro challenges on the other hand include lack of diagnostic markers, reliance on self-report, and memory biases. Let's know more about them one by one.

Macro-challenges : awareness, stigma and cultural bias

  • People aren’t aware of mental health, especially in a developing country like India and due to this lack of awareness (Lysaker, Buck, Salvatore, Popolo & Dimaggio, 2009) people aren’t focusing much on their mental well-being, thereby impacting their overall well-being.

  • There are cultural biases (Snowden, 2003) as well. The symptoms of mental disorders can be culturally influenced. E.g.- in India people talk about depression more in terms of physical symptoms like headaches, fatigue, etc. whereas in Western countries people talk about depression more in terms of emotional symptoms like the sadness of mood or loss of interest. All these results in a poor diagnosis.

  • Another reason why mental health is getting overlooked is because of the stigma associated with mental health (Kakuma, Kleintjes, Lund, Drew, Green & Flisher, 2010). It is because of this fear of being labeled or looked down on by society for reaching out for help that people don’t approach a mental health professional or reach out to them only in emergency cases when things go out of control or the symptoms are at their peak.

However, a proportion of people are aware of their mental health issues and reach out to mental health professionals, but they aren’t able to benefit much because of the micro-level challenges.

Micro-challenges : markers, self-reports and memory bias

  • There is no single test of mental health that can help us to reach a diagnosis unlike those for physical health diagnoses like diabetes.

  • Even if there are clinician and self-assessment tools for screening for different mental disorders, they are time-consuming and rely on self-reports (Nevin, 2009) which may be unreliable, inadequate, and time-consuming.

  • At times, people also under-report their symptoms as they don’t trust the professionals or they forget to report (memory bias).

So we need a solution that can track mental health with fewer biases and more objectivity. All these indicate the need for a powerful solution that can determine the mental health or well-being of an individual.

So we need a solution that can track mental health with fewer biases and more objectivity. All these indicate the need for a powerful solution that can determine the mental health or well-being of an individual.

Can psychiatry, smartphone technology and analytics combine together to make a powerful solution?

All these bring us to technological advancement that is happening in the area of mental health (Huckvale, Venkatesh & Christensen, 2019). Researches have shown that we can leverage technology to identify different behavioral markers like sleep, physical activity, phone usage, the social interaction that are associated with mental health, which can be measured objectively.

Objective assessments key to improved screening and diagnosis

These are passive data as they are collected without direct input from the individual (Nicholas, Shilton, Schueller, Gray, Kwasny & Mohr, 2019). Various studies indicate that wearables and smartphones collect data on these markers in a natural environment (Plarre et al., 2011). E.g.- Passive data like keyboard signals and voice signals have helped to detect relapse (Tsanas et al., 2017). Thus, this can help not only in identifying early-onset and relapse due to continuous monitoring of behavioral markers but also in improving precision in diagnosis and providing early intervention for psychiatric disorders.

In a developing country like India, smartphones can provide us with a solution that provides accuracy in data and is cost-effective. There are various reasons for using smartphones. It is accessible to many people.

According to a report by news18 (Jan 2020), around 50 crore of people in India have smartphones.

They come with inbuilt sensors that can help in tracking human behavior and quantifying them, which in turn can help understand the mental health of the individual. These data can be collected passively, i.e. without requiring the active inputs from the people, thereby making the diagnosis more accurate, precise, and culturally relevant (Onnela & Rauch, 2016). It reduces cultural biases that result from using self-report assessments. The smartphones also come with sufficient memory capacity that can help to store and process data collected over a period of time. There are various mental health apps in the market. However, there are very few research-based apps that provide solutions using passive data.

Join Mannki

Mannki is a mental health app available in the google play store for android phones. We at Mannki are trying to improve the screening and diagnosis of mental health in India by continuously tracking the user's mental wellness journey. As with other apps, there are concerns related to informational privacy and data security (Maher et al., 2019), we at Mannki take privacy issues seriously which ensures that there is no data leakage. The app uses clinician-recommended diagnostic tests alongside passive sensing through a user's smartphone to help them understand their mental health better.

Mannki aims to overcome many of the challenges like imprecise user inputs, lack of diagnostic markers, stigma, and poor access. We are trying to bring transparency and care for undiagnosed problems with precise and measurable inputs. Currently, we are in a research phase where we are trying to collaborate with institutes to understand behavioral markers and build algorithms for various psychiatric disorders.

Join us and support us in improving our model. Write to us at