MedCity Influencers, Employee Benefits

Quantifying stress & anxiety: Why corporate wellness programs will play a pivotal role in this paradigm shift

Establishing digital biomarkers which correlate physiological parameters with mental health and wellbeing not only has the potential to provide more reliable tools for guiding diagnosis and evaluating patient outcomes but will also improve our understanding of the pathophysiology of mental disorders

The past decade has seen us come on leaps and bounds as a society in our awareness and understanding of the scale and impact of mental health problems. In recent years, the focus has switched somewhat from reaction to prevention in parallel with the healthcare industry as a whole, in a bid to secure the sustainability of care services.

The economic impact of the ‘mental health epidemic’ is a key driver behind governments’ and businesses’ move towards more preventive wellbeing initiatives. For instance, the World Health Organization (WHO) estimates that mental health problems in the workplace cost the global economy $1 trillion annually in lost productivity.

Stress and anxiety contribute heavily to this statistic. Stress is defined as the body’s reaction to feeling threatened or under pressure. Anxiety, which is often linked to stress, is defined as a feeling of unease, such as worry or fear, which can be mild or severe and is the main symptom of several mental disorders.

In the UK, for example, 57% of all working days lost to ill health were due to stress and anxiety in 2018. It’s a similar story in the US, where it’s estimated that over half of all working days lost annually from absenteeism are stress-related, with the annual cost in 2013 alone equating to over $84 billion.

Stress and anxiety can also have a significant impact on an individual’s physical health, affecting their work performance and productivity and causing further absenteeism. This form of poor mental health can impact physical health either directly through autonomic nervous system activity or indirectly as a result of unhealthy behaviors (e.g. poor diet, physical inactivity, alcohol abuse and smoking), increasing an individual’s risk of developing cardiovascular problems.

It is therefore in an effort to break this chain, and in doing so save costs long-term, that employers are increasing their focus on establishing effective wellness programs, meaning any promotional activity or organizational policy that supports healthy behavior in the workplace and improves health outcomes. Corporate wellness programs nowadays include anything from healthy eating education, financial advice and access to weight loss and fitness programs, to more direct healthcare such as on-site medical screening, stress management, smoking cessation programs, and counseling services (in the form of employee assistance programs).

And this certainly can save costs long-term! Most famously, Johnson & Johnson leaders estimate that wellness programs have cumulatively saved the company $250 million on healthcare costs over the past decade; with a return of $2.71 for every dollar spent between 2002 and 2008. It’s no surprise, then, that in 2020 the workplace wellness industry was estimated to be worth $48 billion globally.

Recent innovations in the space include the integration of wearable or smartphone technologies, used by employees to monitor and collect physical health data. These technologies provide employees with real-world physiological health insights to further incentivize participation in programs and increase and maintain their engagement. They simultaneously provide employers with an insight into the overall physical health of their workforce.

A golden opportunity to transform our relationship with mental health

However, with this most recent integration of digital health technologies comes a hitherto unrecognized opportunity to transform our understanding and treatment of mental health and wellbeing.

One of the primary barriers to delivering quality mental health care throughout history has been the difficulty in establishing accurate and objective methods to diagnose, assess and monitor treatment outcomes for psychological conditions. As was explained so eloquently by Washington University in November last year, if patients display symptoms of a heart attack, there are biological tests that can be run to look for diagnostic biomarkers that determine whether they are indeed suffering a heart attack or not. However, in the case of mental health disorders, the window by which we access the mind is still through psychological questioning, not biological parameters.

Mental health professionals screen, diagnose and monitor the symptoms and outcomes of patients through self-reported methods prone to excess subjectivity and therefore unreliability, such as diagnostic interviews and questionnaires. A patient’s self-reported symptoms are correlated with the ICD or DSM diagnostic manuals, yet challenges arise in the high heterogeneity of mental illnesses, low inter-rate reliability (i.e. poor agreement between clinicians’ diagnoses) and high comorbidity.

There is therefore a need to expand further than solely symptom-based to biology-based characterization of mental health conditions if we are to combat this unreliability and establish more evidence-based methods for diagnosis and monitoring, similar to our approach to physical illness.

So, how do we do this?

The National Institute for Mental Health for instance has already taken the first steps towards this with the RDoC (Research Domain Criteria). Advancements in MRI technology have also enabled research into understanding brain activity in certain depressive conditions.

But the most exciting development lies in the proliferation of wearable and smartphone health monitoring technologies. As the ability to collect vast amounts of physiological health data becomes more and more ubiquitous, the opportunity to utilize machine learning (ML) to extract new insights into the physiology of each individual grows larger.

With this comes the chance to uncover and establish personalized digital biomarkers for mental health conditions; described as indicators of mental state that can be derived through a patient’s use of a digital technology. These digital biomarkers can cover physiology (e.g. heart rate), cognition (e.g. eye movement on screens), behavioral (e.g. via GPS) and social (e.g. call frequency) factors. However, it is physiology that concerns us here.

Corporate wellness programs provide the perfect environment to explore the use of wearables and smartphone sensors in uncovering digital biomarkers which link physical health to mental wellbeing due to the huge potential benefits for all parties involved; employers and employees.

For example, by validating elements of cardiopulmonary functions as a digital biomarker for excess stress or anxiety disorders (a relationship for which some empirical evidence already exists), employers can not only identify stress and anxiety risks in the workplace and intervene earlier to protect employee mental wellbeing, but also establish an evidence-based approach for evaluating the effectiveness of workplace wellness initiatives. This is due to the fact that quantitative cardiopulmonary data would serve as a reliable measure of employee stress and/or mental wellbeing.

Employees, on the other hand, are empowered with insight into direct correlations between how they feel and their physical health. Therefore their increased engagement in wellness programs will improve their efficacy in preventing the deterioration of their mental health. For this reason, accessibility and ease-of-use must remain top of mind when choosing health monitoring technologies.

Finally, establishing digital biomarkers which correlate physiological parameters with mental health and wellbeing not only has the potential to provide more reliable tools for guiding diagnosis and evaluating patient outcomes but will also improve our understanding of the pathophysiology of mental disorders, in turn allowing for more effective preventive measures.

Photo: Creativeye99, Getty Images

Bipin Patel is CEO & Founder of electronRx, a deep tech team of interdisciplinary scientists and engineers developing novel technologies to sense the physiological environment and inform personalized therapeutic interventions. Dr. Patel is an entrepreneur with over 20 years of biomedical engineering, drug development and commercialization experience. He previously held leadership roles at big pharma like Merck KGaA, GSK and Pierre Fabre.

This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.