Mental Health Support Goes Digital

Using technology to analyze behavioral data can help capture often overlooked aspects and offer greater support amid the patient journey.

AsianScientist (Oct. 10, 2021) – As World Mental Health Day is commemorated this October 10, 2021, the global mission remains clear—pursue dedicated efforts to support the millions affected by mental health issues. Underdiagnosis notwithstanding, mental health conditions such as depression and anxiety account for 10 percent of the global disease burden, contributing to a considerable amount of life lost to illness and disability.

Despite this, effective patient care remains elusive. Diagnosis is rarely straightforward which in turn hampers effective treatment. Many never gain access to the treatment they need, while others often receive wrong or inadequate care.

This misalignment arises out of the range of overlapping symptoms and the still poor understanding of why and how mental health conditions develop. Moreover, the complex causal factors that contribute to mental health states often vary by person, including life events, familial relations, cultural norms, to name a few.

Given this complexity, a holistic approach that accounts for each person’s unique experiences and social contexts is vital to behavioral health. By deriving evidence from these real-world factors, artificial intelligence (AI) systems and new digital healthcare tools can transform how researchers and clinicians make sense of behavioral health data, driving better treatment development and advancing a personalized approach to care.

Accessing support through apps
Historically, mental health issues were typically dealt with separately from physical health and perceived as little more than an afterthought. However, the two are heavily intertwined; when either are left unaddressed, they can potentially ignite a vicious cycle that disrupts daily activities and quality of life.

For example, a chronic disease diagnosis is likely to be extremely upsetting, with many people experiencing depressive symptoms while managing physiological conditions like diabetes, cancer and hypertension. Meanwhile, prolonged mental distress can drive the risk for physical illnesses, causing individuals to forfeit healthy behavior like getting enough sleep or taking medication.

In many such cases, those who battle mental health issues and their damaging effects do so outside the clinic, yet are unable to access effective support when they need it most. Digital solutions are making inroads to alleviate these barriers like limited access and social stigma, allowing care to transcend the boundaries of medical centers.

To support individuals in their day-to-day, various digital tools are emerging to enable increased access to care services, from wearables and trackers to telehealth platforms and digital assessments.

One example is reSET, the first digital therapeutics app to receive approval by the FDA in the US for treating substance use disorder (SUD). Developed by health tech company Pear Therapeutics, reSET delivers cognitive behavioral therapy to treat SUD in outpatients. The app uses progress tracking tools to monitor lapses and triggers, offering interventions and lessons to aid recovery and rewarding its users for compliance.

AI-powered healthcare analytics
Besides patient-facing tools like mobile apps, emerging technologies are also making headway in reinforcing behavioral health research with new data on patient behaviors and treatment effectiveness.

Before gaining authorization for clinical use, treatments are first vetted through randomized controlled trials, the gold standard for evaluating interventions. These controlled setups allow researchers to rule out the influence of other variables like demographic differences.

However, a drug that works well in clinical trials may not always be as effective in the real world. By excluding patient heterogeneity and other contextual factors from the picture, clinical trial data does not provide insights into nuances like missed doses, interactions with other drugs and other external factors that impact disease trajectory.

Most will find that the mental health journey is not linear. An additional challenge lies in that mental health disorders lack distinct endpoints or stages to indicate disease progression and recovery that other physical illnesses have, such as lab tests and biomarkers.

To better account for these complex factors, evidence from beyond the clinic adds an important dimension to understanding patient experiences. Innovations that enable use of real-world behavioral health data—such as Holmusk’s AI-powered analytics platform NeuroBlu—are urgently needed to generate new evidence.

By showing how treatments fare amidst each person’s unique context, real-world evidence can transform behavioral health’s approach to evidence-based medicine. Such information would guide researchers to refine drug development and clinical trials, while healthcare practitioners become equipped with more treatment options and can respond to patient needs effectively.

As the world reels from the pandemic’s distressing effects, communities are paying attention to mental welfare at long last. Importantly, the right digital tools can forge a deeper appreciation of behavioral health’s full complexity, harnessing analytics to innovate better treatments and drive better care decisions that patients need throughout their journey.

Asian Scientist Magazine is a media partner of Holmusk.


Copyright: Asian Scientist Magazine; Photo: Shutterstock.
Disclaimer: This article does not necessarily reflect the views of AsianScientist or its staff.

Asian Scientist Magazine is an award-winning science and technology magazine that highlights R&D news stories from Asia to a global audience. The magazine is published by Singapore-headquartered Wildtype Media Group.

Related Stories from Asian Scientist