Tag: Mental health

Thomas Insel MD has just written “What’s next for digital mental health companies?” in Stat News, a brilliant thought piece on the state of digital mental health. He cuts through some of the hype surrounding mental health startups fuelled by $5.1 billion in venture capital investment in 2021, while pointing to the infinitely larger potential of applying technology to improve a system that today fails most people with mental health problems.

It’s a testament of how limited mental health services are today that mental health startups are growing so fast by doing relatively simple things like moving clinicians from an office to a screen and helping them accept insurance. It is a great start, improving access to mental health professionals outside major cities and making the process of finding a clinician more efficient. Locating a therapist or psychiatrist who accepts insurance and has availability was nearly impossible before Sondermind, Headway, Alma, Spring Health, Lyra Health, Modern Health and Cerebral came along. However, most of those startups target people who have private health insurance and/or generous employer benefits, leaving the majority of the US population just as underserved as it was by the old system. In 2020, only 6.6% of Americans had mental health outpatient services paid for by their employer, 39% by private health insurance, over 40% paid out of pocket (SAMHSA survey). Merely moving the same pool of clinicians online also doesn’t solve the fundamental problem that we have far fewer clinicians than we need: a shortage of 6,984 according to the latest HRSA numbers, which is probably an understatement.

I agree with Tom that the digital mental health industry – and digital health more broadly – is in its infancy. I worked in financial services and retail when they were being transformed by technology in the late 1990s and early 2000s. Healthcare is 20 years behind those industries. One key factor in retail and finance moving faster was that consumers have a lot more power and choice in those industries; they voted with their feet and moved towards better offerings quickly. My first startup job was at one of the ecommerce darlings of the time, eToys, which was backed by big VCs like today’s mental health startups. I didn’t understand until much later that we weren’t in the business of selling toys; we were in the business of providing a better customer experience through technology. Instead of hunting around mall toy stores for that hot out-of-stock-everywhere toy, grandparents could have it delivered straight to the kid’s home, gift-wrapped. During the holiday season the whole company worked in the warehouse to make this happen.

I also share Tom’s optimism that technology has the potential to truly transform mental health care. His point about measurement and accountability reminded me of my early ecommerce experience. I remember when web analytics companies invented page view and session metrics in the early 2000s. Before then we were measuring ‘server hits’ (a thoroughly useless metric) and had no idea what happened between a user coming to our website and placing an order – or more often leaving without placing an order. Along came sophisticated web analytics, and it was like a light switch being turned on. We could see what our users were doing on the website, which pages and features were a success and which needed improvements. As product managers started running A/B tests and using behavioural data to make product decisions, consumers were able to shape products in a way that had never happened before.

Like retail before web analytics, mental health is barely measured in clinical practice today, despite a proliferation of scales. Eiko Fried, a professor at the University of Leiden who studies mental health measurement, analysed the content of 7 leading depression scales and found 52 disparate depression symptoms (Fried 2017). The most commonly used measurement tools are questionnaires like PHQ-9 and GAD-7, which Pfizer generously made freely available to help doctors assess whether a patient needs medication 🤔. These surveys ask questions such as: “How many days in the past 2 weeks have you been feeling bad about yourself — or that you are a failure or have let yourself or your family down?” and “How many days have you had trouble falling or staying asleep, or sleeping too much?” Humans are not very good at self-assessing and tracking these data points over time; technology can help here. A new crop of mental health measurement companies like Ksana Health, HealthRhythms and Kintsugi are working on more accurate ways to measure mental health, using passive sensor data from smartphones, daily surveys called ecological momentary assessments (EMA) and voice diaries. My company Flourish Labs is developing håp, an app combining short EMA-style self-reflections that we call Check-ins with sleep data from wearables to help our members track their own mental health and wellbeing. Our app is still in beta and we’re evolving it with active input from students (our first user group), with the help of our partners Active Minds and Youth Era.

eToys went bust in 2001, as did many other ecommerce pioneers along the way. Today, ecommerce is nearly 25% of the world’s retail sales, and nearly 40% in early adopter countries like the UK. Amazon went on to a build huge business with a relentless focus on better customer experience and analytics. Some argue that the major tech companies are overdoing the analytics and user tracking these days, but there is no doubt that it has led to vastly better (and free) products and experiences for users. Mental health and wellbeing data is more sensitive than your shopping basket content and browsing habits, so as a young industry we have to be much more thoughtful on how we use data to benefit people who want to improve their mental health, with their permission.

It will be interesting to see who emerges as the Amazon of digital health. Amazon being one of the contenders of course… although I’ll place my bet on a startup that nobody has heard of yet today.

A user research report report on opportunities for tech-enabled innovation in student mental health from Shift and X.

Recently I wrote about Amber, the early stage mental health project I led at X. We developed prototype technologies to better measure mental health, including a low-cost, portable, research-grade system to make it easier to collect electroencephalography (EEG) data, and machine learning methods to make it easier to interpret these data. We wrapped up our work at X and made our technology and insights freely available to the mental health community. You can read more about Amber’s story and access our technical resources on the X blog.

Today we are sharing a report on the user research with students and clinicians that we conducted between 2018 and 2020 in partnership with Shift, a social innovation charity.

Project Amber asked the question: what if we could make brain waves as easy to measure and interpret as blood glucose, and use the results as an objective measurement of depression? From my undergraduate degree in psychology I was familiar with EEG, a 96-year-old technology to measure electrical activity in the brain. Today EEG is primarily used in neuroscience research labs and epilepsy clinics. Making EEG more accessible and usable at scale would open up a host of possibilities to deploy it in primary care, counselling and psychiatry. We had a promising technology, but we had to identify specific user needs to figure out how the technology could impact real-world problems.

We started with informal user interviews, with clinicians and people with lived experience of mental health problems. We spoke with primary care physicians, therapists, counsellors, clinical psychologists, psychiatrists, and social workers. We spent time with young people and their parents, mothers who experienced perinatal depression, and people who had struggled with depression all their life.

In one of my interviews with a physician working in a primary care practice at a London university, I first learned about the huge unmet need in student mental health.

Me:  “What percentage of your patient visits are about mental health?”

Dr M:  “Seventy percent.”

Me: “Did you say seventeen?”

Dr M: “No, seventy. Most of my patients are students between 18 and 24 years old. They don’t have many health issues other than sexually transmitted diseases and mental health. Around exam times when they get stressed, nearly 100% of my visits are about mental health.”

She told me about her challenges in triaging students in a 10-minute appointment: deciding who will likely get better by themselves, who can be treated within primary care, who to refer to a mental health specialist, or who needs a safety plan because they face immediate risk of harming themselves. 78% of students on her campus self-identified as having some mental health issues. The average waitlist for therapy was 3 months. Every year there were student suicides at her university.

Back at my desk I researched statistics and literature on student mental health, which concurred with Dr M’s experience. There is a crisis on both sides of the Atlantic. Ever greater numbers of students in the UK and US are presenting with mental health problems. Higher education institutions are struggling to keep up with the demand for support. These challenges are exacerbated by a backdrop of multiple societal crises, including the climate emergency, racial injustice, systemic inequity, and now a global pandemic. This means there is great need for change and even greater potential for innovation. 

After Kit Yee Au-Yeung joined my team as a product manager, we partnered with Shift, a London-based social innovation charity with experience of user-led design and deep knowledge of the youth mental health space. We commissioned Shift to conduct more formal user research into student mental health to learn more about the experiences of students and clinicians working in higher education settings. In a series of studies between 2018 and 2020, Shift tested how Amber’s proposition of introducing a new, more objective measure of depression and anxiety would resonate with clinicians and students with lived experience of mental health problems: how they might use it in their daily lives and professional practice, and what the challenges might be in introducing such a radical new approach.

We found student mental health to be a fertile ground for tech-enabled innovation for several reasons. There is growing unmet need for college mental health services. Students have been pushing for change in mental health and are often early adopters of technology. Universities have both a moral and financial incentive to improve their student mental health systems.

Shift’s report highlights the current challenges in college mental health, the role that better mental health data can play in empowering both students and clinicians, and the importance of putting people at the heart of tech innovation. We emerged with three clear recommendations for those working to improve student mental health:

1. Support students to track their own subjective data
2. Introduce objective data into therapeutic interactions
3. Make data accessible and interpretable for students and clinicians

By sharing our insights as well as open-sourcing our technology, we hope to inform and enhance the work of other researchers and innovators striving to improve mental health services and outcomes for students. We also hope to encourage much-needed investment into further research, tools, and services to improve student mental health, accelerating systemic change towards a world where all students can get the mental health support they need.

Learn more about our user research and download the report on the Shift website.