This mental health app could change how we understand and treat schizophrenia

When I was training in psychiatry, it was always difficult to see patients in the emergency department. We would try to understand their situation as soon as we could, but you are often working to make the best decision with limited information.

Then one day a patient came in and it seemed like something very bad had happened in a personal relationship. The patient agreed to let us read their messages and it was immediately clear what was going on.

It was an eye-opening moment for me—seeing how much information phones can hold to help guide mental health treatmentespecially in schizophrenia.

Unanswered questions in schizophrenia

The way we understand schizophrenia is largely based on research study participants reporting on their condition or circumstances – often quite rarely.

This approach has enabled a lot scientific advances, but we now know that each person has a quite different lifetime experience of the condition. People live in different environmentsthey have different stressors and experience different symptoms or changes over time.

Symptoms of schizophrenia

There are three main types of schizophrenia symptoms:

• positive symptoms (for example, hallucinations)
• negative symptoms (for example, feeling less social or less engaged)
• cognitive symptoms (for example, impaired memory or concentration)

It is such a complex, dynamic disease that it has become nearly impossible to understand using traditional measures and surveys. For example, there are still very limited methods for predicting relapse episodes, and while the cognitive symptoms of schizophrenia are often the most devastating to people’s lives, they are the most difficult to measure.

Yet we are still surprised when people end up back in hospital.

This limited understanding of schizophrenia has also prevented us from developing many new treatments or interventions.

Scientific advances begin when we can measure and quantify what is happening. This is why we need better measurements and tools to understand schizophrenia. And this is where smartphones get so exciting.

The untapped potential of mental health apps

Smartphones are incredibly powerful pocket computers.

They have very advanced sensors that can measure things like sleep, activity and heartbeats, but they also have the ability to respond to these measures and actually provide treatment. We learned this during COVID-19, when doctors were able to schedule video call checkups or use apps to send notifications.

What is even more exciting is that most people in the world now have access to smartphones. We no longer have to give someone complex medical equipment or ask them to take time off work to come to the lab for a scan. The technology can also be easily shared and adapted to work in different cultures, languages ​​and countries.

Ultimately, this makes smartphones an infinitely more scalable tool than existing methods.

But what does this look like in practice, what can you do with all this data once you’ve collected it, and does it work in different countries?

This is what we are investigating with our Wellcome-supported project, SHARP (Smartphone Health Assessment for Relapse Prevention), with a multidisciplinary team based in India and the US.

How a mental health app can predict relapse in schizophrenia

We have developed a mental health app called mindLAMP to understand when someone may be at risk of relapse into schizophrenia.

After securing the appropriate ethical clearances, we are able to use mindLAMP to collect data from one’s smartphone sensors. We can look at digital markers like geolocation, movement and screen time, or even send notifications to ask if they can take a survey on their phone.

We can then use these digital markers to predict when someone is not doing well by identifying anomalies in the data.

The advantage of this approach is that we are looking at each person through their patterns and their phone. It’s not perfect, but it’s certainly better than chance, and it’s better than just asking people how they feel in a poll.

We were also able to adapt mindLAMP for different cultures and regions.

Working with our colleagues in India, we quickly learned that flexibility is very important.

The application is designed in a modular system and is available and free to use for any researcher in the world. This means that clinicians and researchers can tailor the app to their requirements: they can change the language and images, choose the sensors they want to use, write surveys, add education and activity elements – or include none of the theirs.

It’s already been translated into Korean, German, Italian, French, Mandarin, and Spanish, and is used for everything from monitoring adolescent screen time to managing cognitive symptoms.

What’s next for the mindLAMP app?

We’ve probably gone through over 100 app updates – most of them driven by service users or patients.

It’s a unique challenge and requires a diverse team of people with many different expertise – from engineers and data scientists to psychologists and mental health specialists. We certainly don’t look like a traditional research team, but diverse teams bring new ideas and perspectives and challenge your ways of working.

We hope that the data that mindLAMP can collect will continue to advance new discoveries in schizophrenia research. Ultimately, our goal is that this can be translated into useful tools for a clinical setting.

Now that we know the app works, we want to see if smartphones can provide quick and easy tests that can tap into the various cognitive symptoms that affect people with schizophrenia (such as attention, memory or problem solving). For example, we can use it to see if a new medication improves cognition or if a relapse affects someone’s problem solving.

The role of technology in all healthcare will continue to grow, especially in mental health care.

As the two worlds begin to merge more, I think it will become standard to have teams with very different experiences and perspectives; bringing together experienced UI and UX design people, data scientists, patients, researchers and ethicists, all working towards the same goal. It’s a very exciting prospect for me.