Apps and wearable technology help to track sleep of people with mental health disorders

According to the findings of a recent review article, this type of technology could even help to recognize factors that correlate with mental health disorders
Ana Triana Hoyos (vasemmalla) ja Talayeh Aledavood tekivät tutkimuskatsauksen mielenterveyspotilaiden unta seuraavista sovelluksista ja laitteista. Kuva Matti Ahlgren / Aalto-yliopisto
Ana Triana Hoyos (on left) and Talayeh Aledavood reviewed research on apps and wearables used for sleep monitoring. Photo Matti Ahlgren / Aalto University

Mobile apps and wearable technology can help in monitoring sleep of people who suffer from mental health disorders. Researchers make this conclusion in a recent review article that will be published in July in the scientific journal Current Psychiatry Reports. These conclusions are being used in a major research collaboration between the Aalto University Department of Computer Science and University of Helsinki Department of Psychiatry.

Sleep problems relate to many mental health disorders, such as depression, anxiety, and schizophrenia. They can be a symptom of these disorders, but also a cause of them. For example, insomnia can worsen depression, make it last longer, and influence its relapse rate.

Most studies that were included in the review indicate that smart phones are suitable for monitoring behaviour of people with mental health disorders. Some studies showed that wearables can be used for this purpose as well.

The research findings indicate that apps and devices could even help to detect disorder-related factors. According to Talayeh Aledavood, the main author of the review, one such factor could be, for instance, how the person moves. This type of technology can easily monitor movement.

Aledavood is a visiting researcher at Aalto University Department of Computer Science and a postdoctoral researcher at University of Helsinki Department of Psychiatry. For the review, she and Aalto University doctoral candidate Ana Triana Hoyos collaborated with researchers from Harvard University, including John Torous, MD, and Jukka-Pekka Onnela, associate professor of biostatistics.

An app or a device can gather information in many ways, and that is why they have so much potential. By using a mobile device app, the user can report about factors related to their sleep. In addition, the app or device can collect so-called passive data, meaning that new data is collected without the user’s attention. The app or device stays active in the background, following what the user does.

Selecting a reliable app is still difficult

Despite the potential of smart devices, in order to use them in clinical settings, researchers need to be sure about their validity. They need to know what exactly the devices measure and how, and that they do it in a trustworthy manner.

This is still a challenge to both consumers and experts. Aledavood is worried about the fact that there are many apps and wearables for consumers, but it is difficult for the consumers to evaluate which ones can be trusted and which ones not. Research findings have shown that some products produce useless data, whereas others provide the user with incorrect information or advice.

John Torous, a co-author of the review, has studied which criteria should be used in the selection of a health app. He led a work group on the evaluation of smartphone apps for the American Psychiatric Association (APA), which resulted in the development of an improved health app evaluation tool that APA now plans to launch. In June, Torous and his colleagues wrote about the topic in the Lancet, an important medical journal. Researchers focused on how one can make an informed decision based on clinically relevant criteria, when selecting an app for the treatment of mental health disorders. While no single therapy or medical treatment is effective in treatment of all disorders, no single app or device can be used to treat all disorders.

Talayeh Aledavood is a visiting researcher at Aalto University Department of Computer Science. Photo Matti Ahlgren / Aalto University
Talayeh Aledavood is a visiting researcher at Aalto University Department of Computer Science. Photo Matti Ahlgren / Aalto University

But finding a reliable health app or device won’t benefit just people with mental health problems. It could also help people without any diagnosed disorders. “A lot of times, we think that we know our behaviour. We think we know that we sleep enough or too little. However, studies have shown that people make misinterpretations about their behaviour,” says Talayeh Aledavood.

Aledavood has tried many types of apps and wearables, but she keeps a couple of things in mind before downloading or purchasing anything. First, she considers what she actually wants from an app or device. Is her aim to sleep more or perhaps more regularly? Second, by using the gathered data, she makes her own conclusions instead of leaving it to the app.

“It may be better that people make their own research and, for instance, talk to their doctors, if they have real concerns. Apps can be used as some sort of support.”

Passive data could help to identify who is using the device

Smart phones and wearables are still a relatively novel phenomenon. Therefore, the number of studies focused on the topic is somewhat small but, according to Aledavood, increasing at a fast pace.

Right now, for example Aalto University and the University of Helsinki are running a research study titled Mobile Monitoring of Mood (MoMo-Mood) on which Aledavood is working. Aalto University researchers laid the groundwork for the project. They designed the prototype platform Niima (Non-Intrusive Individual Monitoring Architecture) for digital data collection in psychiatric settings, which is utilized in the research project.

Fourteen patients with major depressive disorder and 23 healthy controls participated in the pilot phase of MoMo-Mood. The researchers gave the participants devices that monitored their sleep, activity and factors such as heart rate and respiration. Based on the findings, mobile apps and wearables were feasible for tracking these factors. Moreover, by using passive data gathered by the used technology, researchers could identify whether the user was a patient or a healthy control with an accuracy higher than 90%.

Now the researchers have launched the actual MoMo-Mood study for which they aim to recruit up to 200 patients with various mental health disorders.

 

Further information
Talayeh Aledavood
Visiting researcher, Aalto University Department of Computer Science
Postdoctoral researcher, University of Helsinki Department of Psychiatry
Phone +358 50 5632 634
[email protected]

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