AI predicts success of digital health interventions

Health apps could be better tailored to the individual needs of patients. A new statistical technique from the field of machine learning is now making it possible to predict the success of smartphone-based interventions more accurately.

Photo

Health apps are increasingly used in the context of physical and mental illnesses. Usually, they do not replace traditional treatments but act as a adds-on – for example, to improve mood in cases of depression. Smartphone-based interventions are of particular relevance in low or middle-income countries, where traditional treatment options are not always or only partially available.

However, the impact of these apps varies from individual to individual. And even in the same person, the interventions have stronger or weaker effects depending on the situation. A research group from the Faculty of Psychology at the University of Basel, led by Professor Marion Tegethoff and Professor Gunther Meinlschmidt, investigated how the impact of smartphone-based interventions can be predicted more accurately. To this end, they used data from 324 smartphone-based interventions that aimed to regulate mood.

They employed a statistical technique from the field of machine learning, a specific form of the “random forest” method. This classification method can be used to process large volumes of data. The strength of this procedure is that it allows researchers to offer the decision trees relevant and theory-driven information, such as how tired or restless a subject is. The “learning forest” combines these characteristics with each other in multiple different ways and allows for predictions that reflect the complexity of real life more effectively than those of traditional prediction methods.

In the case described, approximately 6 out of 10 interventions resulted in no mood improvements. In the interventions predicted to be successful by machine learning, however, this number was only around 3 in 10. Hence, with this new technique, the number of unsuccessful uses could be cut by half. “We know that many patients quickly abandon digital interventions after they start using them. If an app is only effective in one out of every two or three uses, people soon loose motivation and see little point in using it any longer. Therefore, the new approach could potentially lead to patients using smartphone-based interventions for longer periods,” explains Professor Meinlschmidt, first author of the article. Further, the study delivers important information on how interventions can be better tailored to the individual, in terms of personalized treatment, in future. One could envisage to use the approach in many other fields where mobile apps are applied.

Subscribe to our newsletter

Related articles

Digital phenotyping helps to treat mental illness

Digital phenotyping helps to treat mental illness

Research shows that digital phenotyping can provide valuable information to mental health professionals about mental illness symptom severity and relapse.

Video games that improve kids’ social skills

Video games that improve kids’ social skills

Imagine racing through a virtual labyrinth against an alien and losing. Given the chance to rerun the race – which you don’t know is stacked against you – or quit, how many times would you try again?

AI algorithm to help manage diabetes

AI algorithm to help manage diabetes

Researchers, using artificial intelligence and automated monitoring, have designed a method to help people with type 1 diabetes better manage their glucose levels.

App monitors COVID-19 symptoms and mental health needs

App monitors COVID-19 symptoms and mental health needs

A new app that helps patients in self-isolation monitor for symptoms of COVID-19 and identify their mental health needs has been developed.

Nexkin: multiparametric monitoring shirt launched

Nexkin: multiparametric monitoring shirt launched

Chronolife announced the launch of Nexkin, a washable smart T-shirt that monitors six key physiological parameters to enable prevention, risk reduction, and remote monitoring.

mhealth: an app to screen for early signs of dementia

mhealth: an app to screen for early signs of dementia

Dementia screening could be as easy as using a smartphone app that listens to elderly people speak.

Digital games may beat mindfulness apps at relieving stress

Digital games may beat mindfulness apps at relieving stress

Digital games, typical of those on smartphones, may relieve stress more effectively than mindfulness apps, a new study shows.

‘Prescribed’ app offers hope to young people who self-harm

‘Prescribed’ app offers hope to young people who self-harm

New research suggests that the 'BlueIce' app developed at University of Bath could have a significant impact in reducing self-harm in young people.

About the usefulness of fertility apps

About the usefulness of fertility apps

Analysing fertility awareness apps, researchers have been able to track behavior patterns and accuracy in measuring menstrual health and ovulation.

Popular articles