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New Mental Health App To Assist Patients With Depression

New Mental Health App To Assist Patients With Depression

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The Dubai Health Authority (DHA) has highlighted features of an under-development app known as ‘Mindspire’ at the UAE innovates event at Expo.

Students from the American University of Sharjah designed the app, which won the first prize at DHA’s Health Hackathon in 2019. Since then, they have been working with the team at DHA to enhance the features of the app to help diagnose and treat patients with depression.

The app aims to help individuals suffering from depression or those who would like a preliminary screening of their state, and aids in alleviating their symptoms. The app focuses on anonymity and has minimal user intervention.

Dr Ayesha Al Basti, a family medicine consultant and vice-chairman of the Mental Health Committee at the DHA’s primary health care sector, said that the application has undergone several important updates since the concept was developed. Using voice notes to put in the daily inputs and voice tonality recognition are some of the latest updates.

She highlighted that DHA is keen to use smart technologies to further improve patient care as well as empower patients to take better care of themselves through the use of daily smart monitoring and technology.

How does the app work?

The non-intrusive analysis continuously collects and consolidates the data readily available on the user’s smartphone such as general phone usage, specific application usage (in terms of frequency, duration and active times of the day), typing speed, emoji usage and spellchecks. The text, calls, social media presence information is not monitored so as not to invade their privacy.

Next, the only user inputs required are the daily logging of their thoughts and feelings into the journal available on the app (Cognitive Behavior Therapy i.e. CBT recommended tool) through voice notes and they need to indicate their general mood by using a colour wheel (Ekman’s Atlas of Emotion) or with a series of Socratic questioning (CBT recommended method).

Machine learning algorithms are then used to detect the tone and associate a mood with journal entries as well as reveal repetitive thinking patterns. This information in conjunction with the background analysis can be used to find an individual’s biorhythms, identify periods of declining mental health, recognize times of generally more productive behaviour and provide personalised recommendations based on the severity of their condition.

Al Basti added that people with milder cases of depression will be encouraged to undertake therapy sessions and they will receive recommendations like light-hearted movies, comedy shows, uplifting music and workout routines.

Those on the higher spectrum will be directly guided to contact a professional and book an appointment with a specialist doctor.

She said the team is currently developing care pathways to ensure every patient gets the right treatment, support and care.

She added that mental health and well-being is of vital importance for every individual and such apps help provide much-needed support to patients suffering from depression while ensuring confidentiality and support.