Technological Advances in Psychiatry – From Couch to Cloud by Arshya Vahabzadeh
Dr Arshya Vahabzadeh, Harvard-trained physician-technologist and innovation officer of the Massachusetts General Psychiatry Academy talks about key technological advances in psychiatry and their potential to change the way we prevent, diagnose and treat mental health disorders.
A DIGITAL SIGNATURE FOR MENTAL HEALTH?
- Is there a digital signature for your mental health? –
Can we get a digital signature for the green light when everyone is doing OK? Can we notice what amber is through this digital signature by collecting data?’
- Will digital signatures redefine categorical diagnoses?
APPS FOR MENTAL HEALTH
What’s important about apps is that if your patient comes up to you and says “I’m using an app to do X or Y or help with anxiety or OCD or to help with my depression” you need to recognise that they are variable in quality, usability and can be potentially harmful.
It’s important to know -Who are the people behind the apps?
A CLOSED LOOP APPROACH
- Collect all the sensor rich data- e.g. voice, affect, sleep, phone use, motor interaction etc.
You can actually use information from search engines… people are searching for symptoms
2. Analyse data
3. Intervene: CBT, DBT, mindfulness, crisis plans, medications support
4. Support: clinical team, research team, social support, caregiver etc.
A study using an app for suicide non-suicidal and suicidal self injury as an intervention tool showeed the following results
- Self-cutting episodes decreased by 32%-40%
- Suicide plans decreased by 21%-59%
- Suicidal behaviours decreased by 33%-77%
- Suicidal ideation was not reduced
There is a long way to go, but people are thinking can you have an app that makes someone less suicidal and when would you deploy that app?
Previously on the hub we also covered Dr Vahabzadeh’s paper on digital prevention of suicide.
A MOTOR SIGNATURE FOR AUTISM?
A study looking to identify a motor signature for autism using tablets with touch sensitive screen found the following according to the authors –
In this study, we employed smart tablet computers with touch-sensitive screens and embedded inertial movement sensors to record the movement kinematics and gesture forces made by 37 children 3–6 years old with autism and 45 age- and gender-matched children developing typically.
Machine learning analysis of the children’s motor patterns identified autism with up to 93% accuracy. Analysis revealed these patterns consisted of greater forces at contact and with a different distribution of forces within a gesture, and gesture kinematics were faster and larger, with more distal use of space.
These data support the notion disruption to movement is core feature of autism, and demonstrate autism can be computationally assessed by fun, smart device gameplay.
APP WITH A PILL?
SENSOR WITH THE PILL
We covered digital medicine systems in a previous post on the hub where the researchers investigated the ability of the ingestible sensor to detect either aripiprazole (an atypical antipsychotic) or a placebo across two studies.
Previous videos of Dr Vahabzadeh include
- Technology and The Converging Paths of Mental Health
- The digital conceptualisation of depression
- Frontiers in psychiatry – an introduction of digital and neuroscientific approaches