Written by Aislinn Bowler
When I started my PhD at Birkbeck, University of London eight months ago, one of the things I was excited about was the prospect of my placement and collaboration with digital health specialists Mindwave Ventures. The opportunity to work with the team came as I am on an iCASE industrial PhD studentship funded by the Medical Research Council.
My PhD is investigating motor development (the use of muscles to form small or big movements) in infants. I am interested in the typical variation in the achievement of significant motor milestones, such as grasping an object or walking.
I am also interested in the relationship non-typical motor development has with later psychiatric and neurodevelopmental disorders, such as autism spectrum disorder, ADHD, and schizophrenia.
Infant brain development in the first two years is rapid; they learn new skills very fast,
including key speech and movement motor skills, such as talking and walking. This rapid change also means this is a vulnerable period, and issues in this period may be representative of later problems.
However, there is also evidence that there can be substantial differences between typical infant development that are not a cause for concern. Therefore, it is crucial to understand which issues may signal a need for support and which are a normal part of development.
As part of this research project, I am developing an app, in collaboration with Mindwave, which allows parents to record information about their child’s motor development and milestones.
One of the main features of the build is to collect data over a long period to have an understanding of how infants motor development varies as they get older. Conversely, the other is collecting data over very short periods.
To do this, I will be using a technique called ecological momentary assessment (EMA). EMA involves the daily collection of a small amount of data, commonly with just one or two questions at regular intervals. This technique allows for the collection of data which can help understand patterns in behaviour or mood, which change daily or weekly. A benefit of using this method in an app is that notifications can be used to remind people to enter the information regularly.
The idea of collecting data at shorter intervals has been around for a long time in childhood
psychological research; in 1978, Lev Vygotsky proposed the “microgenetic method”, where
he suggested sampling at short time intervals to observe development in progress.
To combine the long-term and short-term methods, the app with use the technique of “burst
questionnaires”, where the majority of data is collected at longer intervals, but data for shorter intervals is collected at specific periods of interest, such as when the infant starts walking.
As I started on the process of developing the app by integrating the scientific background with digital techniques, I had a lot of ideas about how to develop a digital tool as part of my PhD project, and I was looking forward to acquiring new skills in app development.
I was, however, unaware of how important digital tools would become in the coming months. Now operating during a lockdown, the work has moved entirely online, which comes naturally to the digital company.
During a pandemic, collecting data has also moved entirely online, and developing digital tools has never been as important. As a consequence of this, I am even more passionate about developing an app to enable virtual data collection.
Find out more about the Mindwave team here.