Alkistis Skalkidou on a new app: Advanced warning of perinatal depression

Advanced warning of perinatal depression

Hello ALKISTIS SKALKIDOU, professor and researcher into perinatal depression at the Department of Women’s and Children’s Health. You and your research group have developed the app Mom2B for expectant and new mothers. What is the idea behind it?

“We want to try an entirely new method for collecting data for studies into how women feel about their pregnancy and giving birth. We gather data of various sorts, both reported by the mothers themselves and passive measurements of how they move around, how much they use their mobile phones, how their voices sound... All of this data is then analysed by artificial intelligence in order to predict who will develop symptoms of depression.” How common is perinatal depression?

“The figures vary from country to country and depending on how one measures but the figure is around 12% both during and after pregnancy. Depression is one of the most common complications by far. Although we often think of complications such as diabetes, pre-eclampsia and bleeding, these are extremely rare in comparison.

“It also has severe consequences given that the mother is in the midst of a period in which she needs to have intensive contact with the child. Suffering from depression at this critical time impacts on the child’s emotional development, the relationship with the partner and the woman herself.” Why is it important to be able to predict depression?

“If we can identify a risk group before they fall ill, we can invest our limited healthcare resources in this group preventively. This may involve simple things such as a few extra phone calls from the midwife and group therapy. These are measures that have proven effective for high-risk groups.” And what benefits do the expectant mothers gain from using the app?

“App users can record important data about their pregnancy and obtain information about the pregnancy and how the child is growing. They also get access to statistics about how much exercise they are getting each day, how much they are using their mobile phones, weight gain and self-estimated health. If their responses indicate depression, we become aware of it and get back to them.” – Annica Hulth