Kristi Priestley & Rebecca Bind 

Mental health problems, such as depression and anxiety, are common in the perinatal period (the period from pregnancy to one year post-delivery) and can have profound impacts on the wellbeing of the mother and the development of her baby. In order to tackle this, good quality research data needs to be collected from the perinatal population, representing as many diverse experiences as possible.  However, pregnancy is a challenging life stage in which to conduct research, given the numerous demands on pregnant people’s time, such as attending antenatal healthcare appointments and preparing for the arrival of the baby.

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At the moment, the majority of studies on mental health in pregnancy rely heavily on asking pregnant people to answer questionnaires or undergo interviews, as well as often providing biological samples such as saliva or blood, which can all be mentally and physically invasive and burdensome for the participants. As a consequence, those most in need of support, for example those with pregnancy complications, may be least likely to participate in research as they have too many other demands on their time. For this reason, there is a clear need to develop and pilot novel strategies for research data collection in this population, which reduce participant burden while maintaining high data quality. Utilising developing technologies, such as smartphone sensors, there is potential to meet this need. 

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The aim of our project is to develop a model in which digital biomarkers can be used to predict mental health deteriorations in pregnancy, so that this can be used clinically to prioritise healthcare resources and ensure care and treatment decisions are as tailored and targeted as possible, for the benefit of both mother and baby. We will recruit participants from a cohort of 150 pregnant people at risk of developing depression, as part of the HappyMums programme, funded by the European Commission. 

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We will test the utility of digital markers, collected via smartphone sensor technology, to give us information about important behaviours related to mental health such as activity and sleep. Participants will be given access to the HappyMums mobile app (developed by Ab.Acus, Milan), where they will be asked to give permission for the passive collection of data from their smartphones, including GPS locations, light intensity sensors and accelerometery (how much the phone moves). These digital biomarkers will then be compared with traditional biomarkers to measure stress, such as cortisol, collected in saliva and blood. These measures will also be compared with standardised mental health questionnaires, which measure depressive and anxiety symptoms in the perinatal period. 

By identifying the data types which are most useful for identifying changes in a pregnant person’s mental health, we aim to improve the information available to clinicians who look after pregnant patients, so that they can make the best treatment decisions to improve outcomes for both the parent and the baby.

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