Diabetes in pregnancy is a common medical disorder complicating pregnancy, affecting 1 in 250 women in Northern Ireland (CEMACH, 2007). It is associated with increased risk of pregnancy complications and adverse birth outcomes. Avoiding such complications could lead to potential savings and benefits, including: reduction in complications during pregnancy and labour and their related costs and improved care for the mother and baby (NICE 2015). NICE guideline indicates good glucose control through healthy diet, appropriate physical activity and blood glucose self-testing is vital.
Occularcentrism (Sinclair 2011, Sinclair 2013) is the key theory underpinning this project as we know that people are more likely to change their behaviour if they can ‘see’ the data and more inclined to adapt their behaviour if they receive individual feedback.
The widespread use of wearable technologies (such as activity trackers) has provided the opportunity for supporting self-management of diabetes in pregnancy. The aim of this project is to develop a cost-effective, blood glucose monitoring system that will enable pregnant women to manage their lifestyle and glucose levels more efficiently and with less anxiety. The selected technology will be tested and evaluated. Intelligent computational methods will be used to analyse women’s personal profile and the measurements of medication, nutrition, physical activity and blood glucose. This information can then be used to provide individually tailored recommendations of lifestyle including physical activity, medication and nutrition allowing users to set goals and self-monitor in line with current behaviour change theory.
A quasi-experimental mixed methods design will be used to design and test an intervention in a pilot feasibility study.
Strategic fit with current research
This proposal aligns with the research theme of healthy communities, a strategic priorities of Ulster University, CSRI, INHR and SESRI.
Anticipated research outcomes
It is anticipated that the project will improve public engagement in health, alter clinical guidelines for maternity care, and increase our understanding of how innovation in technology could improve health outcomes. High quality publications and conference papers will be produced for computer science, midwifery and exercise science journals.
Please note that applications should have a degree in one of the following subject areas: midwifery, sports science or computer science.
Confidential Enquiry into Maternal and Child Health. Diabetes in Pregnancy: Are we providing the best care? Findings of a National Enquiry: England, Wales and Northern Ireland. CEMACH: London; 2007.
NICE guideline, Diabetes in pregnancy: management from preconception to the postnatal period; August 2015.
Sinclair M (2011) Occularcentrism and the need to ‘see’ the evidence of impact. Evidence Based Midwifery 9 (2): 36
Sinclair M. (2013) Occularcentrism and epigenetics: visioning the hardware and software of the human gene. Evidence Based Midwifery 11(3): 75
Rollo, M. E., Aguiar, E. J., Williams, R. L., Wynne, K., Kriss, M., Callister, R., & Collins, C. E. (2016). eHealth technologies to support nutrition and physical activity behaviors in diabetes self-management. Diabetes, metabolic syndrome and obesity: targets and therapy, 9, 381.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 14,777 per annum for three years. EU applicants will only be eligible for the fees component of the studentship (no maintenance award is provided). For Non EU nationals the candidate must be "settled" in the UK.
As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day
Adrian Johnston - PhD in InformaticsWatch Video
Monday 29 October 2018
12 - 16 November 2018
When applying for this PhD opportunity please quote reference number: