Wearable technologies for self-management of diabetes in pregnancy

Summary

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.

Objectives

• To investigate how wearable technology can be used to support self-management of diabetes in pregnancy
• To identify current technology that provides visual and stimulating data to pregnant women about self-management of their diabetes.
• To pilot test the feasibility of selected wearable technology compared to the current standard care protocol
• To apply computational methods to analyse data from nutrition, medication, glucose level and physical activity

Methods

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.

References

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.

Suggested Reading

https://www.diabetes.org.uk/resources-s3/2017-11/diabetes-key-stats-guidelines-april2014.pdf

https://www.reportlinker.com/market-report/Chronic-Disease/125884/Diabetes?utm_source=bingads_uk&utm_medium=cpc&utm_campaign=Healthcare&utm_adgroup=Diabetes_Statistics&msclkid=39a89161fee11fbfae51caccf38fe21f&utm_term=%2Bdiabetes%20%2Bstatistics&utm_content=Diabetes%20Statistics

https://www.diabetes.org.uk/In_Your_Area/N_Ireland

Essential criteria

• To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.

• Experience using research methods or other approaches relevant to the subject domain
• Sound understanding of subject area as evidenced by a comprehensive research proposal

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Practice-based research experience and/or dissemination
• Experience using research methods or other approaches relevant to the subject domain
• Sound understanding of subject area as evidenced by a comprehensive research proposal
• Publications record appropriate to career stage

Funding

The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £15,285 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies