Part-time PhD Student
Research title: Explicit observation and recording of physiological signs other than cervical dilatation can compare with vaginal examination as a means of measuring progress in normal labour.
Supervisors: Professor Neil Small and Dr Melanie Cooper.
I am a registered Nurse and Midwife with a wealth of clinical experience. For the last 10 years I have worked as a lecturer in Midwifery and Women’s Reproductive Health. My special interests are; intrapartum care, active birth and the use of art in health professional education.
I commenced my PhD study, Measuring Progress in labour without the use of Vaginal Examination, in April 2013.
Exploring the question, Can midwives verbalisation of events in labour reveal tacit cues to reliably indicate progress and inform the design of a labour observation tool? This study aims to;
- Unveil the tacit knowledge that midwives use to assess labour progress and provide safe midwifery practice
- Develop a valid and reliable non- invasive labour observation tool, which can be piloted in practice
Midwives care for women in normal labour. Whilst it is known that midwives use a range of cues to assess labour progress, these have yet to be validated. Labour progress is currently measured by vaginal examination (VE) to determine cervical dilation; findings are then plotted against time on a labour chart. VE has been critically examined through recent Cochrane Review, concerns regarding its invasive nature, infection risk, accuracy and reliability, have been raised. Insufficient evidence was found to support VE; prompting recommendations for the development of observational based labour assessment tools.
Taking a qualitative, action research approach this PhD seeks to unveil the contemporary midwife’s direct experience and understanding of labour progress. Midwives verbalisation of events in labour will be recorded, using an unobtrusive microphone. Recordings will then be analysed and compared against standard labour measures, in an attempt to reveal observational signs which may indicate labour progress. The resulting data will inform the design of a labour observation tool which can be piloted across diverse practice settings.