The aim of this study was to explore and analyse midwives' rationales for their decision-making in everyday situations. Design A symbolic interactionist study underpinned by Blumer's Symbolic Interactionism Setting Midwifery practice areas in Central and Southern Scotland Methods Midwives were sampled purposively for age, experience and area of practice. Nineteen midwives took part from a variety of practice areas and three different regions in Scotland. Data collection comprised clinical observation of midwives making decisions in a variety of midwifery practice, use of validated interactive scenarios and in-depth interviews based on the observation field notes. Data were analysed using Blumer's principles of Symbolic Interactionism (Blumer, 1969), his concepts of 'self' and 'other' along with Ritchie and Spencer's (1994) five stage framework analysis. Findings The analysis of the data identified four rationales for midwives' decision-making. The first rationale was the individuality of the midwives, as related to Blumer's self 'I'. The second and third rationales were professional persona and compliance with policy and regulation, which were associated with Blumer's self 'me'. The final rationale was the individuality of women and babies, which is affiliated to Blumer's 'other'. Conclusions The individuality of the midwives and women was a major rationale for the decisions made. Individuality as a component of decision-making has not been well explored, and would benefit from further investigation within the research field of midwives' decision-making. Professional persona and compliance were also important rationales for the midwives' decisions. Midwifery and NHS culture influenced midwives in their actions, and these are issues that need to be examined more closely if midwives are to remain autonomous practitioners.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:636493 |
| Date | January 2014 |
| Creators | Poat, Angela Ellen |
| Publisher | Glasgow Caledonian University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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