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Aboriginal and Torres Strait Islander Subjects in a Graduate Diploma of Midwifery: A pilot study.

Jessica BilesBrett BilesRoainne WestVicki SaundersJessica Armaou
Published in: Contemporary nurse (2021)
Background: Australian Nursing and Midwifery Accreditation Council prescribes midwifery accreditation standards that support students' development in Aboriginal and Torres Strait Islander Health and cultural safety to be deemed practice ready. However, the impact of training programmes are not widely explored.Aim: This study aimed to assess the impact of a mandatory 8-week online subject focussed on the development of culturally safe practices among midwifery students.Methods: The Ganngaleh nga Yagaleh cultural safety assessment tool was used to collect online quantitative data from post graduate midwifery students at the commencement and completion of an online subject.Results: Through a purposive sample (n = 10) participant perceptions of culturally safe practices remained relatively unchanged, except for three items of the Ganngaleh nga Yagaleh cultural safety assessment tool.Discussion: Findings demonstrate that when post graduate midwifery students are exposed to Aboriginal and Torres Strait Islander perspectives of Australia's colonial history it impacts their sense of optimism, personal values and beliefs about the healthcare they will provide to Aboriginal and Torres Strait Islander peoples. However, midwifery students who self-identified as Aboriginal and/or Torres Strait Islander people, reported a decline in optimism when imagining a healthcare system free of racism.Conclusion: The subject did not impact on cultural safety scores. This may be due to prior learning of student midwives. Educators should consider building on prior knowledge in post graduate midwifery to ensure the content is contextualised to midwifery.
Keyphrases
  • healthcare
  • medical education
  • high school
  • primary care
  • quality improvement
  • public health
  • health information
  • randomized controlled trial
  • clinical trial
  • mass spectrometry
  • deep learning
  • high resolution
  • climate change