Semantic analysis of natural language processing in a study of nurse mobility in the Northern Territory, Australia
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In lieu of diverse consequences in the demand and supply of health care professionals such as nurses and midwives in Australia and the world, a firm understanding of the characteristics of staff mobility and the factors influencing their retention could lead to achieving enhanced service delivery, greater job satisfaction, and the establishment of a more stable and robust workforce. The research reported in this paper attempts to shed light on qualitative aspects of mobility in health care professional staff in the Northern Territory of Australia. It builds upon an existing survey study of the quantitative factors that determine why nurses and midwives come to the Northern Territory, why some stay and why many leave, by analysing additional qualitative textual responses of participants using semantic network approaches to natural language processing. Our results illustrate the methodological and policy significance of semantic approaches to knowledge acquisition and representation, especially in complementing findings of traditional survey analysis techniques, and in analysing the broader social settings, effects and consequences of staff retention and mobility.
KeywordsSemantic analysis Semantic networks Knowledge representation Health care professionals Population mobility Nurses and midwives Northern Territory, Australia
We are most grateful to our co-workers in this research: Kate Golebiowska, Helen Walsh and Kerstin Zander at Charles Darwin University and Steven Guthridge, Shu Qin Li and Rosalyn Malyon from the Northern Territory Department of Health and Families. We are also deeply indebted to Greg Rickard of the Northern Territory Department of Health and Families and Dean Carson and Tony Barnes Charles Darwin University for their advice and guidance throughout this study.
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