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Semantic analysis of natural language processing in a study of nurse mobility in the Northern Territory, Australia

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Abstract

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.

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Notes

  1. The remaining responses were excluded from the analysis because of either non-textual responses (e.g., symbols, or dashes), or single-word replies.

  2. Although the three semantic concept groups: husband, spouse and partner, are evaluated separately during the semantic network analysis and the use of natural language data, they are often used interchangeably in the context of the comments provided by the participants. For simplicity, we will assume them interdependent and treat them as such in the rest of the paper, although strictly speaking they are conditionally independent.

  3. Barabási 2003 uses the metaphor ‘the rich get richer’ to explain the functionality of the preferential attachment property in networks.

  4. From the participant responses it was not possible to identify the particular attributes of the people who provided retirement considerations in the reasons to come to NT. Nevertheless, it is worth stating that the cross-correlation between retirement considerations, age, and resident characteristics is relative high, especially at higher ages.

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Acknowledgments

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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Authors and Affiliations

  1. Center for Marine and Environmental Studies (CMES) and College of Science and Mathematics, University of the Virgin Islands, #2 John Brewers Bay, St. Thomas, VI, 00802, USA

    Kostas Alexandridis

  2. CSIRO Sustainable Ecosystems, Davies Laboratory, Townsville, QLD, Australia

    Kostas Alexandridis

  3. Institute for Advanced Studies, Charles Darwin University, Darwin, NT, Australia

    Kristal Coe

  4. School for Environmental Research, Institute for Advanced Studies, Charles Darwin University, Darwin, NT, Australia

    Stephen Garnett

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  1. Kostas Alexandridis
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  2. Kristal Coe
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Correspondence to Kostas Alexandridis.

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Alexandridis, K., Coe, K. & Garnett, S. Semantic analysis of natural language processing in a study of nurse mobility in the Northern Territory, Australia. J Pop Research 27, 15–42 (2010). https://doi.org/10.1007/s12546-010-9030-5

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