The influence of welfare state factors on nursing professionalization and nursing human resources: A time-series cross-sectional analysis, 2000–2015

Virginia Gunn, Carles Muntaner, Edwin Ng, Michael Villeneuve, Montserrat Gea-Sanchez, Haejoo Chung

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Abstract

Aim: The aim of this study was to examine the relationship between welfare states and nursing professionalization indicators. Design: We used a time-series, cross-sectional design. The analysis covered 16 years and 22 countries: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, South Korea, Spain, Sweden, Switzerland, United Kingdom, and the United States, allocated to five welfare state regimes: Social Democratic, Christian Democratic, Liberal, Authoritarian Conservative, and Confucian. Methods: We used fixed-effects linear regression models and conducted Prais-Winsten regressions with panel-corrected standard errors, including a first-order autocorrelation correction. We applied the Amelia II multiple imputation strategy to replace missing observations. Data were collected from March–December 2017 and subsequently updated from August–September 2018. Results: Our findings highlight positive connections between the regulated nurse and nurse graduate ratios and welfare state measures of education, health, and family policy. In addition, both outcome variables had averages that differed among welfare state regimes, the lowest being in Authoritarian Conservative regimes. Conclusion: Additional country-level and international comparative research is needed to further study the impact of a wide range of structural political and economic determinants of nursing professionalization. Impact: We examined the effects of welfare state characteristics on nursing professionalization indicators and found support for the claim that such features affect both the regulated nurse and nurse graduate ratios. These findings could be used to strengthen nursing and the nursing workforce through healthy public policies and increase the accuracy of health human resources forecasting tools.

Original languageEnglish
JournalJournal of Advanced Nursing
DOIs
Publication statusPublished - 2019 Jan 1

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Keywords

  • gender equality policies
  • health human resources
  • nurses/midwives/nursing
  • nursing forecasting tools
  • nursing professionalization
  • patient and health system outcomes
  • politics of health
  • structural political and economic factors
  • time-series cross-sectional design
  • welfare state regimes and policy

ASJC Scopus subject areas

  • Nursing(all)

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