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.
目的: 此次研究的目的是探讨福利国家与护理专业化指标之间的关系。 设计: 我们使用了时间序列以及横截面设计。此次分析横跨16年,并囊括22个国家:澳大利亚、奥地利、比利时、加拿大、丹麦、芬兰、法国、德国、希腊、爱尔兰、意大利、日本、荷兰、新西兰、挪威、葡萄牙、韩国、西班牙、瑞典、瑞士、英国和美国。这些国家可分类为五种福利国家制度:社会民主党、基督民主党、自由党、专制保守党和儒家。 方法: 我们运用了固定效应线性回归模型,并使用面板修正标准差方法进行Prais-Winsten方法进行回归,包括一阶自相关校正。我们采用了Amelia II多重填补策略来替代缺失的观察结果。数据收集于2017年3月到12月,随后更新于2018年8月到9月。 结果: 我们的研究结果强调了规范的护士以及护士毕业率和教育、卫生和家庭政策等国家福利措施之间的必然联系。此外,两个结果变量的平均值在福利国家制度之间存在差异,其中专制保守党的平均值最低。 结论: 要想进一步研究结构性政治和经济决定因素对护理专业化的影响,就需要进行更多国家层面和国际层面的对比研究。 影响: 我们调查了福利制度特性对护理专业化指标的影响,并且研究结果发现这样的特点会影响规范的护士以及护士毕业率。这些发现可用于通过健康的公共政策来加强护理和护理人员队伍,并且提高卫生人力资源预测工具的准确性。.
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.
© 2019 John Wiley & Sons Ltd.