Nursing professionalization is both ongoing and global, being significant not only for the nursing workforce but also for patients and healthcare systems. For this reason, it is important to have an in‐depth understanding of this process and the factors that could affect it. This literature review utilizes a welfare state approach to examine macrolevel structural determinants of nursing professionalization, addressing a previously identified gap in this literature, and synthesizes research on the relevance of studying nursing professionalization. The use of a (...) welfare state framework facilitates the understanding that the wider social, economic, and political system exercises significant power over the distribution of resources in a society, providing a glimpse into the complex politics of health and health care. The findings shed light on structural factors outside of nursing, such as country‐level education, health, labor market, and gender policies that could impact the process of professionalization and thus could be utilized to strengthen nursing through facilitating increased professionalization levels. Addressing gender inequalities and other structural determinants of nursing professionalization could contribute to achieving health equity and could benefit health systems through enhanced availability, skill‐level, and sustainability of nursing human resources, improved and efficient access to care, improved patient outcomes, and cost savings. (shrink)

The American Journal of Bioethics, Volume 12, Issue 7, Page 63-64, July 2012.

Multitrait-multimethod (MTMM) analysis is one of the most frequently employed methods to examine the validity of psychological measures. Confirmatory factor analysis (CFA) is a commonly used analytic tool for examining MTMM data through the specification of trait and method latent variables. Most contemporary CFA-MTMM models either do not allow estimating correlations between the trait and method factors or they are restricted to linear trait-method relationships. There is no theoretical reason why trait and method relationships should always be linear, and quadratic (...) relationships are frequently proposed in the social sciences. In this article, we present two approaches for examining quadratic relations between traits and methods through extended latent difference and latent means CFA-MTMM models (Pohl et al., 2008; Pohl and Steyer, 2010). An application of the new approaches to a multi-rater study of the nine inattention symptoms of attention-deficit/hyperactivity disorder in children (N = 752) and the results of a Monte Carlo study to test the applicability of the models under a variety of data conditions are described. (shrink)