Nurse Turnover Public Health Research Methods

Public Health Research Methods, Theories, and Models

Theories are described as plausible bodies of knowledge that are used to explain effects and their possible causes. Essentially, theories are useful in understanding the world owing to the fact that they control, predict, and describe the world. On the other hand, models are graphical, pictorial, or related representations of viewpoints about the world or of reality (Fried, 2021). They are routinely derived from theories. Therefore, it is important to note that models act as a connection between the real world and theories. In a research article, the researcher’s underlying theory or model are usually found under theoretical frameworks.

The research article that I chose addresses the field of voluntary turnover of experienced nurses. In essence, the research was based on factors that contribute to the decisions that experienced nurses make to abandon their practice settings and explore other employment options (Hayward et al., 2016). In addition, the research explored turnover intentions related to environment and personal factors that influence such decisions. A qualitative, interpretative descriptive approach was deployed in the present study – and more specifically Thornes (2008) interpretive description design. The said model laid the groundwork for collecting data, exploring, and analyzing day-to-day nursing practice with regard to organizational, personal, and social constructs (Hayward et al., 2016). A qualitative came in handy in this case as it provided proper basis for the exploration of the opinions and feelings of participants. Thus, in this case, it allowed for greater insight about the perspectives of nurses who had abandoned their work settings. In the final analysis, it should also be noted that a qualitative descriptive analysis, in the words of the authors, “facilitates a better understanding of the processes and factors that may be useful to consider in planning organizational retention programs” (Hayward et al., 2016).