ABSTRACT
BACKGROUND: Nurse researchers are constantly seeking novel methods of maintaining philosophical congruence while advancing their knowledge of the human condition using paradigmatically diverse means. AIM: To provide an overview of the research philosophies underpinning the mixed methods grounded theory (MM-GT) methodology, illustrate its optimal use and introduce a quality-appraisal tool being developed with reference to extant literature. DISCUSSION: The utility of MM-GT has been effectively demonstrated in the nursing and health literature. Yet, there are examples of how it has been under-used and sub-optimally applied. This article includes a two-phase MM-GT study protocol guided by a pragmatic research philosophy and best practice recommendations that aims to explain neonatal nurses' professional quality of life. CONCLUSION: Optimal use of MM-GT's five essential components - purposive sampling, constant comparative methods with iterative coding and analysis, theoretical saturation, memoing and theory development - combine to produce high-quality, defensible research outputs and new nursing theory. IMPLICATIONS FOR PRACTICE: Research outputs, such as publication and presentation, expounding the multifactorial influences affecting neonatal nurses' professional quality of life will not only benefit the neonatal nursing community but also contribute to the corpus of nursing and midwifery research and enhance the health, well-being and retention of nurses and midwives more broadly.
Subject(s)
Nurses, Neonatal , Infant, Newborn , Humans , Grounded Theory , Quality of Life , Research Design , Nursing TheoryABSTRACT
BACKGROUND: Nurse researchers are increasingly using a wide variety of inferential statistical tests. However, novice researchers might find choosing tests for their studies difficult, as a result of this variety. AIM: To present structured decision-tables to help choose which statistical tests to use in comparative and correlation studies. DISCUSSION: The wide spectrum of statistical techniques the authors identified in nursing research helped them to construct overview tables that researchers could use as a simple tool to help choose appropriate statistical tests for their studies. CONCLUSION: The decision-tables provided in this paper are unique in that they are composed of commonly applied statistical techniques identified in nursing studies and structured to simplify the pathway to statistical test decision-making for a broad spectrum of study designs. IMPLICATIONS FOR PRACTICE: Novice nurse researchers can use the decision-tables presented in this paper as a starting point to explore with research colleagues or supervisors the appropriate choice of statistical techniques.
