Evidence and Practice
This article provides a rationale for selecting nominal group technique as a research method
This article discusses the significance of photo-elicitation in qualitative research
Why you should read this article: • To gain an understanding of how exploratory factor analysis can link with critical realism • To learn from a practical example of how the actual, empirical and real can be used in a mixed methods study • To be able to articulate and link the different aspects of ontology to link theory to practice Background Exploratory factor analysis (EFA) can link the levels of ontology in critical realism together as described in Summers (2020). Aim To demonstrate how components of the actual can be defined by linking potential factors in the empirical to the theorised generative mechanisms in the real. Discussion This article describes one part of a three-part sequential mixed-methods study that used EFA to describe how components of the actual were linked using factors in the empirical to the generative mechanisms in the real. The author theorised three generative mechanisms: the perceived impact of continuing professional development (CPD) on patient care, the motivations for undertaking CPD and the perceived barriers to CPD. He used EFA to test factors from the empirical against these generative mechanisms to identify linking components in the actual. Conclusion This article shows how components of the actual can be defined using EFA. These components are multifactorial and many factors in the empirical are influenced by different generative mechanisms. Implications for practice Being able to articulate and link the different aspects of ontology enables researchers to define theorised generative mechanisms and link theory to practice.
Understanding effects of measurement error will enable researchers to interpret study results
Why you should read this article: • Factorial design is underused in nursing research • Factorial design is a cost-effective way to examine different interventions simultaneously • Factorial design is the only design that enables researchers to study and understand how interventions interact Background Quantitative research designs are broadly classified as being either experimental or quasi-experimental. Factorial designs are a form of experimental design and enable researchers to examine the main effects of two or more independent variables simultaneously. They also enable researchers to detect interactions among variables. Aim To present the features of factorial designs. Discussion This article provides an overview of the factorial design in terms of its applications, design features and statistical analysis, as well as its advantages and disadvantages. Conclusion Factorial designs are highly efficient for simultaneously evaluating multiple interventions and present the opportunity to detect interactions amongst interventions. Such advantages have led researchers to advocate for the greater use of factorial designs in research when participants are scarce and difficult to recruit. Implications for practice A factorial design is a cost-effective way to determine the effects of combinations of interventions in clinical research, but it poses challenges that need to be addressed in determining appropriate sample size and statistical analysis.