Evidence and Practice

Clinical

When and how to use factorial design in nursing research

When and how to use factorial design in nursing research

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.

Use of modified Delphi introduces the risk of chronological bias during clinical research interventions

Use of modified Delphi and risk of chronological bias in clinical research interventions

Raising awareness of the potential to introduce a chronological bias as a confounder

Complementing the P-value from null-hypothesis significance testing with a Bayes factor from null-hypothesis Bayesian testing

Complementing the P-value from null-hypothesis significance testing with a Bayes factor...

Reporting a Bayes factor to complement a P-value adds interpretive value to research

‘Statistical significance’ in research: wider strategies to meaningfully interpret findings

‘Statistical significance’ in research: wider strategies to interpret findings

Researchers need to focus on reporting meaningful research findings

Self-care while undertaking qualitative nursing research

Self-care while undertaking qualitative nursing research

There should be more awareness about potential risks of such research into sensitive topics

Qualitative research interviewing: reflections on power, silence and assumptions

The challenges a novice researcher faced when collecting data using narrative interviews

Practice question

My research study improves patient care – how can I share it?

Tips and rules for successfully sharing your research at a conference or professional meeting