In previous columns, I touched on the differences and similarities between quality improvement and evidence-based practice (Roe-Prior, 2022a, 2022b) and the need to critically evaluate the existing research literature before implementing any practice change or embarking on a quality improvement project. Also mentioned was the weight one should ascribe to the types of literature-less weight to narrative and scoping reviews, more to well-designed systematic reviews, meta-analyses, and original research studies.
In this column, I would like to briefly describe the major categories of nursing research and describe their differences. Some may question the need for more research. Who among us has the time to read and absorb research that has already been published? So why do more research, and specifically, what is the purpose of research for the nursing professional development (NPD) practitioner? One purpose is to produce new nursing knowledge, which may generate theory and improve practice, hence leading to better prepared nurses, more efficient patient care delivery, and cost containment. Another may be to eliminate nursing actions that do not achieve desired outcomes (Polit et al., 2001, p. 5).
Other research findings may affect NPD practitioners' ability to influence administrators and policy makers to implement management and legislative changes that will improve practice. Remember, one needs ammunition to lob at what may be ingrained but unsupported methods and systems. Finally, the legitimacy of a nursing specialty depends on a body of research and theory on which to validate their essentialness to the profession and the healthcare system.
So, what exactly is nursing research? Broadly, it is the systematic application of scientific inquiry to the study of phenomena of interest to the nursing profession. Said in another way, nursing research is the systematic inquiry into a subject that uses various approaches to answer questions and solve problems, with the goal of discovering new knowledge. Scientific inquiry is defined as the systematic, planned approach to data collection, analysis, and evaluation that can be replicated by other researchers (Polit & Beck, 2017, pp. 3, 743).
As I mentioned, there are two major categories of research. These are quantitative and qualitative research designs. Within these two categories are methodological subcategories that are predicated on the type of question to be answered. Some questions lend themselves to numerical answers; some do not. Qualitative research design aims to gain perspective on human experiences based on the premise that reality is subjective. In this type of research, the investigator attempts to identify and bracket any of their own biases or preconceived notions to avoid influencing the participants or the study results. Generally, only a cursory literature review is performed before the study initiation, there is no hypothesis, the resultant data are in narrative form, and the results are themes. Statistics have little role in qualitative data analysis.
Qualitative research is useful to understand little or incompletely known phenomenon or to gain a new perspective. The findings from qualitative research may serve to guide professional practice and/or serve as a basis for instrument development and theory building. When, for example, an NPD practitioner wishes to understand the experience of staff caring for critically ill COVID-19 patients, they may elect to measure how many times the staff break down in tears, or how many contract COVID-19 themselves. These quantitative approaches would not provide the richness of data gained by using open-ended questions to understand the actual meaning of caring for these patients. As Albert Einstein so sagely said, "Everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted" (Clarkson, 2013).
Quantitative designs collect numerical data through measurements and assessments that are then statistically analyzed based on a predetermined plan. Variables may or may not be manipulated, depending on the research question to be answered. Regardless, a well-designed study should conceptually and operationally define the variables to be measured and attempt to control extraneous variables. As we know, when dealing with human beings, control is often quite difficult to impossible; yet, if too highly controlled, a study's findings may not be generalizable.
A quantitative study follows the scientific method, which posits that reality is objective. Before designing a quantitative study, a thorough review of the literature should be performed. Based on this review, the need for the study should be established. A gap in knowledge; inconsistent or contradictory prior study findings; and an intervention, therapy, or group (such as nurses caring for COVID-19 patients) that has not been studied are all good reasons for conducting a study. Any of these aforementioned reasons form the basis for the study's problem statement.
Once the justification for performing the study has been established, the researcher should craft a succinct purpose statement, which should include the sample; setting; dependent and, if applicable, independent variable(s); and whether there is a comparator group. For example, if my review of the literature revealed that it is not known if any characteristics of intensive care unit (ICU) nurses predicted their frequency of sick day absences (problem), I might write my purpose as follows: The purpose of this study is to determine if any nurse characteristics predict sick time use for ICU registered nurses employed in an urban teaching hospital. Sick time use is defined as unscheduled work absences attributed to illness. The characteristics of interest include age in years, gender, years of ICU experience, type of unit (medical or surgical), marital status (single, married, separated, or divorced), and number of children under 12 years of age.
I must have some rationale from the literature and/or my experience to have selected these variables, their conception, and operationalization. A reader of my purpose statement would be able to identify the sample, setting, dependent variable, and independent variables. From the purpose statement, the study design, a correlational study and its statistical analysis, a regression equation can be inferred. One bit of advice I have learned to provide my students is to write that clear purpose statement and refer back to it often for clarity and consistency when writing the research proposal and then again when discussing the study results.
Although the format for a qualitative research study may vary by the type of study design, quantitative research studies follow a fairly typical template, which I hope to explore in greater depth in subsequent journal issues. Either type of research requires institutional review board (IRB) review. Depending on the study proposed, the IRB may provide an exempt, expedited, or full board review. If you are unsure whether your project is quality improvement or research, err on the side of caution by submitting to the IRB. No matter qualitative or quantitative when a study is poorly designed, the research is a waste of the time for the participants, researchers, and reviewers. Few of us have a surfeit of time.
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