Quantitative Research to Inform Nursing Practice

Introduction

Quantitative research findings are of great utility in improving nursing practice. This research type serves as a source of reliable numerical and factual information, bringing multiple benefits to nursing. In contrast to qualitative, quantitative research produces measurable mathematical data relying on statistical methods of information collection. Thus, quantitative data is fundamental for assessing, developing, and selecting interventions, treatments, and medications. Additionally, it helps determine vulnerable populations, risk factors, and socioeconomic determinants of health. These applications of quantitative research ultimately lead to enhanced care quality, patient satisfaction, and experience. The extent to which the results of a study can be implemented into practice depends on its potential for generalization. The studies in the annotated bibliography were chosen based on their scholarly value, representativeness of the topic, and relevancy. The selected articles and other sources revolve around the contribution of quantitative research to evidence-based or holistic nursing practice or the quality of such research. Since the number of studies (or materials in general) dedicated purely to quantitative research and produced recently is rather limited, an array of sources closely related to the topic were also incorporated in the bibliography. The analysis of the sources will be based on their close reading. The accuracy and objectivity of the information presented, the texts’ strong and weak sides, and how in-depth the topic is covered are the principal criteria in terms of evaluating the sources. The presence and quality of supporting evidence will also be considered in the analysis.

Boswell and Cannon’s (1) Introduction to nursing research argues that the advancement of nursing comprehension is impossible without research, quality improvement, and evidence-based practice (EBP). The authors are convinced that frontline nurses bear the responsibility of transforming the management of healthcare. To do so, they need to locate reliable evidence and translate it into policies and procedures. The book aims at improving nurses’ research literacy which applies to a variety of sources, such as research projects, quality improvement reports, published reports, and others. Borbasi, Jackson, and East (2) argue that publishing a paper is not the end but rather the first step toward evidence-based nursing practice because the findings now need to be incorporated into the day-to-day workflow. According to Borbasi, Jackson, and East (2), curiosity is one of the most valuable nursing qualities. Nurses do not have to necessarily do the research themselves, but understanding it is still a must, which is why the book covers research methodologies in detail and equips readers with vocabulary that helps to “navigate the maze of research.” Another group of researchers (3) pursue the same goals with their book titled Research in nursing, midwifery, and allied health. The book guides the reader by starting with putting forward a research question and ending with implementing the practical implications of the findings. All the aforementioned sources have a serious advantage in common, which are the credibility of the authors, their advanced educational background, and their scientific experience. However, the three books lack detail when it comes to the statistical underpinnings of research.

Fain (4) covers the fundamentals of nursing research and teaches the reader all the necessary steps from start to end. What makes this source stand out among other similar books is its attention to the official statements and guidelines of healthcare institutions, such as the American Association of Colleges of Nurses (AACN). Besides, Fain (4) emphasizes the importance of scientific integrity, especially the ethics of human subject research. The source’s major strength is the credibility of the author, who, however, does not offer concrete advice regarding EBP implementation in the workplace. Sharma’s (5) includes the same foundations of nursing research as the previous four sources; however, the book goes deeper on topics related to research approaches, sampling, and data analysis. The second section of the book is dedicated entirely to healthcare statistics, which starts with the basic concepts, such as normal probability and parametric and non-parametric tests. A major strength lies in Sharma’s description of their application in the field of healthcare. Yet, it seems as if more attention could be given to the mathematical underpinnings of statistical tests. The previous sources concur that nursing research should take into account nursing trends, which is the focus of the study conducted by another group of authors (6). They found that holistic nursing research was revolving mainly around such themes as caring, energy therapies, knowledge and attitudes, and spirituality; only 56% of studies from the sample could be considered quantitative. The article provides valuable implications for improving study designs, but its findings may not be exactly inferrable due to the small sample size.

American Association of Colleges of Nurses (7) encourages nurses to achieve higher levels of education and sets standards for what nursing expertise at a master’s level should entail. The essentials that are most relevant to the present bibliography are IV “Translating and Integrating Scholarship into Practice” and V “Informatics and Healthcare Technologies.” By them, nurses should be equipped to integrate theory, evidence, clinical judgment, and research to improve quality and use bio-health statistics and informatics to analyze input and output data. The strength of the source lies in its modern outlook on the nursing profession that now encompasses diverse responsibilities. Yet, at times the document lacks concrete guidelines and provides general descriptions. Bloomfield and Fisher (8) not only explain what quantitative research design and explain its different types: descriptive, correlational, causal-comparative/quasi-experimental, and experimental. What is remarkable about the source is how Bloomfield and Fisher (8) tie statistical concepts, such as mean, standard deviation, parametric tests, and regression, to specific types of research. Esperón (9) seeks to raise awareness about the limitations of quantitative research. In particular, she says that the positivist paradigm has prevailed in nursing science for quite a long time. However, a better understanding of nursing care phenomena may come from the use of the mixed approach that draws on both quantitative and qualitative methodologies. The article’s undisputable strong point is its special attention to the subfields of medicine where statistics find the most use – epidemiology, healthcare economics, and intervention studies (quality improvement). However, it does not quite give rise to practical implications regarding data interpretability.

Visentin and Hunt (10) argue that in the field of mental healthcare (MH) there is a growing demand for more robust research that employs quantitative methods. Even though the quality of MH research has grown in the past few decades, there is a longstanding problem with statistical output interpretation. According to Visentin and Hunt (10), it is not uncommon to see data included in appendices or presented in tables without little to no explanation. The authors (10) address the most common problems of data interpretability and offer solutions that, however, lack practical examples. In their article, McKechnie and Fisher (12) seek to address the problem of choosing the correct statistical methods for nursing research. Firstly, statistical methods need to fit the aim and objective of the study; secondly, they should account for the type and distribution of the data used. Lastly, the nature of the observations (paired/unpaired) plays a role in designing a study. The source deserves attention because the authors constructively describe the selection process; yet, it would still benefit from illustrations. One of the recurring issues of quantitative nursing research is under-representative sampling. Hannigan (11) advocates for better public-patient involvement that could improve research participation and attract demographics that are currently under-researched. The article’s strong point lies in its acknowledgment of lay knowledge in statistical analysis that should not be devalued because it helps the broader audience become more scientifically literate. Yet, Hannigan (11) did not explain how to overcome bias in patient sampling.

Quantitative nursing research has general mathematical and statistical foundations, but its application ranges depending on the subfield. Son and Seo (13) investigated nursing research trends regarding heart failure patients in South Korea. It appears that the most popular type of quantitative study on the topic is observational. Among the most commonly occurring limitations, Son and Seo (13) mention the omission of ejection fraction and New York Heart Association functional classification class (NYHA class) in the inclusion criteria. Apart from that, it is not completely clear how one can mathematically operationalize quality of life. The article provides valuable implications for improving study designs, but its findings may not be exactly inferrable due to the small sample size.

Another area of application for quantitative methodologies is bedside shift reports which have been of interest to nurse managers (NMs) (14). Bedside shift reports hold out a promise to improve nursing surveillance and reduce adverse events. The study has found that traditional methods may be replaced by BSRs, which is valuable knowledge; however, the latter requires better documentation and frameworks. A group of researchers (15) demonstrate the use of the quantitative methodology in their study of attitudes toward suicidal behaviors and associated factors among nursing professionals. The study had a cross-sectional design and employed linear regression as the main method for finding correlations between independent and dependent variables. The study’s strength lies in its novelty; yet, its validity may be compromised by the modest sample size.

Most Relevant Articles

  • 1. Boswell C, Cannon S. Introduction to nursing research. Jones & Bartlett Learning; 2018.
  • 5. Sharma S. Nursing research and statistics. Elsevier India; 2018.
  • 8. Bloomfield J, Fisher M. Quantitative research design. Journal of the Australasian Rehabilitation Nurses Association. 2019;22(2): 27-30.
  • 10. Visentin D, Hunt G. What do the stats mean? Improving reporting of quantitative nursing research. International Journal of Mental Health Nursing. 2017;26(4): 311-313.
  • 13. Son YJ, Seo EJ. Research trends in quantitative nursing studies and quality assessment of intervention studies in patients with heart failure in South Korea. Journal of Korean Biological Nursing Science. 2017;19(4):227-40.

These sources show the most relevance to the discussed topics because they cover the wide range of problems existing in nursing research. Boswell and Cannon (1) put quantitative methods in the broader context of nursing research. The source overviews the most important steps in conducting a study and shows the role assigned to quantitative methods. Sharma (5) and Bloomfield and Fisher (8) delve into more detail regarding computational approaches and tie them to specific types of study. The article by Visentin and Hunt (10) is included because it warns nursing researchers about persisting issues, such as data interpretability, and informs on the measures that can be taken to improve the quality of quantitative nursing papers. Lastly, the paper by Son and Seo (13) illustrates the importance of being on top of nursing research trends.

Conclusion

The positivist paradigm that relies on quantitative research has now become a standard in healthcare. However, applying statistical methods without knowing the foundations of research may not be sufficient. For this reason, quite a large body of literature put quantitative methods of nursing research in a larger context that includes developing research questions, setting goals, and choosing the correct design. Even though nursing papers have improved in terms of quality, there are still recurring problems with data interpretability. An even graver problem is the translation of research and integration into policies and procedures in clinical settings.