All research studies are conducted to reach particular results associated with the issue selected by the professionals. For the readers to be able to understand them, it is critical to be aware of several rules, such as understanding the very purpose of the work, its variables, analysis, and measurement tools. Many people consider that the most important thing is to be aware of the very research purpose because it affects all procedures and interpenetrations. Nevertheless, the value of variables should not be overlooked because their measurement determines the results of the study. What is more critical, many professionals do not identify their variables directly in the study, which causes complications for the readers and prevents them from a decent understanding of research and its findings. Variables can represent different categories measured by professionals (for instance, the presence of disease). There are many types of variables, but the most common are dependent and independent ones. An independent variable cannot be affected and remains stable (patient’s age) while a dependent one can be altered by some factors (test score) (Ben-Eliyahu, 2016).
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There are two major types of significance in those research studies that are associated with the sphere of healthcare. Clinical significance reveals whether results obtained due to a study turn out to be important for real practice and can benefit the field. For instance, it is possible to consider whether some treatment option is clinically significant, discussing the way it affects patients. The influence of the treatment on clients’ daily life and health condition is to be in focus. While an option can be clinically significant due to the noticeable improvement it provides, statistical significance deals with particular numbers. The difference between intervention and its absence with p<0.05 can be considered significant because it is not likely to be observed by chance (Denisse, 2017). Even though clinical significance seems to be more important than statistical one, both of them should be considered in practice. If statistical significance is absent, positive results may be observed by chance and can hardly be applied to a larger population. If the clinical significance is absent, there is no necessity to implement a change.
Research studies conducted for healthcare purposes often include discussions of both descriptive and inferential statistics. Descriptive statistics are used by researchers to discuss the characteristics of the sampled population, allowing the readers to enhance their understanding of the study. It analyzes data and presents it in a meaningful way, using different figures to describe a particular situation. Thus, descriptive statistics explain the information that is already known. Inferential statistics, in its turn, allows considering if the results of the study can be used for other populations. It compares the sample with other groups of people to reveal the probability of the occurrence of the same event in them (Surbhi, 2016). Thus, inferential statistics develop new conclusions, extending beyond the already known information.
The clinical issue under discussion deals with the prevention of pressure ulcers. It is possible to consider the association between nursing care missed and the risk of this problem in immobile patients. In this way, descriptive statistics may reveal factors that increase the possibility to miss care, while inferential statistics can focus on the comparison of factors that influence nurses from different units or the relation between missed and care identified in the patient assessment (Valles, Monsivais, Guzman, & Arreola, 2016).
Ben-Eliyahu, A. (2016). What’s the difference between dependent and independent variables? Web.
Denisse, C. (2017). Statistical significance vs. clinical significance. Web.
Surbhi, S. (2016). Difference between descriptive and inferential statistics. Web.
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Valles, J., Monsivais, M., Guzman, M., & Arreola, L. (2016). Nursing care missed in patients at risk of or having pressure ulcers. Revista Latino-Americana De Enfermagem, 24, e2817.