In the process of conducting a research, levels of evidence are used to assigned to studies according to the quality, validity, and applicability of the study to patient care. Importantly, the study is also rated based on its strength based on the levels of evidence employed. Therefore, it can be argued that a good understanding of each level is essential for nursing practice and study.
In level 1, this is the evidence collected from essential randomized controlled trials and is based on a systematic review or meta-analysis. From level 1, the type of practice change could be a specific patient’s clinical assessment. In level 2, the evidence is based on a systematic analysis of quasi-experimental trials (Bloemen, Dallmeijer, de Groot, Mollema, & Van Wely, 2017). From level 2, the type of practice change could be to evaluate connection between the intervention and result. In level 3, the evidence is based on a non-randomized controlled trial. From level 3, a possible type of practice change could be quasi-experimented practices (Rogers & Revesz, 2020). In level 4, the evidence is provided based on cohort studies which allows for comparison. From level 4, a potential type of practice change could be examining unique conditions within the data collected.
In level 5, the evidence available is obtained from qualitative and descriptive research or meta-analysis of a particular cohort. A possible change could be to ask clinical questions to determine the efficiency of therapy. In level 6, evidence is obtained from one qualitative or descriptive research. A typical practice change could be analyzing and interpreting clinical results from this level. In level 7, the evidence obtained is derived from authorities’ opinions or expert reports. A type of practice change could occur in the healthcare administration. This evidence can be used to analyze how therapeutic services work in patients after an accident or heart attack.
Independent, Dependent and Extraneous Variables
Independent variables are those parameters that remain unchanged when subjected to different changing parameters. Independent variables are used when studying the effect different conditions have on dependent variables (Losh, 2017). For instance, clinical trials can be performed on the lab rats using an experimental drug, and in this case, the drug is the independent variable. In contrast, the rats’ behaviors’ outcomes are the dependent variable. Dependent variable is the parameter that changes when independent variables are manipulated. For instance, if a patient is administered a dose, and the severity of symptoms begin to appear, such manifestations constitute the dependent variable behind the outcome of a specific dose administration.
On the other hand, the extraneous variable is the parameter that has the power to positively or negatively affect both dependent and independent variables. Extraneous variables are pre-defined established conditions that will influence a study’s results (Flannelly, Flannelly & Jankowski, 2018). For instance, if students take an exam in a freezing room that affects the outcome and the students, the cold temperature will produce both desirable and undesirable outcomes that can lower the validity of the study.
From the above comparison, extraneous variables pose a risk to the validity of research, and therefore, researchers should adopt ways to circumvent this obstacle. Randomization is one of techniques used to circumvent the problems by using a large sample size. Secondly, the researcher can use a matching technique that groups and places different parameters equally distributed within the sample size. Matching reduces the effect of extraneous variables in a study by distributing the degree of its effects.
Bloemen, M., Dallmeijer, A., de Groot, J. Mollema, J., & Van Wely, L. (2017). Evidence for increasing physical activity in children with physical disabilities: a systematic review. Developmental Medicine & Child Neurology, 59(10), 1004-1010. Web.
Flannelly, K. J., Flannelly, L. T., & Jankowski, K. R. (2018). Threats to the internal validity of experimental and quasi-experimental research in healthcare. Journal of health care chaplaincy, 24(3), 107-130. Web.
Losh, S. C. (2017). Dependent and independent variables. The Wiley‐Blackwell Encyclopedia of Social Theory, 1-3. Web.
Rogers, J., & Révész, A. (2020). Experimental and quasi-experimental designs. The Routledge handbook of research methods in applied linguistics. New York: Routledge.