Is there a Disparity in Job-Related Burnout between Trauma Nurses and Medical-Surgical Nurses?
Restatement of the Research Question
The study investigates the problem of burnout amongst nurses to design an effective intervention plan. Previous research shows that nursing is the most affected area because of the level of stress and compassion fatigue experienced in healthcare settings (van Mol, Kompanje, Benoit, Bakker, & Nijkamp, 2015). Nurses play an important role in caring for patients, and hence, spend a considerable time of their day and night in the workplace, putting them at the risk of stress and burnout. While it is evident that nurses are affected by burnout, it is critical to establish whether nurses in some nursing settings are at a higher risk than others. However, available evidence is limited on the disparity that exists between the burnout levels in different nursing settings. The research will investigate the potential disparity in the level of burnout amongst nurses in different nursing settings, trauma and medical-surgical, to implement effective solutions. Hence, to achieve the aim, the researcher will answer the study question, which states that “is there a disparity in the rate of burnout between trauma nurses and medical-surgical nurses?”
Restatement of the Hypotheses
The researcher tries to reject, disprove, or nullify the null hypothesis (H0) in the scientific experiment. The null hypothesis is the opposite of the research hypothesis, which the researcher tests in collecting data (Ingham-Broomfield, 2014). The null hypothesis, in the current study, is that the nursing setting does not have any impact on the level of burnout that nurses experience. On the other hand, the research hypothesis that the researcher will test using the collected data is the specific and testable statement regarding the potential outcome. The researcher hypothesizes that nursing context affects the rate of burnout, while nurses in the trauma unit are at a higher risk of the problem due to work-related and compassion stress compared with nurses in medical-surgical setting. The hypothesis is a one-tailed directional approach, predicting the type of influence on the dependent variable by the independent variable (Ingham-Broomfield, 2014). It is possible for the researcher to predict the nurse setting that is likely to have a higher level of burnout due to the nature of work.
Independent and Dependent Variables
Variables are critical in a study because they direct the data collection process. The researcher collects data to test and measure variables. According to Thompson, Amatea, and Thompson (2014), the variables are either dependent or independent. The independent variable can be controlled or changed in the course of the study in testing how it affects the dependent variable. Conversely, the dependent variable is what the researcher tests or measures in an empirical research. The dependent variable depends on the independent variable in the scientific experiment. The researcher observes and records the effect on the dependent variable with changes in the independent variable. In the current study, the independent variable is the nursing setting, either trauma nurses or medical-surgical nurses, while the dependent variable in the study is burnout.
Identifying the sample for the study is a critical step because a researcher cannot collect data from the entire population. Academics can select one of the various sampling methods to obtain a number of units to collect the data. The current study will use a purposive sampling method. The technique involves flexibility in selecting the sample of participants to complete the survey. Purposive sampling is usually convenient and straightforward because the researcher identifies subjects through particular characteristics (Ingham-Broomfield, 2014). For example, in the current study, the researcher will decide on those nurses who will participate in the study. However, purposive sampling affects generalizability because of failure to use random sampling of participants (Ingham-Broomfield, 2014). The results from a researcher-selected sample might not apply to other settings.
The sample for the current study is selected from nurses in my working place, a hospital. The sample includes all the nurses working in the trauma and medical-surgical units of the hospital. The hospital has three nurses working in each of the two units. Therefore, data is collected from a sample of six nurses. The recruitment process is critical in ensuring that the sampled participants are willing to participate in the study. The researcher will approach the colleagues and inquire about their willingness to participate in the research and the amount of personal and professional information they can provide. The sample represents nurses working in the two settings involved in the study. The inclusion criterion includes all the nurses working in the two settings in the hospital and having worked there for more than 3 years. All nurses working in other locations in the hospital will be excluded from participating in the research.
The researcher will provide as much information about the study as possible for the nurses to make an informed decision to participate in the study. A consent form will available for the nurses to sign before commencing with the data collection phase. The informed consent will indicate that they are willingly participating in the study. The researcher will also assure them that whatever information they give will remain confidential, and hence, used for the study.
Data Analysis Plan
The data for the analysis is collected through a survey created in Google forms, which is given to participants and collected immediately to input into the statistical program for analysis. The survey was provided to the participants in hard copy to be completed and returned immediately. I printed the survey and gave it to the participants to respond in a few minutes of their time while still in the workplace. A paper-based survey is usually easy to record information and does not take much time to complete. In addition, it is also possible to print out many copies of the study for the six participants. The data received from the survey monkey will be analyzed through data analysis software (SPSS) while the results will be used for decision-making.
The researcher should prepare the data for the analysis. Some important steps are necessary when organizing the collected data for analysis. One of the steps is to consider the variables and the data to include in the review. The process involves a wide range of variables and eliminating data that lacks value in the research. I will also determine whether to use derived variables. In some cases, the derived variables are more useful than the raw data. Another step is exploring the quality of the data, its state, and limitations. The model’s prediction accuracy will depend on the selected variables for the analysis. Some crucial attributes to test may include the completeness of data, possible outliers, the need to clean data, and possible ways of filling in or eliminating missing values (Little & Rubin, 2014). Once the process is complete, I will feed the data into the analysis program (SPSS).
The researcher uses a statistical test depending on the nature of the study. The tests provide the methods for making quantitative decisions regarding the sample of the population being studied. Statistical analyses measure the research hypothesis. The rationale for the statistical test is to determine whether the researcher has adequate evidence to reject the hypothesis. The current study will use a correlational statistical test. The reason for using this type of test is because the researcher is looking at the association between variables, the level of burnout among nurses, and the nursing setting (Ingham-Broomfield, 2014). The statistical test is significant when the researcher is looking at the correlation between normally distributed interval variables. In this case, the researcher should establish whether the relationship occurs.
After determining the statistical test to use during the data analysis phase, the variables will be ready to input into the data analysis program. The researcher will use the SPSS in examining the data and providing findings. The program will analyze the input and make predictions about the validity of the hypothesis. The process begins with loading the excel file with all the data from the survey, including demographic data to test the relationship between the variables. A tabular form will be used in loading the data on the excel program. The next step will involve importing the raw data into SPSS through the created excel file. Commands are given depending on the expected results. The program provides the results in a format that is accurate and easy to understand, using graphs and charts.