Nurse Burnout in Evidence-Based Research


Evidence-based practice (EBP) implies the rational application of current evidence related to clinical expertise and core patient needs to direct decisions in health care. To ensure the efficiency of EBP and its best outcomes, the implemented evidence should be recent, credible, and of high quality. It may not always be enough only to use the information provided by researchers in previous literature. To substantiate various improvement initiatives, empirical data is needed.

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Validity and the overall quality of study results largely depend on methods that scholars and clinical practitioners use to reach them. For this reason, in the research process, significant attention should be given to the development of study design and the selection of methods. Based on this, in the given paper, we will review the methodology which will be applied during the realization of a research project aimed to evaluate the impacts of nurse scheduling on job and patient satisfaction. We will describe the selected analysis tools, sampling techniques, and ethical standards and justify the choice. The given methodology review will help to minimize risks of data biasing due to the misunderstanding of study methods and instruments.


In this project, a quantitative research design will be employed. Quantitative methods include numerical calculations, estimations, and statistics. The given framework suggests that one can reveal an objective truth about a particular process of interest, and this truth can be measured and scientifically explained by using various quantitative methods that allow researchers to detect cause-and-effect relationships between the studied variables and generalize the findings (Creswell, 2014). Quantitative research is deductive. It means that, initially, the researcher should formulate a scientific hypothesis and then try to verify it empirically by collecting and analyzing appropriate data. When the quantitative methodology is implemented, the risk of information biasing due to the researcher’s personal views, which may frequently interfere with the interpretation of qualitative data, is minimized. Therefore, it is possible to assume that the given research design is a perfect choice for our EBP research project.

In the study, new policies or intervention strategies will not be implemented. Instead, we will observe and evaluate the performance in two settings that adopt different nurse shift models. In one of the selected hospitals, nurses will work on the conventional 8- or 9-hour shifts, while in another one – on longer 12- or 13-hour shifts. During the study, we will analyze and contrast the findings, and it will help us to understand what shift model is correlated with better self-efficacy of health providers and patient satisfaction.

The primary instruments for data collection will be surveys and questionnaires. Since researchers found a direct link between the increased shift length and nurses’ burnout (Stimpfel, Sloane, & Aiken, 2012), we will first collect the data about the given variable. To do so, we will use the Maslach Burnout Inventory (MBI), a standardized tool for measuring three dimensions of burnout: depersonalization, emotional exhaustion, and personal accomplishment (Bria, Spanu, Baban, & Dumitrascu, 2014). The MBI is comprised of 22 items, and each of them uses 7-scale responses. The standard instrument is characterized by a high level of internal validity (Bria et al., 2014) and, therefore, the implementation of the MBI will be beneficial for the research.

Along with nurses’ burnout, some occupational factors in the selected settings will be analyzed. It is suggested that excess job demands and insufficient support resources cause the expenditure of energy in individuals which consequently leads to health impairment, i.e., burnout (Bria et al., 2014). On the contrary, when occupational and organizational factors are well balanced, employees demonstrate greater commitment to work and positive attitudes. For this reason, we will ask nurses to fill a questionnaire measuring their perceptions of the hospital culture and work climate. The questionnaire will include up to 10 items and use 5-scale response options, e.g., from “Strongly Agree” to “Strongly Disagree.” The tool will comprise such items as “I receive sufficient managerial support,” “My current schedule allows me to implement all professional skills efficiently,” “The nursing team cohesion in the hospital is strong,” and so on. Along with shift models, we should evaluate as many other organizational factors as possible because they may impact patient outcomes as well and without considering them, it will be difficult to get credible study results.

Lastly, we will develop a survey to evaluate patients’ satisfaction with service and quality of care. The participants will be asked to provide reports on nurses’ responsiveness, ability to meet their needs, communication style, etc. Additionally, all respondents – both nurses and patients – will fill the questionnaire on demographic factors. By including in the analysis various demographic variables, such as age, gender, the level of education, professional experience (for nurses), etc., we will minimize the risk of biasing during the generalization of final study results.

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Overall, the quantitative data collection tools allow an easier systematization, categorization, and management of data. However, self-reports are associated with increased subjectivity because there is a possibility that the actual situation can be underreported or exaggerated in participants’ responses. For instance, underreporting may result in obtaining the conservative results lacking depth and characterized by lower bound among the variables. Thus, the selected assessment instruments have some limitations, and potential biases should always be considered during the data analysis. Otherwise, the findings may lack validity.


It can be suggested to use the sample comprised of about 100 general practice nurses and 200-300 patients. Participants may be demographically diverse and, for this reason, the probability sampling technique may be applied. It means that the sample should be selected randomly, i.e., any individual and any setting can be involved in the research (Creswell, 2014). The sufficiently large sample size chosen by using random sampling will help to attain a greater generalization of evidence. It means that the study findings will apply to various types of settings and diverse population groups.

For the study, we will select two large public hospitals. The study participants from various intensive and non-intensive clinical units will be invited to participate. To facilitate the distribution of surveys among staff members, we will first contact the managerial and administrative personnel in the hospitals and inquire for their support in the data collection process. With the assistance of hospital managers, it will be easier to engage nurses in the research process, eliminate various organizational issues, and ensure that a high percentage of completed surveys will be returned.

Research Ethics

Ethical attitude towards study participants is essential in both qualitative and quantitative research processes. Research ethics are meant to help scholars to avoid harm to study participants and comply with all regulations and standards which protect the individual and public well-being. These major ethical principles include beneficence, fidelity, responsibility, integrity, justice, and respect for human rights and dignity (Resnik, 2015).

By these ethical principles, researchers must reduce the possibility of harm and negative influences on study participants not merely concerning their physical well-being but psychological state and social identity as well. It is also important to ensure confidentiality and avoid the disclosure of personal information without the permission of an individual. To avoid these risks, in the EBP project, the surveillance will be anonymous, i.e., participants will not be asked to provide confidential information that can be misused. However, although only general demographic data will be collected and disclosed, we will inform respondents about the scope of confidentiality and mention other ethical considerations in the written form. The notifications will be distributed along with surveys and questionnaires, and participants will be asked to give their informed consent for the treatment and disclosure of the collected information. By doing so, we will meet the ethical requirements and participants’ needs for privacy and confidentiality.

Analysis Tools

Quantitative methodology implies the interpretation of numerical information and the use of statistical analysis tools. Therefore, for the evaluation of initial data, we will use the Statistical Package for the Social Sciences (SPSS). The given program provides a large number of test options. First of all, the mean age for every group of study participants, the average time of nurses’ experience, and the mean burnout rate will be identified. A t-test will be conducted to contrast the average levels of exposure to shift-related burnout of nurses in two hospitals. After that, the simple logistic regression test will be carried out. In this test, the length of shift will be considered an independent variable, whereas burnout will be regarded as a dependent variable (no burnout event =0, and burnout =1).

Although statistical analysis is characterized by a high level of accuracy, the implementation of statistical instruments does not eliminate the risk of data biasing. Thus, it is essential to conduct the analysis and select study constructs in the agreement with all scientific rules. To do so, one needs to measure the construct and internal validity before conducting the main research (Shuttleworth, n.d.). For example, it is possible to complete a small pre-test to understand whether the designed research program will measure the intended attributes, or establish the temporal precedence of estimated cause and effect by examining previous studies (Shuttleworth, n.d.). In this way, it will be possible to reduce the risks of error when handling statistical data and achieve greater credibility.

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Week 1: Seeking the approval from the selected settings; design of appropriate data collection tools.

Week 2-3: Discussion of the project details and organizational issues with the hospitals’ management; distribution of surveys among staff members and patients.

Week 4: Data processing and categorization.

Week 5: Data analysis and interpretation of results.

Week 6: Summarizing and submission of findings.


The analysis of methodology, sampling, and data collection tools, their strengths and limitations helped to evaluate the overall efficiency of the quantitative research design. It is possible to say that the major advantage associated with quantitative study techniques is their capability to reduce the chance of misinterpretation. Nevertheless, it is also important to take into account multiple aspects of research design to ensure internal and external validity. It is essential to consider the potential limitations related to the selected data collection and sampling tools which may interfere with the obtaining of accurate and unbiased data or create barriers to the generalization of findings. Researchers should also ensure that the causal relationships between the study variables are analyzed consistently, and all extra demographic and other variables are included – such an approach will demonstrate the adequacy of conclusions. Overall, consideration of the mentioned methodological issues may contribute to the increased value of the EBP research.


Bria, M., Spanu, F., Baban, A., & Dumitrascu, D. L. (2014). Maslach Burnout Inventory – General Survey: Factorial validity and invariance among Romanian healthcare professionals. Burnout Research, 1(3), 103-111. Web.

Creswell, J. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. London, UK: Sage Publications.

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Resnik, D. (2015, December 1). What is ethics in research & why is it important?. National Institute of Environmental Health Sciences. Web.

Shuttleworth. (n.d.). Internal validity. Web.

Stimpfel, A. W., Sloane, D. M., & Aiken, L. H. (2012). The longer the shifts for hospital nurses, the higher the levels of burnout and patient dissatisfaction. Health Affairs, 31(11), 2501-2509. Web.

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