Improving Hand Hygiene In Developing Countries Essay Sample For College

In order to focus on evidence-based practice in the sphere of nursing and providing healthcare services, it is necessary to be able to effectively evaluate articles representing the results of research studies. The article under assessment is titled “Predictors of Hand Hygiene Behavior Among Nurses: A Theoretical Cross-Sectional Study,” and it was written by Rahimi et al. (2019). The authors conducted a quantitative cross-sectional study, and the purpose of this paper is to review and evaluate the research article to determine its quality and validity.

Research Problem/Purpose

The researchers formulated the study’s problem in the following way: poor compliance to hand hygiene (HH) norms is observed among Iranian hospital nurses because of certain personal views and organizational factors. The purpose of the study was to examine the role of the BASNEF (beliefs, attitudes, subjective norms, along with enabling factors) model in constructing nurses’ effective HH behavior and performance (Rahimi et al., 2019). The authors of the study discussed the problem of poor HH performance in the context of existing nursing knowledge with reference to the BASNEF model and evidence from other studies. While referring to the purpose of the study, it is possible to state that it can solve the problem of HH performance that is relevant to nursing. The reason is that the researchers determined the correlation between nurses’ age and experience at work and their HH behavior to prevent nosocomial infections in hospitals.

Review of the Literature

The authors’ assumptions are based on the previous studies on similar topics. The elements of the literature review are presented in the introduction section of the article to provide the background for the study and in the discussion section. The researchers explored such concepts as the HH behavior, HH compliance, and HH behavior predictors in their introductory part to support their formulation of the study problem and aim. In the discussion part, the references to other studies were actively used to compare and support the findings (Rahimi et al., 2019). Among 25 sources, only eight sources were published within the past five years, and the authors used the sources published more than 10-15 years ago although the original study was conducted in 2018 (Rahimi et al., 2019). Therefore, the researchers’ approach to selecting the literature to support findings can be discussed as inappropriate and can be caused only by the limited number of sources on nurses’ HH performance in Iran.

Theoretical Framework

The researchers organized their study as a quantitative theoretical work. However, in spite of referring to the BASNEF model as a framework for their research, Rahimi et al. (2019) did not explain a theoretical framework in their study effectively. One should state that the research is based on the BASNEF model actively applied not only in nursing but also in healthcare-related research (Matar et al., 2018; Schmidt & Brown, 2019). The article lacks a detailed description of assumptions and the nursing theory to be used in this research. The theory that can be applied in combination with the BASNEF model is Ajzen’s theory of planned behavior. The reason is that the theory of planned behavior explains how a person’s beliefs, attitudes, and subjective views influence behaviors, including the HH behavior (Piras et al., 2017). Although this theory is not recognized as a nursing theory, it is directly linked to this study.


The research question and hypotheses were not clearly stated by the researchers, and they can only be implied. Thus, the potential research question is the following: what is the relationship between the predictors of HH behavior and nurses’ actual HH performance? The variables used by Rahimi et al. (2019) were not clearly described in the article, but it is possible to assume that independent variables are nurses’ age, work experience, and the BASNEF model components, and a dependent variable is the HH behavior. Due to the fact that the authors did not present clear definitions of these variables, it is rather difficult to interpret the study results with reference to the research purpose and question. Furthermore, the provided dependent variable of HH behavior did not seem to be concrete or easily measurable.


In the analyzed research, a quantitative descriptive and correlational research design was used. However, the problem is that Rahimi et al. (2019) provided different definitions for their research design as they named it a theoretical cross-sectional study and a descriptive analytical study. As the study is quantitative, deductive reasoning was applied by the researchers. The setting for the study covered hospitals in Ardabil and Khalkhal, Iran. The sample included 498 nurses, and they were selected with the help of a multistage sampling method, as it was reported by Rahimi et al. (2019). The probability sampling technique was applied as the researchers started from random sampling, and then they used inclusion and exclusion criteria to form their sample.

The independent variables were tested with reference to the questionnaire based on the BASNEF model, and the dependent variable in the study was also measured with the help of that questionnaire based on the Likert scale. The problem is that there were no clear descriptions of the variables’ measurement or their validity in the article although it was stated that the used questionnaire was a valid and reliable (Rahimi et al., 2019). Ethical considerations were mentioned by the researchers as the participants were required to provide their oral informed consent to participate in the study.

Data Analysis

The data collected with the help of the adopted questionnaire and a Likert scale were analyzed using statistical tests and SPSS software. The researchers conducted a t-test, an ANOVA test, a Pearson’s correlation test, as well as multiple linear regressions, to determine the relationship between predictors of HH behavior and actual nurses’ behavior. The results of the study were presented with the help of tables to illustrate numerical data, and the findings were interpreted in the results section of the article. It was found by Rahimi et al. (2019) that nurses’ age and work experiences were negatively correlated with their HH behavior as a dependent variable. Nurses’ attitude toward HH was in a positive correlation with some of the BASNEF model components, including enabling factors. Still, the BASNEF model elements did not have a significantly high predictive power (3%) for influencing nurses’ HH behavior (Rahimi et al., 2019). It is possible to state that the interpretation of the results could be more detailed for guiding nurses and other researchers on the findings’ significance.

Summary/Conclusions, Implications, and Recommendations

The researchers concluded that the BASNEF model specific components could not predict nurses’ HH behavior although age and work experience served as critical factors in HH performance. The authors noted that the limitation of the study was associated with the lack of time to conduct a causal relationship study (Rahimi et al., 2019). However, it is important to state that the current study also has other limitations and weaknesses, such as problems with defining the variables and a research design. It is rather problematic to determine how the researchers measured nurses’ HH behavior as a dependent variable as no explanations were provided. The strengths of the research are associated with the application of several statistical tests to provide credible results on the relationship between the variables.

Still, it is rather problematic to generalize the study’s results to other populations as the focus was only on nurses, and the discussed research design has weaknesses in its organization and realization. The significance of the presented findings is in drawing the attention to such factors as age and work experience that can predict nurses’ HH behaviors, and these factors need to be tested in clinical practice. It is important to note that the study’s significance for nursing is in providing a new perspective on the effectiveness of the BASNEF model to explain nurses’ behaviors, including those related to HH.


The completed review and assessment of the research article indicate that the study presentation lacks details and explanations. When referring to the limited explanations presented in the article, it is possible to assume that the study had some weaknesses associated with the formulation of variables and its methodology. In spite of the study’s weaknesses, the ideas that were presented in the article can be used by other researchers and nurses for testing similar hypotheses in other contexts and clinical settings.


Matar, M. J., Moghnieh, R. A., Awad, L. S., & Kanj, S. S. (2018). Effective strategies for improving hand hygiene in developing countries. Current Treatment Options in Infectious Diseases, 10(2), 310-329.

Piras, S. E., Lauderdale, J., & Minnick, A. (2017). An elicitation study of critical care nurses’ salient hand hygiene beliefs. Intensive and Critical Care Nursing, 42, 10-16.

Rahimi, G., Kamran, A., Sharifian, E., & Zandian, H. (2019). Predictors of hand hygiene behavior among nurses: A theoretical cross-sectional study. Journal of Medical Sciences, 39(6), 278-283.

Schmidt, N. A., & Brown, J. M. (2019). Evidence-based practice for nurses: Appraisal and application of research (4th ed.). Jones & Bartlett Learning.

Modelling In The Marine Environment

Storm surges provoke increasing interest in relation to catastrophic occurrences and their damage in coastal and estuarine areas as the physical processes presently observed jeopardize coastal life. Notably, Global Warming raises the danger of coastal flooding caused by multiple phenomena (Rahmstorf, 2017). For instance, the Atlantic hurricane season in 2017 resulted in almost unprecedented damage as Hurricane Irma maintained category five according to Saffir–Simpson scale for especially log time (Rahmstorf, 2017). Although storm surges are not the only danger that climate change accentuates, they are significant for the global community’s well-being. With climate change rendering hurricanes more deadly, it is essential to gain a more in-depth understanding of such phenomenon as storm surge. It is also significant to ensure that accurate and prompt forecasting systems are available in the most vulnerable zones.

Defining the notion from the outset helps gain a more in-depth understanding of its nature and mechanisms. Thus, storm surges constitute one of the numerous variables used to characterize the dynamic state of oceans and seas (Wu et al., 2018). More precisely, a storm surge is described as “the abnormal sea level variation forced by wind stress and sea level pressure gradients over the sea surface” (Ji and Li, 2019, p. 301). The mechanisms of storm surge formation can be seen in Figure 1 (National Weather Service, 2020). The phenomenon is also known under the name of ” meteorological residuals” or “meteorological tides.” In combination with waves and tidal oscillations, it is a primary contributor to elevated water levels in the zones bordering the shoreline (Ji and Li, 2019). Such territories more frequently experience damaged infrastructure, loss of human life, and biodiversity caused by flooding resulting from elevated water levels. In its turn, the flooding is typically a result of a combination of multiple factors, among which are high storm surges.

The mechanisms of storm surge formation.
Figure 1. The mechanisms of storm surge formation.

In recent decades understanding of storm surges and predictive models has considerably improved. Currently, storm surge forecasting systems became integrated into more countries. The systems can issue forecasts in real-time and became large-scale (Khan et al., 2020). Although storm surge systems consist of somewhat straightforward and well-established physics, detailed forecasts have higher requirements. In order to be accurate, storm surge forecasting systems need “TC condition (predictions and forecasts) as input, reasonable storm surge predictions (with forecasting systems), and effective advisories/warnings (i.e., useful information products)” (Kohno et al., 2018, p. 128). Such systems’ performance is determined by the quality of data regarding relevant processes (waves, tides, surges, and their interactions) and wind and atmospheric pressure forcing (Khan et al., 2020). Typically, mistakes related to wind and atmospheric pressure forcing impede accurate storm surge forecasting. As a result, for enhanced reliability, input, forecasting systems, and efficient data should be ameliorated systematically.

Storm surge forecasting and modeling are of supreme significance in the North Sea region. This region is particularly vulnerable because of the low-laying territories bordering the sea. For instance, the flood of 1953 was a disastrous event heavily affecting countries situated along it (Garnier et al., 2020). Advanced storm surges forecasting systems can alleviate the danger in the region. Presently, pan-European Storm Surge Forecasting enhances storm surge predictive capability along the North Sea (Fernández-Montblanc et al., 2019). The system led to a 2% reduction in RMSE (the inaccuracy of a model in forecasting), which is a considerable improvement for the region (Fernández-Montblanc et al., 2019). The superior performance permits to record the tidal dynamics and surges propagation in the area under consideration. In addition to the Europe-Wide forecasting, countries along the North Sea have their operational systems. For instance, the system protecting the German North Sea coastline consists of weather forecast systems, a surge model, and model output statistics (Niehuser. et al., 2018). It can be seen that storm surge forecasting operates extensively along the North Sea.

In the North Adriatic Sea, water level abnormalities are not exceptional. The area suffers from astronomical tides, seiches, storm surges, relative sea level rises, and others (Lionello et al., 2020). These phenomena do not have the same impact on how they contribute to extreme water level events and coastal inundations (Zampato et al., 2016). These events are mostly caused by large storm surges, while other water level abnormalities contribute only slightly, which can be seen in Table 1 (Lionello et al., 2020). Regarding Venice, low tides are typical for the city as it is flooded several times a year when the Adriatic Sea tide rises, with the first such instance registered in 782 AD (Garnier, 2018). While low tides are ordinary for Venice, storm surges causing extreme sea levels are less habitual in the territory as the frequency with which they occur accelerated only during this century given the climate change. Hence, the contradiction can be explained by the fact that high tides and storm surges are less typical and more dangerous as the height of water they bring is drastically different from low tides.

List of the extreme sea levels in Venice.
Table 1. List of the extreme sea levels in Venice.

In terms of damage caused by extreme sea levels, similarly to countries along the North Sea, Hong Kong is particularly vulnerable. The city is projected to be among the top 50 urban zones at risk of future flood losses (De Dominicis et al., 2020). The projection is partly based on the city’s geography: situated on Southern China’s coast, the city experiences the effects of tropical cyclones, significantly raising water levels. Hence, storm surges are a frequent problem in this urban area, causing severe damage, which is seemingly amplified in the forthcoming years due to the rising global mean water level (Jilong, 2020). Similar to the North Sea territories, storm surge monitoring and prediction in Hong Kong cannot be overestimated for the well-being and protection of the local community.

Despite the equal implications, storm surges in Hong Kong and the North Sea have a somewhat different nautre. While in Hong Kong, their leading cause is tropical cyclones, in the North Sea, storm surges result from hurricane-force winds and several accidental factors in combination with the territory’s meteorological peculiarities (Jilong, 2020). Ultimately the cause of storms in the two territories is comparable, as low pressure and strong winds are necessary for both tropical cyclones and storms (Ji and Li, 2019). The purpose of forecasting systems in these territories can be reduced to detection and reaction to the forthcoming danger as promptly as possible.

In conclusion, storm surges are complex natural phenomena, the effect of which the current state of climate aggravates. Large coastal areas suffer from storm surges, including the territories along North Adriatic Sea, the North Sea, and such massive urban regions as Hong Kong. Although the nature of storm surges is slightly different there, its dangers appear almost equally high. The potential damage of storm surges accentuates the need for accurate and fast forecasting systems. They are systematically developed and show consistently improving accuracy even in real-time reporting, bringing hope to coastal areas.

Reference List

De Dominicis, M. et al. (2020) Future interactions between sea level rise, tides, and storm surges in the world’s largest urban area. Geophysical Research Letters, 47(4), e2020GL087002.

Fernández-Montblanc, T. et al. (2019) Towards robust pan-European storm surge forecasting. Ocean Modelling, 133, pp.129-144.

Garnier, E. et al. (2018) Historical analysis of storm events: case studies in France, England, Portugal and Italy. Coastal Engineering, 134, pp.10-23.

Ji, T. and Li, G. (2019) Contemporary monitoring of storm surge activity. Progress in Physical Geography: Earth and Environment, 44(3), pp.299-314.

Jilong, C. (2020). Impacts of climate change on tropical cyclones and induced storm surges in the Pearl River Delta region using pseudo-global-warming method. Scientific Reports, 10, pp.1-10.

Khan, M. et al. (2020) Towards an efficient storm surge and inundation forecasting systemover the Bengal delta: chasing the super-cyclone Amphan. Natural Hazards and Earth System Sciences, pp.1-29.

Kohno, N. et al. (2018) Recent progress in storm surge forecasting. Tropical Cyclone Research and Review, 7(2), pp.128-139.

Lionello, P. et al. (2020) Extremes floods of Venice: characteristics, dynamics, past and future evolution. Natural Hazards and Earth System Sciences, pp.1-34.

National Weather Service (2020). About storm surge. Web.

Niehuser, S. et al. (2018) A novel high-resolution storm surge forecast for the German bight. Coastal Engineering Proceedings, 36, p.80.

Rahmstorf, S. (2017) Rising hazard of storm-surge flooding. Proceedings of the National Academy of Sciences, 114(45), pp.11806-11808.

Wu, W., et al. (2018) Mapping dependence between extreme rainfall and storm surge. Journal of Geophysical Research: Oceans, 123(4), pp.2461-2474.

Zampato, L. et al. (2016). Storm surge modelling in Venice: two years of operational results. Journal of Operational Oceanography, 9(1), pp.46-57.

The Orange Door Health Center: Solution

Strategic Plan for the Orange Door Health Center Addressing Environmental Issues and Perspectives for Development

Because three areas will be considered in a strategic plan – staff development, managerial approaches and technological advancement – a transformation of the Orange Door Health Center should be carried out about these aspects (Filipovitch, 2006). First, an action plan will be directed at restructuring voluntary-based staff to the paid-off staff, which is possible through introducing salary planning and beneficial schemes.

Second, the strategic plan will integrate a specific management information system that will enable nurses to freely communicate and exchange information. In such a manner, nurses can ensure efficient medical treatment of patients, as well as high-quality delivery of health care services. Finally, technological advancement is imperative for enhancing the information flow between patients and nurses through supplying effective data recording systems. Overall, the given plan should greatly promote the transition process and provide fresh insights for developing new facets of the center’s improvement.

Identifying Strategies from Organizational, Operational, Managerial, Financial Perspectives

For introducing the above-identified changes, the following strategies must be highlighted. First of all, it is necessary to survey the employees to have a better picture of the staff needs and concerns. Hence, a survey can be presented in the form of a questionnaire composed of the questions related to the environmental, organizational, and material concerns of the nurses. In such a manner, it is possible to define what packages and salaries should be introduced.

In addition, the questionnaire will provide nurses with incentives for increasing their professional and organizational performance. Second, introducing an integrative management system implies changing nurses’ outlook on and attitude to cooperation and communication. Managers should consider carefully the cultural and social backgrounds of nurses to meet their concerns and needs more effectively. In their turn, nurses should report to managers about their actions because accountability and transparent reporting minimize the risk of misconceptions and ensure effective information flow. Finally, technological advancement is possible through presenting specific data exchange devices, such as I-Pads that will contribute to the quick and easy exchange of information among the employees.

Defining How the Identified Strategies Affect Environmental Issues

Promoting a new outlook on the managerial system and staff development, the managers will certainly notice tangible changes that will occur in the department. This is of particular concern to such fields as workforce identification, nurse turnover, organizational performance, and level of patient satisfaction. All these strategies can significantly improve the working environment and provide wider space for the development and advancement of the Orange Door Health Center. Moreover, it will help to gain a competitive advantage over other reputable health centers.

The rationale for the Strategic Plan

An effective and accurate algorithm for introducing changes to the organizational process at the center is indispensable for ensuring proper performance and delivery of health care services. Specific attention should be paid to determining workforce size and shift schedule for allocating human resources properly (Sinreich & Jabali, 2007). Focusing on resources allocation is paramount because it shapes the basis for effective nurse management (Yarbrough & Powers, 2006). The proposed strategies can integrative a transformative dimension in the future because organizational change is an important condition for successful management of the center, as well as for sustaining a competitive edge over other existing centers (Michielsen et al., 2010). Finally, applying these approaches can guarantee the high quality and safety of patient treatment.


Filipovitch, A.J. (2006). Organizational transformation of a community-based clinic. Nonprofit Management & Leadership, 17(1), 103-115.

Michielsen, J. A., Meulemans, H., Soors, W., Ndiaye, P., Devadasan, N., De Herdt, T., &… Criel, B. (2010). Social protection in health: the need for a transformative dimension. Tropical Medicine & International Health. pp. 654-658.

Sinreich, D. & Jabali, O. (2007). Staggered work shifts: A way to downsize and restructure an emergency department workforce yet maintain current operational performance. Health Care Management Science, 10(3), 293-308.

Yarbrough, A.K., & Powers, T.L. (2006). A resource-based view of partnership strategies in health care organizations. Journal of Hospital Marketing & Public Relations, 17(1), 45-65.

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