Hala Gabr And Ahlam Mahmoud El-Shaer In

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¶ … Hala Gabr and Ahlam Mahmoud El-Shaer in Public Policy and Administration Research. The purpose of the study was to determine if there are relationships between the job demands and resources of head nurses with their work engagement. The two authors argue that it is important to understand the role of the head nurse in order to understand their sense of engagement in their work. The researchers used a correlation design. They conducted their study in the general units of four University hospitals in Mansoura -- Emergency Hospital, Main University Hospital, Specialized Medical Hospital, and Pediatric Hospital. These hospitals were chosen because they provide a wide range of services and would provide in-depth information about the work engagement of head nurses. The dependent variable was work engagement while the independent variables were job demands and job resources Gabr & El-Shaer, 2013() Study participants

The study included all head nurses working in all general units of the four hospitals mentioned above. The number of head nurses in the Main University Hospital was 66 followed by 59 in the Emergency Hospital, 34 in the Specialized Medical Hospital and 20 in the Pediatric Hospital. To be included in the study, the head nurses had to have at least one year in the job as a first-line nurse manager. They also had to be available during the data collection period Gabr & El-Shaer, 2013()

Data collection

The study used three (3) tools to collect data. The first tool is the Job Demands Scale which was developed by the researchers based on their review of the literature. This tool collected demographic information about the teachers then asked 32 questions relating to the job demands of head nurses while at their workplace. The demands were categorized as their physical, social, psychological, or organizational concepts Gabr & El-Shaer, 2013()

The second tool that they used was the job resources scale. This tool defined the job resources of head nurses that facilitate them to achieve their work goals, reduce their demands in the workplace and stimulate their personal growth. This tool included six subscales of resources and these were autonomy, organizational support, and performance feedback Gabr & El-Shaer, 2013()

The last tool that the researchers used was the work engagement scale. This tool measures the work engagement of the head nurses. It has 17 items that are categorized under vigor of the job -- defined as the persistence in face of challenges, dedication -- defined as the sense of significance or enthusiasm from a person's work, and absorption -- defined as being totally immersed in one's work Gabr & El-Shaer, 2013()

Data collection

Using coefficient alpha, the researchers found that the internal consistency reliability of the work engagement scale was 0.90. To ascertain the clarity, feasibility, and focus of the study, the researchers conducted a pilot...

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After participating in interviews, the head nurses were given the questionnaire to respond to the questions. Each sheet was estimated to take between 10 and 15 minutes per nurse to answer Gabr & El-Shaer, 2013()
Data analysis and results

After collecting the data, the researchers used simple mean and standard deviation to summarize the numerical variables. They conducted multiple regression analysis to evaluate whether job resources and job demands would be predictive factors of work engagement. To test their hypothesis the researchers used standard linear regression. They used the r-test for correlation analysis between numerical variables Gabr & El-Shaer, 2013()

The use of correlation in studies dates back many years. The largest advantage of this method according to scholars is that it allows the researchers to predict which one set of variables Voss & Parasuraman, 2003.

A good example is if we know the SAT scores of students, we can predict their achievement in college. Therefore, for this study, since they used correlation to predict work engagement using job resources and job demands, the researchers were interested to know whether there was a relationship between these variables and how this can be quantified on a particular scale.

At the same time, the correlation method has one significant weakness. This is that it does not indicate causation. In the results section of the paper, table 4 and 5 show that there is significant correlation between components of job demands and job resources to work engagement. However, this correlation does not mean that job demands or job resources cause work engagement. This is a common misconception and should also be avoided in interpreting the results of this study. When correlation is positive, it suggests that when the independent variable increases or decreases, the other follows the same patter. A negative correlation suggests that as the independent variable increases, the other follow the opposite pattern.

The multiple regression model method chosen the researchers is used to determine the relationship between dependent and independent variables. Since the dependent variable of this study is work engagement and the independent variables are job demands and job resources, the researchers use the multiple regression method to estimate this relationship. Multiple regressions, however, does not check whether the data is linear in nature. It assumes that the relationship between the dependent and independent variables is linear. The second assumption is that there is no multi-collinearity. This means the independent variables -- job demands and job resources - are not tested against each other.

The significance level was 0.05. This level of significance is the most common in quantitative studies. This is because the pioneer of significance testing, Fisher, argued that the P

Sources Used in Documents:

References

Gabr, H., & El-Shaer, a.M. (2013). Head Nurses ' Job Demands and Resources and its Relationship with Their Work Engagement at Mansoura University Hospitals. Public Policy and Administration Research, 3(4), 33-42.

Peck, R., & Devore, J. (2011). Statistics: The Exploration & Analysis of Data. Stamford, Connecticut: Cengage Learning.

Voss, G.B., & Parasuraman, a. (2003). Conducting Measurement Validation with Experimental Data: Cautions and Recommendations. Marketing Letters, 14(1), 59-73.


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