Objective(s): To measure the level of job satisfaction and job performance of nurses and to find out
the association between participants' socio-demographic characteristic of nurse and their job
satisfaction and job performance.
Methodology: A descriptive analytic study design was carried out to measure the nurses' level of job
satisfaction and job performance in Al-Suwaira general hospital and to find out the association between
nurses and their socio-demographic characteristic. The study was started from March 5th, 2017 to
September 31th, 2017. The sample was Non - probability (purposive) sample of (100) nurses were
selected according to the study that are actual working in nursing department in Al-Suwaira General
Hospital. The data were collected by direct interview using specific questionnaire thats composed of
three parts (27) items which are: Part (1) Socio-demographic characteristics which included seven
items (age, gender, marital status, level of education, participation in training courses or scientific
conferences inside or outside Iraq and engaged in the nursing by your choice). Part (2) which deals
with job satisfaction and includes (10) items and Part (3) which deals with job performance including
(10) items. Data were analyzed by using (SPSS) package version 20. Descriptive data through
determination of: Frequency, percentage and mean of score. Inferential statistical data analysis
approach: used by enforcement of the Chi –square test used for determining the association between
Socio-demographic characteristics and job satisfaction, job performance, testing the significant of the
contingency coefficient. For this study the significant P-value ≤ 0.05.
Results: ( (77%) were female, (56%) were married, the total grade level of job satisfaction is low, and
present highly statistical significant association between items which is related to job satisfaction and
gender and highly statistical significant association between the items related to the job performance
and age.
Recommendations: The study recommends that establish and follow up programs about job
satisfaction to increase job performance
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. T
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