Objective: To evaluate the knowledge and practices of nursing staff at the orthopedic wards relative to
nursing care presented to patients with femur fractures.
MethodologyThe sample consisted of (50) staff nurses was selected out of orthopedic wards of five
teaching hospital in Baghdad city for duration 15th Nivember 2001-15th of January 2002.
For the purpose of data collection, two instruments were constructed. First, observational
checklist for the practices measurements and second, knowledge test for the evaluation of the nurse
knowledge. Such construction was employed through literature review and validity expert’s responses.
Data were analyzed through the application of descriptive data analysis (frequency, percentage, standard
deviation, mean of scores and the inferential data analysis (Pearson correlation coefficient, one-way
analysis of variance, t-test and LSD).
Results The findings indicated that there was no significant between nurses knowledge and their nursing
care, years of employment, years of experience and training courses, but, there was significant
relationship between their knowledge and education only. The study concluded that there was no
significant relationship between the nurses practices and their years of employment, education, and
training courses, but, significant relationship was found between their practices and years of experience.
Recommendations :The study recommended that the numbers of staff nurses should be increased,
education and training programs for the nurses should be evaluated and periodic evaluation measures for
these nurses should be constructed
KE Sharquie, AA Noaimi, SA Al-Hashimy, MM Al-Salih, Journal of Cosmetics, Dermatological Sciences and Applications, 2014 - Cited by 12
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The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit
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