Objective(s): To evaluate nurses' practices who work in respiratory intensive care units to control the
complications of patients admitted at this unit and determine the relationship between nurses' sociodemographic
characteristics and their practices.
Methodology: A descriptive study was carried out at Respiratory Care Unit at Baghdad teaching hospitals that
started from February 22th, 2013 to August 30th, 2013. A purposive "non-probability" sample of (70) nurses who
work in Respiratory Care Unit was selected from Baghdad teaching hospitals. The data were collected through the
use of constructed questionnaire that consists of two parts; (l) Demographic data form that consists of 7items and
(2) nurses' practice form that consists of 4sections (112) items. Data were collected by means of direct observation
technique with the nurses. The reliability of the questionnaire was determined through a pilot study that was
carried out through the period from January 6th 2013 through February 10th 2013.Descriptive statistical measures
(frequency, percent, mean of score, Standard deviation and Weighted mean) and inferential statistical (Regression)
was used for the data analysis.
Result: The findings of the study indicated that there is a practice deficit of Respiratory Care Unit nurses in some
aspects relative to control of patient complication. significant relationship was found between nurses' practice and
their (age, gender, marital status, level of education, Years of working in nursing, Years of working in RCU,
Participation in training courses, Number of training courses related to RCU, Place of training courses in RCU,
Duration of training courses in RCU, and in Respiratory Care Unit Nurses' practice to control of patient
complication in Respiratory Care Unit.
Recommendations: The researchers recommend that special training session, concerning patient complication and
standard Respiratory Care Unit nurse practice toward patient complication that should be followed in Respiratory
Care Unit wards and booklets should be designated and presented to all Respiratory Care nurses.
A new class of higher derivatives for harmonic univalent functions defined by a generalized fractional integral operator inside an open unit disk E is the aim of this paper.
As major nosocomial pathogens,
In this study, 20
This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc
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