Objectives:
To evaluate mothers’ attitudes toward readiness for discharge care at home for a premature baby in Intensive Care Unit at teaching hospitals in Medical City Complex and to find out the relationship between mothers’ attitudes and their socio-demographic characteristics.
Methodology: A quasi-experimental study design was carried out through the period of 6th January 2020 to 2021 to 11th March 2021, to evaluate mother’s attitude toward discharge care plan for premature babies. The study carried out in Welfare Teaching Hospital, Nursing Home Hospital and Baghdad Teaching Hospital at Medical City Complex in Baghdad City on 30 mother of premature babies in neonatal intensive care units using the nonprobability sampling technique. The data was analyzed through the use of descriptive and inferential statistical data analysis approaches.
Results : The study findings indicated that most of the mothers are at age (23-29) years old, graduated from secondary schools, housewives, urban resident, and they had cesarean section delivery, they spend days at the NICU, with moderate level of socioeconomic status. Mothers had negative attitude at pretest mean score is (1.57), and at posttest mean score is (2.78) at high level of attitude toward readiness for discharge care at home for a premature baby in Intensive Care Unit.
Conclusion: The study concluded that the educational program has proved its effectiveness in improving mother’s attitudes toward readiness for discharge care at home for a premature baby in Intensive Care Unit.
Recommendations The study recommend for Training session for the nurses about discharge care plan and improves the attitudes of mothers to implementation that attitudes of mother to care of the premature babies at home.
The research dealt with the reservoir division for Upper Shale Member from Zubair formation in Luhais field, Where it was divided into six units of reservoir and non-reservoir, including the main reservoir unit 1C, which is the subject of research in this study, and studied in terms of thickness and lithology.
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This decline in agricultural and green land areas in cities has negatively affected the environment, natural life and biological diversity in cities in addition to the great impact on the climate and the increase in temperatures and the negative impact on the economic side, since urban agriculture is an important pillar of the economy, especially
... Show Morethe research was exposed to a study the importance of the role of the supportive entities in providing the useful information to the tax administration and their ability to extend the level of the tax base of taxpayers, through the improvement of the tax payers determination and their tax settle for the purpose of increasing the tax revenue, and shed light on the legal evidence through which these entities become officially assigned to perform a supplementary task to the General Committee for Taxes GCT, to help it to perform its task efficiently, and to study the reasons of the weak cooperation of the supportive entities and their reluctance to provide useful information which leads to limiting the tax base.
The research data hav
... Show MoreBackground: Ultrasonography has been used to examine the thickness of the lower uterine segment in women with previous cesarean sections in an attempt to predict the risk of scar dehiscence during subsequent pregnancy. The predictive value of such measurement has not been adequately assessed. Objectives: To correlate lower uterine segment thickness measured by trans abdominal ultrasound in pregnant women with previous cesarean section with that measured during cesarean section by caliper and to find out minimum lower uterine segment thickness indicative of integrity of the scar.Methods: A prospective observational study at Elwyia Maternity Teaching Hospital, from January 2011 to January 2012. A total of 143 women were enrolled in the stu
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... Show MoreCommunity detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local
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