Objective: To determine the effectiveness of the educational program on nursing staffs' knowledge about uses of steroids and their side effects.
Methodology: A pre-experimental study design (one group design: pre-test and post-test) was used. This study was conducted in Al-Diwaniya Teaching Hospital for the period from ( 28th May to 10 th June, 2020) on a non-probability (purposive) sample consisting of (30 nurses) working in Oncology unit. A questionnaire was built as a data collection tool and consisted of two parts:
First part: The demographic characteristics of the nursing staff (gender, age, level of education, years of experience in hospital, participation in training courses related to nursing care for a patients undergoing to steroid therapy).
Second part: It consists of two domains. The first domain contains (27) multiple-choice questions about assessment of the nursing staffs` knowledge regarding steroids and their uses, while the second domain contains (15) multiple-choice questions about assessment of the nursing staffs` knowledge regarding side effects of steroids. The validity of the questionnaire and the educational program were verified by presenting it to (14) experts. The sample has received a pre-test, educational program, and post-test. Descriptive and inferential statistics were used to analyze the results of the study using the Statistical Package of Social Sciences (SPSS) version 25 and Microsoft Excel (2010).
Results: The study indicates that all the study sample responses at the pre-test were poor knowledge with a statistical mean of scores (1.20), other than the post-test, shows (100%) of the study sample have high knowledge at the mean of scores (1.91). Also, the results revealed a highly significant difference between the pre-test and post-test of the study sample after participated in the educational program at the p-value (0.0001). The conclusion of the study that the educational program was effective in the enhancement of nursing staffs` knowledge about uses of steroids and their side effects in Oncology Unit.
Recommendations: The study recommended the necessity of developing continuous educational programs to educate and train nurses and all health care workers regarding steroids.
A Tonido cloud server provides a private cloud storage solution and synchronizes customers and employees with the required cloud services over the enterprise. Generally, access to any cloud services by users is via the Internet connection, which can face some problems, and then users may encounter in accessing these services due to a weak Internet connection or heavy load sometimes especially with live video streaming applications overcloud. In this work, flexible and inexpensive proposed accessing methods are submitted and implemented concerning real-time applications that enable users to access cloud services locally and regionally. Practically, to simulate our network connection, we proposed to use the Raspberry-pi3 m
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Decolorization of red azo dye (Cibacron Red FN-R) from synthetic wastewater has been investigated as a function of solar advanced oxidation process. The photocatalytic activity using ZnO as a photocatalysis has been estimated. Different parameters affected the removal efficiency, including pH of the solution, initial dye concentration and H2O2 concentration were evaluated to find out the optimum value of these parameters. The results proved that the optimal pH value was 8 and the most efficient H2O2 concentration was 100mg/L. Toxicity reduction percent for effluent solution was also monitored to assess the degradation process. This treatment method was able to strongly reduce the color and toxicity of reactive red dye-238 to about (99 an
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... Show MoreThis paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF
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