Abstract
Objectives: The study aims to: (1) Find out the relationship among participants’ age, body mass index (BMI), and Health Belief Model (HBM) related to colorectal examinations among graduate students. (2) Investigate the differences in Health Belief Model constructs between the groups of age, gender, marital status, and education level among graduate students.
Methodology: A descriptive correlational study design which conducted in the College of Fine Arts – University of Baghdad. A convenience sample of 80 graduate students were included in this study. The data were collected by using a self-reported questionnaire which consisted of two parts (I) socio-demographic characteristics (II) Colorectal Cancer Screening Beliefs Scale. The statistical package for social science (SPSS) for windows Version 24 was used for data analyses.
Results: The study finding revealed that the participants’ age mean was 39.82. There was no significant association between all Model constructs and each of age and BMI. While, there was a positive significant association between participants’ perceived susceptibility of contracting colorectal cancer and their perceived severity of colorectal cancer. Furthermore, there was a statistically significant difference in the cues to action related to performing colorectal examinations between education level groups.
Recommendations: Future studies and instructional programs based on the Health Belief Model are needed on various segments of the Iraqi population with the goal of changing the public’s beliefs about performing colorectal examinations.
This study aims to measure the basic foundations of organizational health in the General Company for Food Products and to indicate the extent of its presence or not within the company under investigation.
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The research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.
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Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.
In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe
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This research deals with one of the most important components of civilizations in general and Islamic civilization in particular, which is thinking and what is related to it. It is an essential and influential component in man's dealing with life around him and the for
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Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat
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