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.
Abstract
The purpose of the present paper is to light on the relationship between jobs design, analysis and its reflections on reinforcing workers' vocational adjustment. The present paper aims to accomplish cognitive and applied goals, top of which, test of functional analysis ability to have effect upon workers' vocational adjustment via job design directly and indirectly owning to the virtual factor practiced by these practices on the sought organization. The problem of the present paper comes with many, the most important is the of how to bolster and back up worker's technical adjustment through good and accurate design for the job.
Based on this problem and goals as to expla
... Show MoreThe current research aims to evaluate the activities and evaluation questions implied in the content of the computer textbook for the fifth preparatory grade according to the creative thinking and developing suggestions through answering the following question: what is the percentage of creative thinking skills in the content of the computer textbook for the fifth Preparatory grade students issued by the Iraqi Ministry of Education/ Directorate General of the curriculum in the academic year (2019-2020)? The researchers followed the descriptive-analytical approach. The research community was determined by the content of the computer textbook for the fifth preparatory grade. As for the research sample, it was limited to all activitie
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... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca
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... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
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