Objective(s): To assess the practices of early childhood’s mothers regarding toilet training and to find out the relationship between mothers’ practices and their socio-demographic characteristics and their children’s demographic characteristics.
Methodology: A descriptive study is conducted at primary health care centers in Al-Rusafa District in Baghdad City for the period of September 19th 2020 to March 16th 2021. Non probability “convenient” sample of (225) early childhood’s mothers is selected. A questionnaire format is designed and composed of two parts: the first part includes mothers’ socio-demographic characteristics and their children and the second part includes structured close-ended questions to assess the practices of the early childhood’s mothers regarding toilet training. The reliability of the questionnaire is determined through a pilot study and the content validity is obtained through a panel of (15) experts. The data are collected through the use of the questionnaire and analyzed through the use of the descriptive and inferential statistical data analysis approaches.
Results: The study findings indicate that mothers’ practices are moderate toward toilet training and there are significant relationship between mothers’ practices and their socio-demographic characteristics of their education and marital status.
Recommendations: Extensive health education program should be applied by the Ministry of Health and Environment to enhance and develop early childhood’s mother practices regarding toilet training. Such program can be delivered through mass media, posters, booklets, and primary health care centers staff.
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... Show MoreDeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio
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