Objective(s): To assess mothers' practices toward children with steroid – sensitive Nephrotic Syndrome (SSNS) who
are visiting nephrology consultation units, and to find out the relationships between their practices and the
demographical data for mother and child.
Methodology: A descriptive study was carried out at nephrology consultation units of Baghdad pediatrics hospitals
(Child's Central Pediatric Teaching Hospital, Al-kadimiyia Teaching Hospital, and Welfare Teaching Hospital) started
from February 18th to the end of July 2009. A purposive sample of (80) mothers who company their children were
selected. The data were collected through a constructed questionnaire, with two parts; the first part is concerned with
mother's and child's demographical characteristic, the second part is concerned with mothers' practices about
steroid– sensitive nephrotic syndrome. An interview method was used to full questionnaire format. The validity was
determined through a panel of experts. While, the reliability was determined through a pilot study. The data were
analyzed by using descriptive and inferential statistical measures by using the statistical package of social science
(SPSS) version (15).
Results: The findings of the study showed that mothers have poor practices (61.3%). The study results revealed that
there is a significant association between mothers' practices and their educational level, and duration of the child's
disease. While mother's age, occupation, child's age, child's sex, child's age at onset (years), child's previous disease
and heredity have no association with their practices.
Recommendations: The study recommends that health education for mothers would improve their practices.
KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Drugs in Dermatology: JDD, 2013 - Cited by 22
The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.
And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)
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