Objective(s): To Evaluate Diabetes self –management among patients in Baghdad City and to compare
between these patients self-management relative to the type of the disease.
Methodology: A descriptive design was conducted in Baghdad city, started from November 16th 2017 to the
end of May 17 th 2018 in order to evaluate Diabetes self-management. Purposive (non-probability) sample,
which was consisted of (120) patients who were diagnosed with D.M. The sample is comprised of (60) patient
with diabetes type I and (60) patient with diabetes type II. It is consisted of (60) male and (60) female. A
questionnaire is constructed for the purpose of the study. It is composed of (42) items. Reliability and validity of
the questionnaire is determined through pilot study. Data are collected through the use of the questionnaire and
the structured interview as means of data collection. Data are analyzed through the application of descriptive
statistical data analysis approach of frequency, percentage, mean, range and total scores and inferential
statistical data analysis approach of t-test.
Results: The results show that more than a half have a poor level of diabetes self-management (n = 64; 53.3%)
and a lesser proportion who have a good level of such management.
Recommendations: Further study can be conducted on subjects with a large sample size. An education
program can be done to improve patient knowledge about the diabetes self-management. Better attention can be
directed for patients who were students, married and low income ones
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Objectives: To determine the correlation between serum cholinesterase activity and gastric cancer, in comparison to benign gastric diseases.
Subjects and Methods: A case control study carried out at Medical City Direct
... Show MoreNowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th
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