Zeitschrift für Gesundheit und medizinische Informatik

Background:Sexually transmitted infections are a major global cause of acute illness, infertility; long-term disability especially in women and children. In Ethiopia, Sexually transmitted infections are among the top five disease for which child bearing age group and adult seek medical care. However, information with regard to knowledge, attitude and practice towards STI is limited in our country.

Objective:To assess Knowledge, Attitude and Preventive Practice towards sexually transmitted infection among preparatory school students, in Shone Town, SNNPR, Ethiopia, 2014.

Methodology:Institution based cross sectional quantitative study was conducted among 982 students in Shone preparatory school. The sample size was calculated by using single population proportion and stratified sampling method was used to get the study subjects. Finally the collected data was analyzed by SPSS 20 version.

Results:Almost all the students had heard about STIs before the interview. They had good knowledge regarding to mode of transmission, prevention method of STIs and others in the study group. Only 15.18% had negative attitude towards STIs. Among the respondents 42.20% didn’t agreed with the idea that having history of STIs increase acquisition of HIV/AIDs and 27.70% had not agreed with condom can prevent STIs.41.25% had practiced sexual intercourse while, 1.60% of them had practiced with commercial sex workers and 71.20% who had sexual intercourse had used condom. On bivariate analysis only knowledge about STI shows significant association with attitude of students towards STI prevention, with those who had poor knowledge about STI were more likely to develop negative attitude towards STI prevention than those who had good knowledge about STI (OR 3.65, [95% CI 1.44 to 9.30]).

Awareness about STIs and methods of prevention of STIs was high. Generally the level of knowledge towards prevention of STIs were high despite half of them had negative attitude towards STIs can cause social stigma and discrimination. Based on the results, the following recommendations were made. The link between STIs and HIV/AIDS should be reinforced. Emphasizing that STIs increase the likelihood of HIV transmission may increase people’s concern about STIs and lead to less risky behavior. Our investigation call for continued and strengthened health education to bring and promote positive attitude and behavioral changes among the students in shone town.

Abstract Background: The Objective Structured Clinical Examination (OSCE) and Multi Mini Interviews (MMI) are established tools in the repertoire of clinical assessment methods in Schools of Medicine and Health Sciences worldwide. The use of OSCEs facilitates the assessment of psychomotor skills as well as knowledge and attitudes. Identified benefits of OSCE assessment include development of students’ confidence in their clinical skills and preparation for clinical practice. However, a number of challenges exist with the traditional paper methodology, including documentation errors and inadequate student feedback, electronic assessment is therefore new future. Objectives: To explore electronic OSCE delivery and evaluate the benefits of using an electronic OSCE management system. Design: A pilot study was conducted using electronic software in the management of a five station OSCE assessment with a cohort of first year undergraduate medical students delivered over two consecutive years (n=383) in one higher education institution in Ireland. Methods: All OSCE documentation was converted to electronic format. Assessors were trained in the use of the OSCE management software package and laptops were procured to facilitate electronic management of the OSCE assessment. Following the OSCE assessment, assessors were invited to evaluate the experience. Results: Electronic software facilitated the storage and analysis of overall group and individual results thereby offering considerable time savings. Submission of electronic forms was allowed only when fully completed thus removing the potential for missing data. Conclusions: Analysis of results highlights issues around inter-rater reliability and validity of measurement tools. Regression analysis, as a standard setting method, increases fairness of result calculations as compared to static cutoff scores.

Abstract Background: Compared with the number of candidate genes used for DNA microarray experiments, the number of available samples is extremely limited. As a result, overfitting of the data may occur during regression analyses. To solve this problem, various penalized regression models have been suggested. In general, the validity of a regression model should be verified using a validation data set, as opposed to the training data used to construct the model. However, at present there are no programs available to calculate statistical properties, including the precision, validity, and the statistical power of the Cox’s proportional hazards model regularized by various penalties; therefore, the properties of these models are not sufficiently clear. Methods: In this study, we created programs using the R language to calculate statistical properties of the Cox’s proportional hazards model, including the statistical power based on the prognostic index, and conducted simulation experiments under various conditions of DNA microarray expression data with survival time. Results: The results showed that the power of a validation set for penalized methods is greater than for stepwise methods in many cases, particularly when n < p. This tendency is most remarkable for the penalized methods including both the L1-norm and the L2-norm. Furthermore, we tested our programs using actual microarray gene expression data with survival time data to confirm their validity. Conclusions: Our simulation programs for the Cox’s proportional hazards model regularized by various penalties are very useful for planning DNA microarray studies or for evaluating the results of such studies

Abstract Aims: Fetal life and environment should be known in the management of the mother, fetus and newborn. Details; Fetal living and environment are very different from postnatal state, and a fetus lives and grows depending the transfer of oxygen and nourishing materials through the placenta, which attached the uterus, and supported by the umbilical cord circulation. Environment temperature is stabilized by maternal body temperature, humidity is nearly 100%, because the fetus is immersed in amniotic fluid. Fetal circulation differs from postnatal one due to placental circulation and no air respiration. Since the fetus grows floating in amniotic fluid, the fetus lives in the condition of no gravity, which supports fetal movements, and the blood circulation in the long umbilical cord vessels. The acoustical and visual fetal capacities were confirmed by sound and light stimulation, and fetal response with fetal movement and FHR acceleration. Conclusion: The fetal life and growth are useful in the fetal monitoring and postnatal preterm infant incubation

Abstract Background: Data mining has ability to extract useful knowledge that is hidden in huge data. Health care system is potential area to apply and take the advantage of data mining. The causes of child illnesses and admissions to hospitals that utilize the scarce resource in sub-Saharan region were easily preventable. Higher priority was given for prevention and control of these diseases at community level. However, for seriously ill children admissions should be facilitated in order to save the life of the child. Therefore, the purpose of this study was to apply data mining techniques on underfive children dataset in developing a model that support the discovery of the causes for under-five children admission to pediatric ward. Methodology: The six-step cross industry standard process for data mining model was applied. Decision tree and artificial neural network algorithms were tested for classification. Exploratory data analysis techniques, graphs and tabular formats for visualization and accuracy, true positive rate, false positive rate, Receiver Operating Characteristic curve and the idea of experts were used for evaluation of the model. Result: A total of 11,774 instances were used to construct the decision tree and artificial neural network. The decision tree algorithm J48 has higher accuracy (94.77%), weighted true positive rate (94.7%), weighted false positive rate (5.3%), weighted Receiver Operating Characteristic curve (0.99) and performs much faster than multilayer perceptron. According to the interesting rules in J48 presenting complaint of not taking any food, fluid or breast feeding (98.32%), was the top cause of under-five children admission to pediatric ward without any consideration of health information management system admission criteria. Conclusion: In conclusion, encouraging results were obtained in classification tasks, data mining technique was applicable on pediatric dataset in developing a model that support the discovery of the causes of under-five children admission to pediatric ward.

Abstract Thick blood smear examination is a necessary part for rapid screening of malaria parasite. Primary diagnosis of malaria by thick smear examination is cheap and highly sensitive, advocated by the World Health Organization (WHO). For the examination of thick blood smear, manpower and time can be reduced by using automated computational techniques. These techniques would facilitate such detection that are usually based on morphology and in few cases on analysis of colors. In this work, we propose a combined algorithm consisting of morphological operations and color based pixel discrimination technique to identify malaria parasites from thick smear images of Plasmodium vivax. Using morphological operation segmentation of cells from thick blood smear image is done and color based pixel discriminator distinguished malaria cells from segmented image. Evaluation of percentage of detection and False Positive Rate (FPR) shows that our proposed algorithm has significantly higher predictive rate, and lower FPR as compared to any existing methodology when tested on same input slides. Importantly the reported method does not need any training set and assumes unsupervised methodology. This makes the portability of the approach at various scales as discussed in the paper. The experiment has been carried out using JSB (Jaswant Singh Battacharya) stained thick blood smear images. It is assuming that our algorithm can identify malaria in less perfect dirty slides. This makes the algorithm more powerful and robust.