Health Journal Impact Factor & Information
Current impact factor: 2.10
Impact Factor Rankings
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ABSTRACT: Objective: To assess the knowledge, attitudes and practices regarding blood donation in the general population. Methods: A cross-sectional study was conducted and enrolled 416 people between 18 and 65 old years at random, living in three health zones in the city of Bukavu in eastern DRC. These subjects responded to a questionnaire on knowledge, attitudes and practices regarding blood donation. Results: Our sample consisted of 61.5% men, 70.9% of people from one level of education at the secondary level and 60% unemployed. According to the surveyed subjects blood was considered a fuel of the body in 44.6% and as a source of life in 44.1%. Sixty-one percent of the population did not know the practice of blood donation, this knowledge differed significantly (p <0.0001) according to the level of education also 67.1% of people knew that the blood had effects negative and 27.4% did not know where the blood bags were stored. Channels of knowledge about blood donation practices were associations of blood donors (30.9%), awareness campaigns (18.2%), school (17.3%) and media (15.5%), churches (10%), friends (8.1%). Approximately 85% of subjects who knew blood donation agreed with blood donation and blood transfusion but only 54.9% had donated blood in their lifetime, with a proportion of loyalty to blood donation 31.8%. In the population 59.4% were willing to donate blood. Motivation to donate blood most common (66%) was volunteerism while 19.1% were willing to donate blood for a family member and 12.6% willing to donate blood against money . The reasons for refusal to donate blood identified were fear of contracting diseases especially HIV, lack of information, religious beliefs, the sale of the collected blood by medical staff, fear of test result for HIV . Conclusion: Factors of refusal to donate blood were identified. Efforts and New strategies tailored to these factors must be developed and implemented to increase blood donation. Keywords blood donation, Bukavu, transfusion, blood donorHealth 10/2014; 6(18).
Health 09/2014; Vol.6.
Health 09/2014; 6(17):2303-2312. DOI:10.4236/health.2014.617265
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ABSTRACT: Abnormalities in the concentrations of metallic ions such as calcium and potassium can, in principle, lead to cardiac arrhythmias. Unbalance of these ions can alter the electrocardiogram (ECG) signal. Changes in the morphology of the ECG signal can occur due to changes in potassium concentration, and shortening or extension of this signal can occur due to calcium excess or deficiency, respectively. The diagnosis of these disorders can be complicated, making the modeling of such a system complex. In the present work an artificial neural network (ANN) is proposed as a model for pattern recognition of the ECG signal. The procedure can be, in principle, used to identify changes in the morphology of the ECG signal due to alterations in calcium and potassium concentrations. An arrhythmia database of a widely used experimental data was considered to simulate different ECG signals and also for training and validation of the methodology. The proposed approach can recognize premature ventricular contractions (PVC) arrhythmias, and tests were performed in a group of 47 individuals, showing significant quantitative results, on average, with 94% of confidence. The model was also able to detect ions changes and showed qualitative indications of what ion is affecting the ECG. These results indicate that the method can be efficiently applied to detect arrhythmias as well as to identify ions that may contribute to the development of cardiac arrhythmias. Accordingly, the actual approach might be used as an alternative tool for complex studies involving modifications in the morphology of the ECG signal associated with ionic changes.Health 05/2014; 6(66):1323-1332. DOI:10.4236/health.2014.611162
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ABSTRACT: Purpose: This study reports the reliability and validity analyses of the Audit on diabetes-dependent quality of life (ADDQoL) and EQ-5D in elderly Slovenian diabetic patients. Methods: A crosssectional study of elderly (age ≥ 65 years) non-insulin dependent diabetes mellitus type 2 (DMT2) patients was carried out. The ADDQoL and EQ-5D surveys were conducted between January and May, 2012. Statistical analysis was performed using IBM SPSS Statistics software, version 20.0. Results: After exclusion of non-eligible respondents, the final sample for the analysis was 261 cases (51% male), resulting in 52.2%of response rate. The mean age of the patients was 70.3 years (SD ± 4.1). The Cronbach’s alpha was 0.93 for ADDQoL and 0.73 for EQ-5D.There was no improvement in the alpha value if any item was deleted in all instruments. Missing value items ranged from 0.8% to 1.5% for EQ-5D, and from 0.8% to 59.1% (working life) in ADDQoL. Spearman’s correlation between the EQ-5D VAS score and ADDQoL weighted overall score resulted in weak correlations coefficient (r = 0.294; p < 0.001). Conclusions: The ADDQoL proved reliable and valid for assessing Health Related Quality of Life (HRQoL) among elderly Slovenian DMT2 patients. EQ-5D seemed to be too generic to describe limitations of DMT2 patients in detail. Using disease specific QoL instruments to learn about patient limitations was recommended. Comparison of ADDQoL results between various studies provided significant differences in the impact of diabetes.Health 03/2014; 6(8). DOI:10.4236/health.2014.68091
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