Showing 4 results for Zolala
S Daneshi, Aa Haghdoost, Mr Baneshi, F Zolala,
Volume 10, Issue 3 (Vol 10, No.3 2014)
Abstract
Background & Objectives: After an earthquake, casualty information is needed for planning and providing health care. However, developing countries do not have an efficient health information system even in normal conditions. In these countries, health information systems become worse in critical conditions. The aim of this study was to estimate the number of mortalities, limb amputations, and spinal cord injuries after the Bam earthquake.
Methods: In this cross sectional study, the network scale up method was used to estimate the number of casualties. We selected 80 residents of Bam and asked them whether they knew any one with spinal cord injury or limb amputation in three houses on the right and three houses on the left.
Results: The total estimated number of deaths was 54,041 in the earthquake. The number of people with spinal cord injury and limb amputation was 622 and 519, respectively.
Conclusion: For tertiary prevention measures and better resource allocation, an accurate health information system is needed. In the absence of such a system, there are limitations in using direct methods. It sounds that the network scale up method is an appropriate method for estimating such casualties.
A Raeisvandi, Aa Haghdoost, Mr Baneshi, S Garousi, S Farvahari, F Zolala,
Volume 10, Issue 4 (Vol 10, No 4 2015)
Abstract
Background and Objectives : Knowledge transition is an important issue in social epidemiology. Taking into account the importance of knowledge translation network among vulnerable young people in closed environments, this study was conducted to recognize and survey knowledge transition in school lessons. The study aimed at teenagers residing in orphanages in the city of Kerman, using social network analysis.
Methods: The study samples of this cross-sectional study were all teenagers aged 12-18 years old residing in orphanages. Data was collected via a checklist. In order to study the structural cohesion of social networks and the position of teenagers, density and centrality indices were calculated. Local structure of networks was studied using the triad census method. Finally, the effects of independent variables on indegree index were investigated using a mixed model.
Results : The mean density in knowledge transition was 0.34 (0.42 and 0.27 in girls and boys, respectively. (P=0.2)). Completely null and completely mutual triads were 17.1% and 11.2% in girls and 33.7% and 0.09% in boys, respectively. Indegree increased with an increase in age (P<0.001), the average of the scores in school exams (P=0.002), and studying non school materials (P=0.04).
Conclusion: Age, average score of school exams, and studying non school materials were important factors in indegree. In general, density of social network was rather low. The rate of knowledge transition was small. Therefore, activities are required to enhance knowledge sharing and transition.
S Abbaszadeh, Mr Baneshi, F Zolala, Y Jahani, H Sharifi,
Volume 13, Issue 3 (Vol.13, No.3, Atumn 2017)
Abstract
Background and Objectives: We may sometimes measure the joint effect of correlated independent variables on several dependent variablesThe present study aimed to evaluate the performance of multivariate analysis of variance (MANOVA) and structural equation modeling (SEM) on complex relationships between variables.
Methods: The present study evaluated the knowledge and attitude of 15-18 year-old individuals towards narcotics (glass, ecstasy). The effect of independent variables on two latent variables of knowledge and attitudes was studied using SEM and MANOVA modelingThe mean square error of methods were compared.
Results: The direction of associations was similar in both methods but their coefficients and p-values were different. only the effect of gender (P-value= 0.007) on knowledge in both methods was significant. Nevertheless, gender (P-value < 0.001) and marital status (P-value< 0.001) were significantly associated with attitude in both methods. The mean square error of multivariate analysis of variance and structural equation modeling was 0.98 and 0.002 respectively.
Conclusion: In the current studythe performance of SEM was better than MANOVA. Therefore, it is suggested that SEM to be used to study the multifactorial relationship between variables. In addition, only gender was effective on knowledge in both methods, while gender and marital status were effective on attitude in both methods.
S Mehdipour, F Zolala, M Hoseinnejad, R Zahedi, E Najafi, M , N Farrokhnia, M Fathi,
Volume 14, Issue 2 (Vol.14, No.2, 2018)
Abstract
Background and Objectives: Evidence suggests that underlying diseases increase the severity of influenza and lead to hospitalization or death. This study was conducted to determine the risk factors associated with hospitalization of patients in Afzalipour Hospital, Kerman, Iran during an outbreak of H1N1 influenza in December 2015.
Methods: In this case-control study, the case group comprised 85 patients who were hospitalized for influenza and the control group included 51 patients who had influenza symptoms and were discharged after required evaluations and check-up. The data were collected from both groups on a daily basis for two weeks. For data analysis, descriptive analysis, logistic regression analysis, Lasso Regression, and likelihood ratio were used. Analysis was performed using the Stata version 12 and R software.
Results: Among the variables examined, after removal of additional variables, 12 variables were introduced into the multivariate regression. The history of pulmonary disease and diabetes increased the odds of hospitalization following influenza by more than 11 (OR = 11.6, P. value = 0.003) and 9 times (OR = 9, P. value = 0.01), respectively.
Conclusion: Underlying disease and factors play a major role in exacerbating the disease. Therefore, the health system should take the necessary preventive measures when outbreaks occur.
