Adeleh Hashemi fard; Seyed Ehsan Saffari; Akram Ghasemi Hosseinabadi; Hamidreza Hashemifard; Majid Hashemifard
Volume 22, Issue 1 , March and April 2015, , Pages 84-92
Abstract
Background: Suicide is a huge problem in today's society. Due to the prevalence of this phenomenon especially amongyouth, this study was aimed atinvestigatingthe possible factors affecting on suicide attempts in patients of health centers of Sabzevar University of Medical Sciences.
Material and Methods: ...
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Background: Suicide is a huge problem in today's society. Due to the prevalence of this phenomenon especially amongyouth, this study was aimed atinvestigatingthe possible factors affecting on suicide attempts in patients of health centers of Sabzevar University of Medical Sciences.
Material and Methods: The present study was a descriptive-analytical and cross-sectional study. All patients who have madesuicide attemptsand referred to Vasei Hospital of Sabzevar University of Medical Sciences in 2013 were subjected as study population, and finally 242 cases among all registered cases in the Medical Records Unit of the hospital were entered to this study using the simple random sampling. SPSS 16 was used as well as the descriptive statistics and Chi-square test to analyze the data with %5 significance level.
Results: The suicide attempt cases in this study have the mean age of 25.77±9, with %45.6 of singles and %86.78 of urban. The most prevalent method in suicide attemptswas found to betheuse ofmedicine (%56.68) and the most important reason leading tosuicide attemptswas found to be the family problems (%38.02). Furthermore, the relationship between result, method, reason and the number of suicide attempts,varieswith demographic variables,obtained about%5 of significance level.
Conclusions: The results showed that lots of factors such as gender, age, marriage status, history of Psychosis, history of physical illness and history of suicide attemptsplay important roles in suicide attempt as a leading cuase of dead.
Ribah Adnan; Adeleh Hashemi fard; Seyyed Ehsan Saffari
Volume 20, Issue 4 , January and February 2014, , Pages 447-456
Abstract
Background: The number of hospitalization days is an important issue for the hospital managers, patients and their families. Regarding to the importance of this issue and few similar researches, this study aimed to model the number of hospitalization days for myocardial infarction (MI) patients admitted ...
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Background: The number of hospitalization days is an important issue for the hospital managers, patients and their families. Regarding to the importance of this issue and few similar researches, this study aimed to model the number of hospitalization days for myocardial infarction (MI) patients admitted in Vasei hospital of Sabzevar, and to investigate its effective factors.
Material and Methods: This descriptive-analytical study was performed to model the number of hospitalization days for myocardial infarction (MI) patients admitted in Vasei hospital of Sabzevar, in 2012. By using census method, 201 patients were entered to this study and the value of the length of hospitalization as the response variable, and the value of gender, age and residence location of the patients as the independent variables are considered. The data were analyzed using an advanced and new model, zero-truncated generalized poisson regression model, and SAS9.2 software.
Results: The results showed that the average length of hospitalization of MI patients was 4.876 days in Vasei hospital. Also, it was found that one year increase in age was related to one day increase in hospitalization of the MI patients. Moreover, the regression models predicted that the average length of hospitalization for female patients was less than male patients, and the average length of hospitalization for the urban residence patients was less than those of rural residence.
Conclusions: In this study, a suitable statistical method for analyzing and modeling of hospitalization days was obtained. Because of differences in hospitalization days in different units of hospitals, use of these advanced statistical models is proposed for another hospitals and cities.