Nasser Behnampour, Ebrahim Hajizadeh, Shahriar Semnani, Farid Zayeri,
Volume 1, Issue 2 (10-2013)
Abstract
Background & objective:
One of the common purposes of medical research is Determination of effective factors on the occurrence of event. Due to the interaction of risk factors regression models, discriminant analysis and classification procedures used. Uses of these models require making the assumption which in the medical data isn’t usually established. Therefore, alternative methods must be used. According to diversification of risk factors for of esophageal cancer, the purpose of this article is the Introduction and application of classification and regression tree for determination of risk factor for esophageal cancer in Golestan province.
Methods:
Data of this article gathered from case-control study. Case group contain all confirmed cases of esophageal cancer that consist of 90 male and 60 female subjects in Golestan province during one year. Two control groups were considered for each case. Control groups were selected from family of patients and neighbors and matched for age, sex, ethnic and place of residence. Data was analyzed with classification and regression tree model and by using of R software. Gini criterion was used for selection of best splitting in each node and ROC surveyed accuracy of CRT model.
Results:
(ethnic factors) can be effective in esophageal cancer occurrences.
Results of Classification tree model showed that exposure to CT and X-ray dye (socio-environmental factors), unwashed hands after defecation, history of smoking (lifestyle factors) and family history of cancer
Conclusion:
models results` interpretation are two essential beneficiary of these models which can use in medical sciences.
Tree models don’t require the establishment of no default for making model and feasibility of tree
Alireza Heydari, Mohammad Javad Kabir, Ashrafi Babazadeh Gashti, Nahid Jafari, Mansoureh Lotfi, Mohammad Aryaei, Mohammad Reza Honarvar, Mohammad Ali Pourabasi, Maryam Iri,
Volume 2, Issue 2 (10-2014)
Abstract
Background & Objective: Job satisfaction Increases individual efficiency and commitment to the organization, ensuring the physical and mental health, life satisfaction and accelerate the learning of new skills on the job. The aim of this study was to determine the status of health professionals› satisfaction in the Golestan province.
Method: In this cross- sectional study, 1,275 health workers of Health centers in the Golestan province in the year 1391 were participated using the census method. Data was collected using Herzberg job satisfaction questionnaire. The data were analyzed using SPSS software, ANOVA and t-Test at the significant level of 0.05.
Results: Job satisfaction in terms of staff maintenance and support and given the potential and experience of individuals in granting liability were at dissatisfied level, In terms of corporate communications, career development, salary and benefits, challenges and job management, at relatively dissatisfied and from the aspect of social acceptance level was at relatively satisfied. Job satisfaction was significantly associated with work experience (P=0.049), ethnicity (P=0.009) and city of service location (P=0.001).
Conclusion: Due to poor job satisfaction levels, effective actions should be taken to improve organizational communication, career development, salary and benefits, social acceptance, staff maintenance and support, management, Job challenges, and granting responsibilities based on the ability and experience of the individuals.
Hamidollah Iri, Dr Ghahreman Mahmoudi, Dr Mohammad Ali Jahani Tiji,
Volume 5, Issue 2 (10-2017)
Abstract
Background & Objective: The fair distribution of medical specialists among the population of a country is one of the requirements for the public health. We aimed to investigating the distribution of medical specialists using Gini coefficient in all governmental hospitals in two medical universities of Golestan (15 hospitals) and Mazandaran (23 hospitals) provinces.
Methods: The present practical study was conducted using descriptive and analytical methods. The research data including the number of physicians, population and number of active beds in each city and province were obtained from the deputy of treatment of medical universities in each province. The Lorenz curve and the Gini coefficient were used to analyze the distribution of specialists using Excel software. T-test was used to compare the Gini coefficients between the two provinces. Multiple regression tests were performed using SPSS software version 16 to investigate the relationship between variables.
Results: The results showed that Gini coefficients on the basis of population in Mazandaran province were within optimum limit (less than 0.2). However, Gini coefficients on the basis of population in Golestan province were undesirable (more than 0.2) and there was also an inequality in the Gini coefficients based on the number of population between the two provinces of Golestan and Mazandaran (P=0.000, t=17.89).
Conclusion: According to the findings, the distribution of specialist physicians is desirable in Mazandaran province based on population. However, there was inequality in the distribution of specialist physicians in Golestan province. The accurate and fair estimation of the required human resources and the distribution on the basis of population and required indicators could lead to a reduction in the cost of treatment for families and better efficiency of health resources.
