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Showing 5 results for Ghaderi
The Relationship Between Macroeconomic Variables And Health Indicators In United Nations Member States: 2002-2010
Mehdi Khakian, Javad Neshani Sadabad, Mohammad Hadian, Hosein Ghaderi, Malihe Ram, Yaser Jouyani,
Volume 9, Issue 4 (11-2015)
Abstract

Background and Aim: In a severely inflationary environment with unemployment, social problems increase and, therefore, high health care expenses are imposed on the society.

Materials and Methods: This was a correlational study. Panel data model and EVeiws 6 software were used in this study. The data were collected from the World Bank website. The required pre-tests, including F-Limer and Hauseman tests, were given to check the appropriateness of data and to determine a appropriate model. Following the pre-tests, the results were estimated in the form of a regression model.

Results: The results indicated that F-test and t-statistic were significant, and that R2 statistic was high. In the three models, R2 was 99%, 99% and 98%, respectively. Moreover, it can be said that employment is positively related with life expectancy, but negatively related with infant mortality and total fertility rate. Also, inflation is negatively related with life expectancy, but positively related with infant mortality, and total fertility rate. Finally, Gross Domestic Product (GDP) is negatively related with total fertility rate and life expectancy, but has no meaningful relationship with infant mortality (p = 0.31).

Conclusion: Employment, inflation and GDP are the variables that have the greatest impact on health indicators. however, life expectancy is more sensitive to explanatory variables.


The Effect of Socioeconomic Factors on Household Health Expenditures: Heckman Two-Step Method
Mahdi Shahraki, Simin Ghaderi,
Volume 13, Issue 2 (Jun & Jul 2019)
Abstract
Background and Aim: Due to the high level of out-of-pocket payments for health expenditures and the importance of household health expenditure management, this study aimed to investigate socioeconomic factors affecting Iranian urban households’ health expenditures.
Materials and Methods: This descriptive-analytic and applied study was conducted cross-sectionally at national level with microeconomic approach. The sample included 18809 urban households living in Iran's provinces in 2016; they were selected by three-stage sampling method. Data were collected by the household income-expenditure questionnaire of Statistical Center of Iran (SCI). The results were evaluated in Stata 14 software using Heckman two-step method.
Results: The results showed that socioeconomic factors such as increasing of income and insurance expenditures, having insurance, number of employed people, head's literacy, increasing of per capita expenditures of tobacco and education led to an increase in household health expenditures. Mother-headed households had lower health expenditures than others; and head of household’s age, household size, and the presence of elderly persons led to an increase in household health expenditures.
Conclusion: Household socio-economic factors not only affected the decision to enter health market but also influenced the purchase of goods and health services and inequality in health sector. Therefore, certain policies are essential to improve the socio-economic status towards reducing inequality in health sector; such a thing can be achieved through employment creation, growth of income, investment in education, and increase of insurance coverage.

Forecasting of Physicians Supply and Demand in Medical Sciences Universities of Iran
Mahdi Shahraki, Simin Ghaderi,
Volume 14, Issue 4 (Oct & Nov 2020)
Abstract
Background & Aim: Physicians as human capital and resources are one of the main components of health production. The imbalance of physician supply and demand affects the health and economics. Therefore, this study aimed to estimate and forecast the supply and demand of physician working in Iranian medical universities.
Materials and Methods: This a descriptive-analytical and applied study was conducted at national level for Iran during 1991-2017. The statistical population was physicians working in Iranian medical universities. ARIMA method was used to estimate and forecast physician supply and Vector Error Correction Models was used for physician demand. The data is annual time series that was extracted from the statistical yearbooks of the Statistical Center of Iran and the World Bank database. Eviews 10 software was used to estimate the models.
Results: The results showed that physician demand in Iran was affected by Gross Domestic Product, age structure and hospital beds, and according to the forecast of supply and demand of physicians, we will be faced to the physician shortage in the years 2018-2030.
Conclusion: In the coming years, Iran is facing with physician shortage. Therefore, it is recommended to adopt policies to increase physician capacity in medical universities and to increase strong incentives to retain physicians and prevent their migration.

Requirement Analysis and Design of an Alumni Relationship Management Solution for Medical Universities
Mohammadhiwa Abdekhoda, Taha Samad Soltani, Leial Ghaderi Nansa,
Volume 18, Issue 6 (2-2025)
Abstract
Background and Aim: Establishing dynamic relationships between graduates and current students should be a high priority for universities striving to progress in the rapidly changing and competitive market of third-generation universities. Due to the lack of effective communication with graduates in Iranian universities and the role of these systems in the technology ecosystem, the aim of this study is to analyze the needs of a graduate alumni management system and propose a conceptual model.
Materials and Methods: The research consisted of two main phases: needs analysis and process and software design. During the requirements engineering, as described in systems analysis and design references, a quick review was first conducted in selected databases regarding the capabilities and use cases of existing studies and the proposed features of innovative graduate alumni management systems. The extracted items from the rapid review were presented in a checklist. Then, functional requirements were extracted through interviews with 10 experts from the university’s educational deputy and faculty, using a two-round Delphi method. In the next stage, work processes were observed, and process owners were interviewed. UML diagrams were used to achieve a suitable description of a good system.
Results: In this study, the requirements were categorized into two main groups, comprising 37 functional and non-functional needs. The functional category included three significant subcategories: basic needs, social needs, and innovation needs. Basic needs encompassed the essentials required for the system’s fundamental operation. Social needs referred to the system’s ability to facilitate user interactions, while innovation needs involved new and creative features that could be added to the system. A software engineering specialist analyzed these functional needs and translated them into system use cases to be effectively incorporated into the system’s development.
Conclusion: The proposed conceptual model of the graduate alumni management system was analyzed and modeled based on user-centered requirements engineering. The proposed model provides a practical document for the effective implementation of a communication mechanism and active interaction between graduates, as well as current students, faculty members, and other staff in an innovation and entrepreneurship ecosystem.

Investigating the Association between Resilience and Demographic Information in Nurses Working in COVID-19 Special Wards
Afzal Shamsi, Musab Ghaderi, Sajjad Mirzaee,
Volume 19, Issue 3 (9-2025)
Abstract
Background and Aim: One of the risks of the nursing profession is psychosocial risks that affect their adaptation and, consequently, their resilience. This risk can have a deeper impact in certain situations such as the COVID-19 pandemic; Accordingly, the present study was conducted with the aim of “determining the relationship between resilience and demographic information in nurses working in COVID-19 special wards”.
Materials and Methods: The present study was a cross-sectional descriptive-analytical study and was conducted among 128 nurses working in the COVID-19 special wards of Ziaian Hospital in 2021. Participants were selected using convenience sampling based on inclusion criteria. Data were collected using demographic questionnaires and the Connor-Davidson Resilience Scale (CD-RISC). The scale’s score ranges from 0 to 100 (cutoff point 50), with scores above 50 indicating resilience. This questionnaire has been translated and validated by Iranian researchers. Its content validity was 0.82, and its reliability, based on Cronbach’s alpha, ranged from 0.74 to 0.9 for all subscales. The data were then analyzed using SPSS software with descriptive and inferential statistical tests. A P-value of less than 0.05 was considered statistically significant.
Results: The mean age of the participants was 35.59±7.22 years. The majority of nurses were male (61.7%) and married (89.8%). The mean resilience score among nurses was 37.25±5.68, which is considered very low given the cutoff point of 50. Results from linear regression showed that work experience (β=0.485, P=0.000), shift work (β=0.233, P=0.084), and employment type (β=0.189, P=0.021) had significant predictive power for overall resilience. This indicates that nurses with fixed shifts, more work experience, and permanent or contractual employment tend to have greater resilience. This analysis revealed that these variables, in total, predict 26% of the variance in the overall resilience variable.
Conclusion: Finally, the results of this study showed that the resilience of nurses working in COVID-19 special wards was low. Factors such as service history, work shift, and employment status were effective on their resilience. Accordingly, planning to improve the level of nurses’ resilience is necessary, especially in critical situations.

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