جستجوی مقالات مرتبط با کلیدواژه « داده های ترکیبی » در نشریات گروه « پزشکی »

Social capital has an effective role in promoting the mental health of people in the community by providing emotional and psychological support. Accordingly, the main purpose of this study is to investigate the effect of social capital on mental health in provinces of Iran.

This was a descriptive-analytical and applied study. It investigated the long-term relationship between mental health index, social capital, per capita income, unemployment, education and urbanization from 2006 to 2019 using the panel data of Iran's provinces. The data used were collected from Central Bank and Statistics Center of Iran. For this purpose, based on Putnam and Colman's approach to measuring social capital, 3 levels of participation, trust and unity have been considered. In order to combine the indicators used in these levels, factor analysis method has been used. Model estimation was also conducted using the Generalized Method of Moment (GMM) and data analysis was performed using Eviews 9  and Stata 12 software.

Based on the results obtained from the model estimation, increasing social capital will improve the mental health index in the provinces of the country in the long term. 1 percent increase in social capital in the long run, reduces the suicide rate in the provinces of the country by 0.27 percent. Based on other results, in the long term, per capita income and education have a positive and significant effect and the unemployment rate has a negative and significant effect on mental health in the provinces of the country.

Based on the findings of this study, authors can conclude that the greater amount of social capital in the provinces of the country leads to higher mental health.

Uncompensated care causes many financial problems for hospitals. It would be helpful to use any interventions to reduce uncompensated costs. This study aimed to investigate factors affecting Iran University of Medical Sciences (IUMS) hospitalschr('39') uncompensated costs during 2014-2018.

The present study was an analytical and applied research with monthly data from 2014 to 2018. The study population included all hospitals affiliated to Iran University of Medical Sciences, and the tool was an Excel data collection form. Data analysis was performed using EViews 10 software. Model estimation was carried out using the panelchr('39')s econometric approach.

Uncompensated costs during the study period averaged 25 million dollars. The largest share of uncompensated costs belonged to insurance deductions, debts of poor and foreign patients. The results showed a significant positive relationship between the variables of foreign patients, outpatients, hospital beds, bed occupancy rate, and length of stay with uncompensated costs. There was no significant relationship among the variables of number of surgeries, number of hospitalized patients, and uncompensated costs. Moreover, the bed rotation coefficient variable did not affect uncompensated costs, and the hospital beds had the most positive effect on uncompensated costs, followed by the variables of the length of stay and number of foreign patients.

The results of the study showed the high level of uncompensated costs in IUMS hospitals. Due to uncompensated costs’ effect on hospital revenues, it seems that identifying the causes of deductions and subsequently ways to reduce insurance deductions as well as expanding insurance coverage to mitigate non-recoverable costs can be effective.