An empirical study to measure the relationship between management style and conflict management

Leadership plays an important role among five main components of management. These days, many organizations try to resolve any existing conflicts through adapting an appropriate leadership strategy. During the past few years, there are increasing interests in examining the relationship between management style and conflict management. The proposed study of this paper performs an empirical study to find the relationship between relationship-oriented leadership style and solution-oriented strategy as well as between leadership style and conflict management. The proposed study distributed a questionnaire among 43 managers who were in different industries in west part of Iran. Most of the people who participated in our survey were male and they were between 25 to 30 years old. The study considers relationship between leadership style and conflict management, which includes the relationship between relationship-oriented and task-oriented leaderships with avoiding conflict management strategy, solution and control based conflict managements. The results confirmed that there is only a meaningful relationship between relationship-oriented leadership with solution-based conflict management. In other words, our survey indicates that when there is a conflict, management can handle the problem using his/her relationship and find appropriate solution to resolve any possible conflict

Skills, Capabilities, and Requirements of Hospital Managers: A Qualitative Study

Introduction: The hospital, as the most important organization in the delivery of health care services, requires effective and efficient management more than other organizations. Therefore, the skills and capabilities of hospital managers are important issues. The aim of this study was to determine the skills, capabilities, and requirements of hospital managers. Method: This qualitative study was conducted in Shiraz University of Medical Sciences, Shiraz, Iran, in 2015. The study population was composed of teaching hospital managers, senior managers, faculty members, and postgraduate students of Shiraz University of Medical Sciences. Sampling was conducted through purposive sampling method and continued until data saturation. In this study, interview and focus group discussion were used for data collection, and data analysis was performed using content analysis method. Results: The skills and capabilities of hospital manager were classified into 7 themes (communication, work experience, managerial knowledge, knowledge of the hospital, motivation and interest, systemic thinking and problem solving, individual characteristics and integrity) and 24 sub-themes. For the enhancement of these skills and capabilities, 2 themes (empowerment before and after obtaining the managerial post) and 8 sub-themes were identified. Conclusion: Hospital management requires specific skills and capabilities. Decision makers and policy makers in the health sector should select hospital manager based on these skills. Keywords: Capabilities, Manager, Hospital, Qualitative stud

Socio-demographic and Religious Factors Affecting Fertility Rate among Childbearing Women in Easter Iran: A Population-based Study

Background & aim: The reduction of fertility rate in the recent years in Iran may be due to the cultural and socioeconomic development in this country. The present study was conducted to investigate the relationship of fertility rate with demographic, socioeconomic, and religious factors among childbearing women in a city in Easter Iran. Methods: This cross-sectional study was conducted on 254 childbearing women in Torbat Heydariyeh, Iran, in 2016. The data were collected using a demographic questionnaire and scale of religiosity developed by Khodayari Fard (2000). Mann-Whitney U test, Spearman correlation, and general linear model were used to assess the relationships between variables Results: The mean number of children among women was 1.85±0.99. Fertility rate showed a direct relationship with age, age of spouse, and duration of marriage. There was an indirect relationship between age at marriage and fertility rate (P=0.001). Also, fertility rate was significantly correlated with education (P=0.001) and the mean total score of religiosity and its three dimensions (

The Comparison of Knee Joint Muscles Flexibility between Women with and without Radiographic Knee Osteoarthritis

Background: Approximately 60% of individuals above 50 years of age are affected by knee osteoarthritis (KOA). KOA is most commonly assessed through radiographic evaluation and classified using the Kellgren -Lawrence (KL) grading system with KL Grade 0 (KLG0) indicating a definite absence of radiographic KOA (RKOA) and KLG2 presenting a definite presence of RKOA. The current study compared knee joint muscle flexibility among three groups with KLG0, KLG2, and KLG3 RKOA. Methods: In this descriptive cross-sectional study, 94 KLG0, KLG2, and KLG3 knees on 57 women aged ≥40 years were examined. The flexibility of the quadriceps, hamstring, iliotibial band, adductor, and gastrocnemius muscles was compared. Results: Iliotibial band flexibility was lower in subjects with KLG3 RKOA than those with KLG2 (p 0.05). Conclusion: In patients with RKOA, the flexibility of the iliotibial band and quadriceps muscles may decrease as the disease progresses from KLG2 to KLG3. Moreover, quadriceps and iliotibial band flexibility may be lower in KLG3 compared to KLG0, with a lower likelihood of quadriceps flexibility in KLG2 compared to KLG0. These results suggest that quadriceps and iliotibial band stretching may be potentially important components of treatment

Factors Associated with The Incidence of Coronary Heart Disease in The Mashad: A Cohort Study

Coronary heart disease (CHD) is the leading cause of morbidity and mortality globally, and specifically in Iran. Accurate assessments of Coronary heart disease (CHD) incidence is very necessary for public health. In current study we aimed to investigate the incidence of CHD and importance of several classical, modifiable and un-modifiable risk factors for CHD among an urban population in eastern Iran after 6 years of follow-up. Methods The population of MASHAD cohort study were followed up for 6 years, every 3 years in two step by phone and who reported symptoms of CVD were asked to attend for a cardiac examination, to estimate the incidence of CHD with 95% confidence interval (95% CI) as well multiple logistic regression analysis was performed to assess the association of several baseline characteristics with incidence of CHD event. Evaluation of goodness-of-fit was done using ROC analysis. CHD cases divided into four different classes which include: stable angina, unstable angina pectoris, myocardial infarction and sudden cardiac death. Results In the six years\u27 follow-up of Mashhad study, the incidence rate of all CHD event in men and women in 100,000 people-years with 95% confidence intervals were 1920 (810-3030) and 1160 (730-1590), respectively. The areas under ROC curve (AUC), based on multivariate predictors of CHD outcome, was 0.7825. Conclusion Our findings indicated that the incidence rate of coronary heart diseases in MASHAD cohort study increases with age as well as our final model designed, was able to predict approximately 78% of CHD events in Iranian population

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. METHODS: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING: Bill & Melinda Gates Foundation

Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd