• Journal of Preventive Medicine and Public Health
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• v.54 no.4
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• pp.265-274
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• 2021

Objectives: Given the importance of social determinants of health in promoting the health of slum residents, this study was conducted with the aim of identifying the main dimensions and components of these determinants. Methods: This scoping review study was conducted according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). A comprehensive search was performed of PubMed, ProQuest, Scopus, and Web of Science for articles conducted from 2010 to the end of 2019. Studies were selected based on inclusion criteria, with a special focus on studies dealing with the social determinants of physical and mental health or illness. Results: Thirty-three articles were selected to extract information on the social determinants of health. After reviewing the articles, 7 main dimensions (housing, socioeconomic status of the family, nutrition, neighborhood characteristics, social support and social capital, occupational factors, and health behaviors) and 87 components were extracted as social determinants of health among slum dwellers. Conclusions: This framework could be used by planners, managers, and policy-makers when making decisions affecting the health of these settlements' residents due to the common characteristics of slums around the world, especially in developing countries.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.327-337
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• 2023

Objectives: Considering the importance of social determinants of health (SDHs) in promoting the health of residents of informal settlements and their diversity, abundance, and breadth, this study aimed to identify, measure, and rank SDHs for health promotion interventions targeting informal settlement residents in a metropolitan area in Iran. Methods: Using a hybrid method, this study was conducted in 3 phases from 2019 to 2020. SDHs were identified by reviewing studies and using the Delphi method. To examine the SDHs among informal settlement residents, a cross-sectional analysis was conducted using researcher-made questionnaires. Multilayer perceptron analysis using an artificial neural network was used to rank the SDHs by priority. Results: Of the 96 determinants identified in the first phase of the study, 43 were examined, and 15 were identified as high-priority SDHs for use in health-promotion interventions for informal settlement residents in the study area. They included individual health literacy, nutrition, occupational factors, housing-related factors, and access to public resources. Conclusions: Since identifying and addressing SDHs could improve health justice and mitigate the poor health status of settlement residents, ranking these determinants by priority using artificial intelligence will enable policymakers to improve the health of settlement residents through interventions targeting the most important SDHs.

• Journal of Preventive Medicine and Public Health
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• v.53 no.3
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• pp.189-197
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• 2020

Objectives: Our aim was to answer the following questions: (1) Can mental health variance be partitioned to individual and higher levels (e.g., neighborhood and district); (2) How much (as a percentage) do individual-level determinants explain the variability of mental health at the individual-level; and (3) How much do determinants at the neighborhood- or district-level explain the variability of mental health at the neighborhood- or district-level? Methods: We used raw data from the second round of the Urban Health Equity Assessment and Response Tool in Tehran (in 2012-2013, n=34 700 samples nested in 368 neighborhoods nested in 22 districts) and the results of the official report of Tehran's Center of Studies and Planning (in 2012-2013, n=22 districts). Multilevel linear regression models were used to answer the study questions. Results: Approximately 40% of Tehran residents provided responses suggestive of having mental health disorders (30-52%). According to estimates of residual variance, 7% of mental health variance was determined to be at the neighborhood-level and 93% at the individual-level. Approximately 21% of mental health variance at the individual-level and 49% of the remaining mental health variance at the neighborhood-level were determined by determinants at the individual-level and neighborhood-level, respectively. Conclusions: If we want to make the most effective decisions about the determinants of mental health, in addition to considering the therapeutic perspective, we should have a systemic or contextual view of the determinants of mental health.

• The Journal of Industrial Distribution & Business
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• v.9 no.9
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• pp.7-14
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• 2018

Purpose - Social welfare is a social insurance system that provides funds and services for all citizens to maximize their life quality. Its ultimate goal is to alleviate social contradictions. Therefore, this paper explores the determinants of social welfare in terms of macroeconomics. Research design, data, and methodology - Based on the vector error correction model, the annual time series from 1990 to 2017 will be used to conduct an empirical analysis. The real GDP, the real income, the inflation and the degree of openness will be treated as independent variables. The input of social welfare will be treated as a dependent variable. These variables will be used to perform the cointegration test and the vector error correction model to explore how the macroeconomic variables affect social welfare both in long run and short run. Result - Via the empirical analysis, it can be summarized that the real GDP, the real income and the degree of openness are the driving determinants to enlarge the social welfare. Conversely, the inflation is the obstructive determinant to reduce the social welfare. Conclusion - The positive and negative determinants of social welfare exist simultaneously, China's government should take macroeconomic regulation and control to balance them to enlarge social welfare.

• The Journal of Information Systems
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• v.29 no.3
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• pp.77-101
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• 2020

Purpose Internet only bank is one of the promising untact businesses which are rising in COVID-19 pandemic. Kakaobank and Kbank have been offering banking services since 2017 in Korea and WeBank and MYbank in China opened the services since 2015. It is necessary to examining determinants of customer loyalty beyond intention to use. The purpose of the present study is to analyze factors influencing customer loyalty and their determinants. A research model integrating the relationships among customer loyalty, service satisfaction, trust, and social influence, and their determinants was proposed. Design/methodology/approach Structural equation modelling for validating the research model was employed. 235 valid data were collected from users of Internet only bank in China. Nine latent variables grouped from 38 indicators were reliable and valid and nine hypotheses were tested by using SmartPLS. Findings All nine hypotheses were supported at significant levels of 0.001 and 0.01. Trust, service satisfaction, and social influence had influenced on customer loyalty. Trust not only affected customer loyalty directly, but also had influence on it indirectly through service satisfaction. Empathy and convenience are determinants of trust. Perceived expertise and dispositions believing acquaints had a positive influence on social influence, whereas users' anxiety for technology or change had a negative influence on social influence. Implications for academics and practitioners were suggested.

• Korean Management Science Review
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• v.28 no.3
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• pp.95-112
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• 2011

The Internet has generated a number of online review sites where dissatisfied consumers can easily articulate their opinions and comments on products or services. Little attention, however, has been directed to investigating the relationship between negative electronic word-of-mouth (eWOM) and its critical determinants that affect consumers' purchasing behaviors. This study attempts to explore the influence of the key determinants of consumers' negative eWOM behaviors, including their social relationships online. The results show that tie strength is positively associated with the proposed determinants, such as information credibility, external search efforts, and product involvement. Further, we find that perceived risk plays a mediating role in the relationship between consumers' intention to spread eWOM and its key determinants.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.311-316
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• 2016

Breast cancer is one of the most common causes of cancer mortality in Iran. Social determinants of health are among the key factors affecting the pathogenesis of diseases. This cross-sectional study aimed to determine the social determinants of breast cancer survival time with parametric and semi-parametric regression models. It was conducted on male and female patients diagnosed with breast cancer presenting to the Cancer Research Center of Shohada-E-Tajrish Hospital from 2006 to 2010. The Cox proportional hazard model and parametric models including the Weibull, log normal and log-logistic models were applied to determine the social determinants of survival time of breast cancer patients. The Akaike information criterion (AIC) was used to assess the best fit. Statistical analysis was performed with STATA (version 11) software. This study was performed on 797 breast cancer patients, aged 25-93 years with a mean age of 54.7 (${\pm}11.9$) years. In both semi-parametric and parametric models, the three-year survival was related to level of education and municipal district of residence (P<0.05). The AIC suggested that log normal distribution was the best fit for the three-year survival time of breast cancer patients. Social determinants of health such as level of education and municipal district of residence affect the survival of breast cancer cases. Future studies must focus on the effect of childhood social class on the survival times of cancers, which have hitherto only been paid limited attention.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.1
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• pp.34-52
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• 2018

The aim of this study is to identify economic geographical determinants that affect the sustainability of the social economy. The sustainability of the social economy means the sustainability of the pursuit of social value as well as the sustainability of business operation. This study is aiming to economic geographical determinants as factors affecting sustainability of the social economy and extracted measurement index through examination on the theory and case study. As a result, 10 items in two areas(the sustainability of the pursuit of social value, the sustainability of business operation) had been deducted as the measurement index of which sustainability of the social economy. In addition, 20 items in four areas(local networks, intermediary organizations, local community culture and public roles) had been deducted as economic geographical determinants. Multiple regression analysis through 193 firm surveys suggests that 'local networks', 'intermediary organizations', and 'public roles' have an positive impact on sustainability. This result implies a need for policies to create an economic geography ecosystem of social economy.

• Child Health Nursing Research
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• v.13 no.1
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• pp.13-20
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• 2007

Purpose: This investigation examined a model to predict body mass index in order to prevent later development of obesity among adolescents. The hypothesized model was developed based on the principle of Social Cognitive Theory that social influences predict perceptions of cognition as well as behavior. Method: The 5,770 adolescents, aged 14-18 who participated in this study came from 11 separate school districts in Busan and Kyungnam province of South Korea. The adolescent surveys were administered in a group setting at the participating school. Of the 5770 surveys, adolescents with more than 10 percent missing data in the entire survey were excluded. The final sample contained 4,527 cases. The adolescents were included 2,250 (49.7%) males and 2,277 (50.3%) females. Data was analyzed Pearson correlation coefficients using SPSS 12 program and structural equation model (SEM) using Maximum Likelihood estimation was employed using Amos 5.0. Results: Social support directly affects cognitive determinants. Cognitive determinants directly affect behavior determinants which directly affect BMI. Cognitive and behavioral factors mediated the relationship between social support and BMI (GFI= 0.984, CFI= 0.974, RMSEA=0.031). Conclusion: Social levels should be supportive to help adolescents have healthier behaviors. This support can be accomplished by providing frequent support to establish positive cognitive factors as the foundation of the solution to prevent overweight and obesity.

• Journal of Preventive Medicine and Public Health
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• v.55 no.2
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• pp.144-152
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• 2022

Objectives: This study aimed to identify the social and policy determinants of coronavirus disease 2019 (COVID-19) infection across 23 countries. Methods: COVID-19 indicators (incidence, mortality, and fatality) for each country were calculated by direct and indirect standardization. Multivariable regression analyses were used to identify the social and policy determinants of COVID-19 infection. Results: A higher number of doctors per population was related to lower incidence, mortality, and fatality rates of COVID-19 in 23 countries (β=-0.672, -0.445, and -0.564, respectively). The number of nurses/midwives per population was associated with lower mortality and fatality rates of COVID-19 in 23 countries (β=-0.215 and -0.372, respectively). Strengthening of policy restriction indicators, such as restrictions of public gatherings, was related to lower COVID-19 incidence (β=-0.423). A national Bacillus Calmette-Guérin vaccination policy conducted among special groups or in the past was associated with a higher incidence of COVID-19 in 23 countries (β=0.341). The proportion of the elderly population (aged over 70 years) was related to higher mortality and fatality rates (β=0.209 and 0.350, respectively), and income support was associated with mortality and fatality rates (β=-0.362 and -0.449, respectively). Conclusions: These findings do not imply causality because this was a country-based correlation study. However, COVID-19 transmission can be influenced by social and policy determinants such as integrated health systems and policy responses to COVID-19. Various social and policy determinants should be considered when planning responses to COVID-19.