As China’s economy is rapidly changing from a planned to a capitalist economy, many families find themselves financially struggling. In some cases, conflicting values and attitudes may contribute to mental health challenges such as depression that would lead to further feelings of helplessness and immobilization. Using a random sample of 1006 low-income households from Pudong District of Shanghai, China, this study aims to examine the relationships between household assets, beliefs about government as the primary way to improve economic circumstances and self-reported depressive symptoms. In addition, this study investigates the mediation effects of beliefs that government is the best change agent for improved life circumstances on the relationship between household assets and depression. We found those who indicated that government was the main means for attaining a better life had significantly higher depression levels whereas higher numbers of household assets were associated with lower depression levels. We also found that viewing government as the most important change agent only partially mediated the relationship between household assets and depression (p?<?.001). Findings from this study support anti-poverty policies and social work related practice initiatives aimed at assisting low income families in China, in particular the need to address psychological as well as economic needs.
Many research papers calculate corporate social performance (CSP) with the net score method, i.e., by subtracting the number of concerns from the number of strengths. Although widely adopted, this method implies, perhaps mistakenly, that each indicator is of equal importance and that however serious the social misconduct a firm may have engaged in, it can be completely offset by some positive social action. The method also implies that a given firm that has done both a lot of harm and a lot of good will have CSP similar to that of another firm that has done little harm and little good. In this study, however, we question the appropriateness of the net score method in terms of its ability to truly reflect CSP and truly identify the real effects of CSP on various characteristics. We therefore propose a data envelopment analysis-based methodology that adopts the assurance region approach for evaluating CSP, through which various CSP indicators are converted into a single composite measure of CSP. Our findings show that our proposed methodology consistently performs better than the net score method in evaluating CSP.
In human mortality modelling, if a population consists of several subpopulations it can be desirable to model their mortality rates simultaneously while taking into account the heterogeneity among them. The mortality forecasting methods tend to result in divergent forecasts for subpopulations when independence is assumed. However, under closely related social, economic and biological backgrounds, mortality patterns of these subpopulations are expected to be non-divergent in the future. In this article, we propose a new method for coherent modelling and forecasting of mortality rates for multiple subpopulations, in the sense of nondivergent life expectancy among subpopulations. The mortality rates of subpopulations are treated as multilevel functional data and a weighted multilevel functional principal component (wMFPCA) approach is proposed to model and forecast them. The proposed model is applied to sex-specific data for nine developed countries, and the results show that, in terms of overall forecasting accuracy, the model outperforms the independent model and the Product-Ratio model as well as the unweighted multilevel functional principal component approach. 相似文献
Lifetime Data Analysis - This work was motivated by observational studies in pregnancy with spontaneous abortion (SAB) as outcome. Clearly some women experience the SAB event but the rest do not.... 相似文献