Predicting Children’s Depressive Symptoms from Community and Individual Risk Factors

Community, demographic, familial, and personal risk factors of childhood depressive symptoms were examined from an ecological theoretical approach using hierarchical linear modeling. Individual-level data were collected from an ethnically diverse (73% African-American) community sample of 197 children and their parents; community-level data were obtained from the U.S. Census regarding rates of community poverty and unemployment in participants’ neighborhoods. Results indicated that high rates of community poverty and unemployment, children’s depressive attributional style, and low levels of self-perceived competence predict children’s depressive symptoms, even after accounting for demographic and familial risk factors, such as parental education and negative parenting behaviors. The effect of negative parenting behaviors on depressive symptoms was partially mediated by personal variables like children’s self-perceived competence. Recommendations for future research, intervention and prevention programs are discussed.

Surviving the suicides of significant others: a case study

Psychological pain has been reported to be major contributing factor for completed suicide, and classical suicidology based its wisdom on this construct. In this paper we report the case of a patient whose family experienced a high number of suicides apparently due to an escalation of psychological pain in the family members after the successive suicides. We also briefly discuss the problem of helping survivors after the suicide of loved one.     

Suicide among indigenous peoples: the usefulness of the Human Relations Area Files

The present note describes the resource for studying suicide in indigenous peoples provided by the Human Relations Area Files and describes three ways in which these files can illuminate suicidal behavior: testing theories of suicide, exploring the linguistics of suicide, and challenging myths about suicide.     

Models of E‐Government: Are They Correct? An Empirical Assessment

Research into e-government is relatively new. Nevertheless, much contemporary thinking and writing about e-government is driven by normative models that appeared less than a decade ago. The authors present empirical evidence from three surveys of local e-government in the United States to test whether these models are accurate or useful for understanding the actual development of e-government. They find that local e-government is mainly informational, with a few transactions but virtually no indication of the high-level functions predicted in the models. Thus, the models do not accurately describe or predict the development of e-government, at least among American local governments. These models, though intellectually interesting, are purely speculative, having been developed without linkage to the literature about information technology and government. The authors offer grounded observations about e-government that will useful to scholars and practitioners alike.