Conducting research on violence in Asian American communities: methodological issues

Conducting culturally competent research is a challenge as the United States becomes increasingly multicultural. When conducting research on violence in Asian American communities, researchers need to consider how culture, race, and ethnicity influence definitions of concepts, and methodological issues such as research designs, sampling, developing and translating instruments, ethical issues, recruiting research participants, supervising and training interviewers, and disseminating findings. Examples from the authors' research studies on community violence in the Khmer community, domestic violence in the Chinese American community, and dating violence in Asian American groups are extrapolated to highlight various themes. A commitment to a research program that collaborates with the community under study and cultural experts is vital at every stage of the research process.     

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Fathers in Family Therapy: A Survey of Family Therapists

Sixty family therapists were surveyed in an investigation of resistance by family members to family therapy. Consistent with other investigations, the father was viewed as the most resistant along a number of dimensions. Therapist behaviors that related to difficulties with the father, specifically, and to family therapy generally, were identified. The implication of these results and possible strategies to reduce the resistance of the father are discussed.     

WHICH SECTORS MAKE POOR COUNTRIES SO UNPRODUCTIVE?

Which sectors are most responsible for the low total factor productivities of developing countries? To answer this question we develop a new framework for sectoral development accounting. Applying this framework to the Penn World Table, we find that in equipment, construction, and food the sectoral TFP differences between developing countries and the United States are much larger than in the aggregate. However, in manufactured consumption the sectoral TFP differences are about equal to the aggregate TFP differences, and in services they are much smaller. We show that our level of disaggregation allows us to reconcile the results of existing studies of sectoral productivity differences, which have focused on noncomparable two‐sector decompositions of the aggregate data. We also show that our results help shed light on existing theories of aggregate TFP differences.     

Child abuse and neglect in Cambodian refugee families: characteristics and implications for practice

This study examines the characteristics and patterns of child maltreatment among Cambodian refugee families in Los Angeles and assesses the implications for child welfare practice with Cambodian refugee families. Data were extracted from 243 active Cambodian case files maintained by the Los Angeles County Department of Children and Family Services (LAC-DCFS). Some of the major findings include (1) Cambodian child maltreatment cases were most frequently reported to the LAC-DCFS among various Asian Pacific ethnic groups; (2) Cambodian refugee families were more likely to be charged with neglect, while their Asian Pacific counterparts were more likely charged with physical abuse; (3) the circumstances under which maltreatment occurred most frequently were parental substance abuse and mental illness; and (4) while fathers who maltreated their child were likely to use alcohol, mothers were also more likely to have a mental health problem such as depression. This study suggests the importance of collaboration between Child Protective Service agencies, substance abuse programs, traditional healers, mental health services, and other social service agencies for effective child abuse prevention and intervention efforts.     

Bayesian analysis for mixtures of discrete distributions with a non-parametric component

Bayesian finite mixture modelling is a flexible parametric modelling approach for classification and density fitting. Many areas of application require distinguishing a signal from a noise component. In practice, it is often difficult to justify a specific distribution for the signal component; therefore, the signal distribution is usually further modelled via a mixture of distributions. However, modelling the signal as a mixture of distributions is computationally non-trivial due to the difficulties in justifying the exact number of components to be used and due to the label switching problem. This paper proposes the use of a non-parametric distribution to model the signal component. We consider the case of discrete data and show how this new methodology leads to more accurate parameter estimation and smaller false non-discovery rate. Moreover, it does not incur the label switching problem. We show an application of the method to data generated by ChIP-sequencing experiments.