Responding to teen dating violence: Perspectives from mothers who have been abused and seeking services in domestic violence shelters

ABSTRACT

Teen dating violence (TDV) is a significant public health problem, but we know little about how mothers who have been abused respond to TDV. This article analyzes qualitative data from three focus groups conducted with 17 mothers who had experienced abuse. Mothers responded to four hypothetical scenarios of their child reporting TDV to them. Mothers reported that their approach to children’s reports of TDV would entail engaging in varying levels of authoritarianism, considering the gender of the child, and exercising caution in their responses. In response to the scenarios, mothers stated that they would ask questions, educate their teens, contact the perpetrator and/or parents, share their own experiences, and call for outside help. The study’s findings may assist prevention educators working with mothers who experienced abuse in responding to their children’s disclosures of incidents of TDV.     

A note on efficient simulation of multidimensional spatial autoregressive processes

In applications of spatial statistics, it is necessary to compute the product of some matrix W of spatial weights and a vector y of observations. The weighting matrix often needs to be adapted to the specific problems, such that the computation of Wy cannot necessarily be done with available R-packages. Hence, this article suggests one possibility treating such issues. The proposed technique avoids the computation of the matrix product by calculating each entry of Wy separately. Initially, a specific spatial autoregressive process is introduced. The performance of the proposed program is briefly compared to a basic program using the matrix multiplication.     

Developing an undue influence screening tool for Adult Protective Services

The study purpose was to develop and pilot an undue influence screening tool for California’s Adult Protective Services (APS) personnel based on the definition of undue influence enacted into California law January 1, 2014. Methods included four focus groups with APS providers (n = 33), piloting the preliminary tool by APS personnel (n = 15), and interviews with four elder abuse experts and two APS administrators. Social service literature—including existing undue influence models—was reviewed, as were existing screening and assessment tools. Using the information from these various sources, the California Undue Influence Screening Tool (CUIST) was developed. It can be applied to APS cases and potentially adapted for use by other professionals and for use in other states. Implementation of the tool into APS practice, policy, procedures, and training of personnel will depend on the initiative of APS management. Future work will need to address the reliability and validity of CUIST.     

Factors That May Influence Parent Treatment Decision Making for Young Children with Autism Spectrum Disorder

ABSTRACT

The number of interventions available for children with autism spectrum disorder (ASD) has expanded greatly in recent years, although relatively little is known about the factors that influence family caregivers as they make treatment decisions for their children. This study involved a statewide survey of parents of young children with ASD to examine the relative weights of the factors that influenced their treatment decisions. Results suggested that caregivers rely on their own intuition for much decision making, although selected professionals are also influential. Implications for professionals working with children with ASD and their families are discussed.     

Singularity and Autoregressive Disturbances in Linear Logit Models

The implications of including autoregressive disturbances in linear logit models of demand systems are explored. It is argued that the normality assumption of the error terms is more appropriate in the linear logit model than in a share equation model with additive disturbances (commonly found in the literature). Autoregressive disturbances and their implications for model estimation are discussed in that context. Both theoretical arguments and empirical evidence are presented in favor of the logit specification given the presence of serial correlation.