Young people and caregivers' perceptions of an intervention program for children who deliberately light fires

A significant number of children and adolescents engage in deliberate fire setting, beyond the scope of curiosity and experimentation. Interventions developed to respond to the needs of such fire setters generally involve educational and/or psychosocial approaches. Research evaluating the effectiveness of these interventions is dominated by outcome studies which rely on recidivism rates determined by either official records or parent reports. There has however, been no process evaluation studies published. This study presents a process analysis which aimed to identify the strengths and weaknesses of a Fire Awareness and Intervention Program in New Zealand, from the perspectives of program consumers. Qualitative research methods were employed, with data being derived from in-depth interviews with young people and their parents/caregivers. The analysis indicated that (a) the FAIP was generally regarded as a positive experience, (b) practitioners' qualities of empathy and understanding are important for developing rapport with the young people and their parents, (c) education-based intervention tailored to the young person's age and developmental level is important, (d) educational resources need to be updated and used flexibly to respond appropriately to the age and developmental level of the young person, and (e) inter-agency and intra-agency relationships need to be developed and maintained, with formal arrangements for reciprocal referral systems developed in order to respond to the needs of the clients. The resulting implications for service providers, along with future research are discussed.     

Applications and Implementation

We propose an alternative solution to the discriminant problem, one that requires little more than a minimum familiarity with linear programming. The approach shows promise for eliminating the complexities of conventional statistical approaches without sacrificing the essential power of existing methods.     

EVALUATING ALTERNATIVE LINEAR PROGRAMMING MODELS TO SOLVE THE TWO-GROUP DISCRIMINANT PROBLEM

The two-group discriminant problem has applications in many areas, for example, differentiating between good credit risks and poor ones, between promising new firms and those likely to fail, or between patients with strong prospects for recovery and those highly at risk. To expand our tools for dealing with such problems, we propose a class of nonpara-metric discriminant procedures based on linear programming (LP). Although these procedures have attracted considerable attention recently, only a limited number of computational studies have examined the relative merits of alternative formulations. In this paper we provide a detailed study of three contrasting formulations for the two-group problem. The experimental design provides a variety of test conditions involving both normal and nonnormal populations. Our results establish the LP model which seeks to minimize the sum of deviations beyond the two-group boundary as a promising alternative to more conventional linear discriminant techniques.     

A Postmodern Critique of Societal Discourses of Male Violence in Interpersonal Family Relationships: A Balancing Act for Social Work

In recent years, treatments of family violence have tended to be built around conventional discourses suggesting that men are major initiators in instances of interpersonal violence. Utilizing a postmodernist analysis, we assess societal discourses that continue to give life to this narrow conceptualization of interpersonal violence. We also examine literature suggesting that both men and women resort to violence to resolve relationship difficulties and suggest that a more holistic and inclusive approach to understanding interpersonal violence is critical for social workers committed to social justice and a balanced understanding of the contextual nature of human problems.     

Construction of a Markov Chain with Given Stationary Distribution

Given a rational, finite probability vector, a Markov chain is constructed having the given vector as its stationary distribution.     

An attribution model of public discrimination towards persons with mental illness

In this study, we build on previous work by developing and estimating a model of the relationships between causal attributions (e.g., controllability, responsibility), familiarity with mental illness, dangerousness, emotional responses (e.g., pity, anger, fear), and helping and rejecting responses. Using survey data containing responses to hypothetical vignettes, we examine these relationships in a sample of 518 community college students. Consistent with attribution theory, causal attributions affect beliefs about persons' responsibility for causing their condition, beliefs which in turn lead to affective reactions, resulting in rejecting responses such as avoidance, coercion, segregation, and withholding help. However, consistent with a danger appraisal hypothesis, the effects of perceptions of dangerousness on helping and rejecting responses are unmediated by responsibility beliefs. Much of the dangerousness effects operate by increasing fear, a particularly strong predictor of support for coercive treatment. The results from this study also suggest that familiarity with mental illness reduces discriminatory responses.