The Divide Between “Evidenced‐Based” Approaches and Practitioners of Traditional Theories of Family Therapy

Evidenced‐based approaches continue to grow in the field of family therapy. However, practicing family therapists do not always embrace these approaches. In this article, we explore factors contributing to practitioners' concerns with evidence‐based treatments and suggest a broader, more clinically palatable view of evidenced‐based treatment. We also suggest how family therapy researchers, practitioners, and educators might begin to close the researcher–clinician divide in the best interest of all concerned.     

The effects of direct experience on consumer product evaluation

The effects of different sales strategies on consumer product evaluation were investigated. It was expected that direct product experience could decrease economic product valuation. Experiments 1 and 2 studied the effects of product trials and money-back guarantees on consumer willingness to pay (WTP). It appeared that WTP was significantly lower after a product trial than with a money-back guarantee or normal sale. In Experiment 3 a structural equation model showed that product trials had a positive effect on attitude toward the product. Also, a negative effect on WTP was found when the effect was measured directly, but a positive effect when the effect was measured indirectly (through attitude).     

USING CONJOINT ANALYSIS TO PREDICT TRIAL AND REPEAT-PURCHASE PATTERNS OF NEW FREQUENTLY PURCHASED PRODUCTS*

A new approach is proposed to evaluate new-product opportunities. This approach uses the distribution of brand-purchase probability of the new product over a population of potential customers and the outputs from conjoint analysis. The heterogeneous distribution of brand-purchase probability is expressed by a beta binomial brand-choice model compounded with a negative binomial product-class purchase-incidence model. The resulting model provides a way to predict trial and repeat-purchase patterns of new-product concepts. The paper discusses the development of the model. It also discusses issues of measurement, estimation, testing, and implementation of the proposed approach based on actual empirical data.     

A NEW CLASS OF MODELS FOR THE DISCRIMINANT PROBLEM

Discriminant analysis is relevant to business decision making in a variety of contexts, such as when one decides to make or buy a specified component, fund a venture project, or hire a particular person. Potential applications in artificial intelligence, particularly in the area of pattern recognition, have further underscored the importance of the field. A recent innovation in discriminant analysis is provided by special linear programming (LP) models, which offer attractive alternatives to classical statistical approaches. The scope of application in which discriminant analysis can be advantageously employed is broadened by the flexibility to tailor parameters in the LP approaches to reflect diverse goals and by the power to explore the sensitivity of these parameters. In spite of the promise of the LP formulations, however, limitations to their effectiveness have been uncovered in certain settings. A recent advance involving a normalization construct removes some of the limitations but entails solving the LP model twice (to allow for different signs of a normalization constant) and does not yield equivalent solutions for different rotations of the problem data. This paper introduces a new model and a new class of normalizations that remedy both remaining limitations, making it possible to take advantage of the modeling capabilities of the LP formulations without the attendant shortcomings encountered by earlier investigations. Our development shows by empirical testing and illustrative analysis that the quality of solutions from LP discriminant approaches is more favorable (relative to the classical model) than previously supposed.     

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.