What clients of couple therapy model developers and their former students say about change, part II: model-independent common factors and an integrative framework

Proponents of the common factors movement in marriage and family therapy (MFT) suggest that, rather than specific models of therapy, elements common across models of therapy and common to the process of therapy itself are responsible for therapeutic change. This article-the second of two companion articles-reports on a study designed to further investigate common factors in couple therapy. We used grounded theory techniques to analyze data from interviews with MFT model developers Dr. Susan M. Johnson, Dr. Frank M. Dattilio, Dr. Richard C. Schwartz, former students of Dr. Johnson and Dr. Schwartz, and each of their clients who had been successful in couple therapy. This article reports model-independent variables, that is, general aspects of therapy that are not directly related to the therapist's model. Model-independent categories include client variables, therapist variables, the therapeutic alliance, therapeutic process, and expectancy and motivational factors, each with several subcategories. We also present a conceptual framework that outlines how model-dependent and model-independent common factors may interact to produce change. We discuss our findings and proposed framework in relation to the current common factors literature in psychology and MFT. We also discuss clinical, training, and research implications.     

The life course perspective on drug use: a conceptual framework for understanding drug use trajectories

This article discusses the life course perspective on drug use, including conceptual and analytic issues involved in developing the life course framework to explain how drug use trajectories develop during an individual's lifetime and how this knowledge can guide new research and approaches to management of drug dependence. Central concepts include trajectories marked by transitions and social capital and turning points influencing changes. The life course perspective offers an organizing framework for classifying varying drug use trajectories, identifying critical events and factors contributing to the persistence or change in drug use, analytically ordering events that occur during the life span, and determining contributory relationships.     

Can we immunize children against violence?

Psychiatric nurses should support best practices to prevent youth violence. The magnitude and significance of youth violence gives us both social and moral mandates to proceed. Health care professionals have made giant strides in sparing our children from the ravages of childhood diseases. Let us try to do the same by preventing the development of violent behaviors.     

Camera-Related Behaviors during Video Recorded Medical Interactions

Video recording provides an objective record of the content of medical interactions. However, there is concern that cameras may be reactive measurement devices that alter what normally transpires during interactions. This study addressed potential reactivity of cameras in medical interactions. Interactions between 45 patients and 14 medical oncologists were video recorded and coded for camera-related behaviors. Eleven of 45 patients performed none of the behaviors. Among the other patients, camera-related behaviors were infrequent and, on average, constituted about 0.1% (one-tenth of one percent) of total interaction time. Behaviors occurred most often in very early stages of interactions, and when physicians were absent from the room. Seven physicians showed camera-related behaviors, comprising less than 0.1% of the time they were in the interaction. Results suggest video recording can provide nonreactive means of studying medical interactions.

Robust signed-rank estimation and variable selection for semi-parametric additive partial linear models

A fully nonparametric model may not perform well or when the researcher wants to use a parametric model but the functional form with respect to a subset of the regressors or the density of the errors is not known. This becomes even more challenging when the data contain gross outliers or unusual observations. However, in practice the true covariates are not known in advance, nor is the smoothness of the functional form. A robust model selection approach through which we can choose the relevant covariates components and estimate the smoothing function may represent an appealing tool to the solution. A weighted signed-rank estimation and variable selection under the adaptive lasso for semi-parametric partial additive models is considered in this paper. B-spline is used to estimate the unknown additive nonparametric function. It is shown that despite using B-spline to estimate the unknown additive nonparametric function, the proposed estimator has an oracle property. The robustness of the weighted signed-rank approach for data with heavy-tail, contaminated errors, and data containing high-leverage points are validated via finite sample simulations. A practical application to an economic study is provided using an updated Canadian household gasoline consumption data.