Working Experientially and Somatically with Couples

SUMMARY

Working experientially and somatically with couples is a powerful method of accessing, exploring, and transforming both intra-psychic issues and interactional patterns. In this article, a number of methods of working experientially will be described, along with their underlying rationale. Basic assumptions about the nature of couple's difficulties and the role of the therapist also will be explored along with an integrated approach to assessment that provides a solid basis for these dramatic interventions.     

Managers' Implicit Assumptions About Personnel

ABSTRACT— Effective managers recognize both positive and negative changes in employee performance and take appropriate remedial action when required. Managers' assumptions about the rigidity or malleability of personal attributes (e.g., ability and personality) affect their performance of these critical personnel management tasks. To the extent that managers assume that personal attributes are fixed traits that are largely stable over time, they tend to inadequately recognize actual changes in employee performance and are disinclined to coach employees regarding how to improve their performance. However, a growth-mindset intervention can lead managers to relinquish their fixed mindset and subsequently provide more accurate performance appraisals and helpful employee coaching. Implications for performance evaluation procedures and avenues for future research are outlined.     

Fostering a “Group Ethos”: Truth or Dare!

A group ethos permeates the two Special Issues of Group dedicated to the future of group psychotherapy in the 21st century. This ethos is elaborated through a parable, an integration of authors' conclusions, and a brief exploration of the myths and basic assumptions about group leadership and followership that characterized the 20th century. A new basic assumption is proposed for the 21st. BaC suggests that members are drawn to groups for the unconscious collaboration necessary to discover something between them, as yet untold—something that may hold the key to their own fates and to the human condition.     

Tableau reductions: Towards an optimal decision procedure for the modal necessity

We present a new prefixed tableau system $\mathsf{TK}$ for verification of validity in modal logic $\mathsf{K}$. The system $\mathsf{TK}$ is deterministic, it uniquely generates exactly one proof tree for each clausal representation of formulas, and, moreover, it uses some syntactic reductions of prefixes. $\mathsf{TK}$ is defined in the original methodology of tableau systems, without any external technique such as backtracking, backjumping, etc. Since all the necessary bookkeeping is built into the rules, the system is not only a basis for a validity algorithm, but is itself a decision procedure. We present also a deterministic tableau decision procedure which is an extension of $\mathsf{TK}$ and can be used for the global assumptions problem.     

The Role of Independence and Stationarity in Probabilistic Models of Binary Choice

After more then 50 years of probabilistic choice modeling in economics, marketing, political science, psychology, and related disciplines, theoretical and computational advances give scholars access to a sophisticated array of modeling and inference resources. We review some important, but perhaps often overlooked, properties of major classes of probabilistic choice models. For within‐respondent applications, we discuss which models require repeated choices by an individual to be independent and response probabilities to be stationary. We show how some model classes, but not others, are invariant over variable preferences, variable utilities, or variable choice probabilities. These models, but not others, accommodate pooling of responses or averaging of choice proportions within participant when underlying parameters vary across observations. These, but not others, permit pooling/averaging across respondents in the presence of individual differences. We also review the role of independence and stationarity in statistical inference, including for probabilistic choice models that, themselves, do not require those properties. Copyright © 2017 John Wiley & Sons, Ltd.     

Do traumatic events influence cognitive schemata?

Within the field of crisis psychology empirical research on the subject whether cognitive schemata are influenced by victimization, and whether possible changes in cognitive schemata are related to post-traumatic stress disorder (PTSD) is somewhat sparse. In the present study cognitive processing of 602 parents, who had lost an infant, were examined. Among other things results showed a significant relationship between level of cognitive processing and symptoms of PTSD. When items selected to reflect fundamental assumptions about the self and the world were assessed, there were only few differences between parents who had lost an infant, and the control group. Furthermore, there were numerous significant relations between items selected to reflect fundamental assumptions and symptoms of PTSD. The results are discussed in relation to central theories within the cognitive area of crisis psychology and recommendations for future research are offered.     

Trust and the collection,selection, analysis and interpretation of data: A scientist’s view

Trust is a critical component of research: trust in the work of co-workers and colleagues within the scientific community; trust in the work of research scientists by the non-research community. A wide range of factors, including internally and externally generated pressures and practical and personal limitations, affect the research process. The extent to which these factors are understood and appreciated influence the development of trust in scientific research findings.     

Traiter ses données proprement : vers un meilleur usage du data cleaning

Data cleaning has long been shown to be an essential step in data analysis but its application is not systematic and varies between researchers. The aim of the present article is to study the effect of the different elements of data cleaning and to give recommendations. The steps considered are normality, outliers and missing values. Firstly, we advise a close examination of the data and its normality with a view to transformation. Secondly, we look at outliers and their treatment (trimming and winsorizing). Lastly, we turn our attention to missing values and how to deal with them depending on their randomness. We also cover the importance of visualizing data before analysis. Finally, we illustrate the effect of these data cleaning practices on a real data set. We show that data cleaning can lead to a significant result becoming non-significant and therefore demonstrate the importance of these steps before starting data analysis.