"Good enough stories": helping couples invest in one another's growth

This article utilizes key constructs of the narrative metaphor: that stories organize, structure, and give meaning to events in our lives. When stories are used as a way to understand the lives of couples, they have the potential for enhancing individual and relational growth. It is proposed that knowing both our own and our partner's story and development goals increases the likelihood of making an investment in self/other and relational growth. It is further suggested that helping couples develop narratives with a sense of "We" promotes a more generative perspective. These ideas were developed in a small qualitative pilot study with long-married, middle-class, heterosexual couples, which suggested that the synthesis of each partner's life story into a couple story promoted individual and relational development. Implications for therapeutic work with couples are presented as well as specific recommendations for ways to utilize the life story approach as an aspect of treatment. It is intended to assist clinicians and teachers in translating narrative ideas into therapeutic work with couples.     

Beta-MPT: Multinomial processing tree models for addressing individual differences

Traditionally, multinomial processing tree (MPT) models are applied to groups of homogeneous participants, where all participants within a group are assumed to have identical MPT model parameter values. This assumption is unreasonable when MPT models are used for clinical assessment, and it often may be suspect for applications to ordinary psychological experiments. One method for dealing with parameter variability is to incorporate random effects assumptions into a model. This is achieved by assuming that participants’ parameters are drawn independently from some specified multivariate hyperdistribution. In this paper we explore the assumption that the hyperdistribution consists of independent beta distributions, one for each MPT model parameter. These beta-MPT models are ‘hierarchical models’, and their statistical inference is different from the usual approaches based on data aggregated over participants. The paper provides both classical (frequentist) and hierarchical Bayesian approaches to statistical inference for beta-MPT models. In simple cases the likelihood function can be obtained analytically; however, for more complex cases, Markov Chain Monte Carlo algorithms are constructed to assist both approaches to inference. Examples based on clinical assessment studies are provided to demonstrate the advantages of hierarchical MPT models over aggregate analysis in the presence of individual differences.     

A Signal Detection Model for Multiple-Choice Exams

A model for multiple-choice exams is developed from a signal-detection perspective. A correct alternative in a multiple-choice exam can be viewed as being a signal embedded in noise (incorrect alternatives). Examinees are assumed to have perceptions of the plausibility of each alternative, and the decision process is to choose the most plausible alternative. It is also assumed that each examinee either knows or does not know each item. These assumptions together lead to a signal detection choice model for multiple-choice exams. The model can be viewed, statistically, as a mixture extension, with random mixing, of the traditional choice model, or similarly, as a grade-of-membership extension. A version of the model with extreme value distributions is developed, in which case the model simplifies to a mixture multinomial logit model with random mixing. The approach is shown to offer measures of item discrimination and difficulty, along with information about the relative plausibility of each of the alternatives. The model, parameters, and measures derived from the parameters are compared to those obtained with several commonly used item response theory models. An application of the model to an educational data set is presented.     

Gender-related inequalities in the division of family work in close relationships: A social psychological perspective

We offer a social psychological perspective on gender-related inequalities in close relationships and integrate two lines of research that have focused on the intrapersonal perceptions and interpersonal consequences respectively of the gendered division of labour. We start with a brief summary of research on gender-related inequalities in the division of labour and discuss prior explanations and paradigms. We then address the extent to which spouses consider the division of labour as fair and the factors that contribute to perceptions of (un)fairness. Central to our argument is the distributive justice framework (<citeref rid="b76">Major, 1987</citeref>, <citeref rid="b77">1993</citeref>; <citeref rid="b113">Thompson, 1991</citeref>) which claims that fairness judgements are affected by people's wants and values, comparison standards, and justifications. In the following section, we address the question of whether dissatisfaction over the division of labour causes relationship conflict and how couples manage these conflicts. The main argument is that conflict over the division of labour generally comprises an asymmetrical conflict structure (with wives as complainants and husbands as defenders of the status quo), which elicits asymmetrical conflict interaction patterns (i.e., demand/withdraw interaction) that result in asymmetrical outcomes (i.e., status quo maintenance). Finally, we summarise the main conclusions and address contributions to theory and research as well as directions for further research.     

A Minister's Information-Handling

ABSTRACT

One of the roles which ministers perform is that of “caregiver.” Caregiving functions include such activities as visiting parishioners, hearing confessions, and counselling people. These functions are carried out within a legal context. In this paper, two aspects of the parish minister's information handling in respect to his/her role as caregiver are examined. Specific attention is given to the pastor's vulnerability, while carrying out pastoral duties, to civil lawsuits for malpractice and to her/his expectation of privilege against testifying in criminal proceedings. It is observed that in North America, considerable confusion exists over who actually owns and who can control the information a minister acquires and disseminates.     

The response dynamics of preferential choice

The ubiquity of psychological process models requires an increased degree of sophistication in the methods and metrics that we use to evaluate them. We contribute to this venture by capitalizing on recent work in cognitive science analyzing response dynamics, which shows that the bearing information processing dynamics have on intended action is also revealed in the motor system. This decidedly “embodied” view suggests that researchers are missing out on potential dependent variables with which to evaluate their models—those associated with the motor response that produces a choice. The current work develops a method for collecting and analyzing such data in the domain of decision making. We first validate this method using widely normed stimuli from the International Affective Picture System (Experiment 1), and demonstrate that curvature in response trajectories provides a metric of the competition between choice options. We next extend the method to risky decision making (Experiment 2) and develop predictions for three popular classes of process model. The data provided by response dynamics demonstrate that choices contrary to the maxim of risk seeking in losses and risk aversion in gains may be the product of at least one “online” preference reversal, and can thus begin to discriminate amongst the candidate models. Finally, we incorporate attentional data collected via eye-tracking (Experiment 3) to develop a formal computational model of joint information sampling and preference accumulation. In sum, we validate response dynamics for use in preferential choice tasks and demonstrate the unique conclusions afforded by response dynamics over and above traditional methods.     

Hierarchical models for relational event sequences

Interaction within small groups can often be represented as a sequence of events, each event involving a sender and a recipient. Recent methods for modeling network data in continuous time model the rate at which individuals interact conditioned on the previous history of events as well as actor covariates. We present a hierarchical extension for modeling multiple such sequences, facilitating inferences about event-level dynamics and their variation across sequences. The hierarchical approach allows one to share information across sequences in a principled manner—we illustrate the efficacy of such sharing through a set of prediction experiments. After discussing methods for adequacy checking and model selection for this class of models, the method is illustrated with an analysis of high school classroom dynamics from 297 sessions.     

Mental Health and Adverse Childhood Experiences

The theoretical basis of occupational therapy interventions was investigated in two mental health facilities in the Midwestern United States. Using retrospective cohort and grounded theory designs, 121 medical records were reviewed and five occupational therapy practitioners were interviewed. Theoretical reasoning was not explicitly documented, but according to analysis, the behavioral/cognitive-behavioral model, client-centered models, and the model of human occupation were the most frequently used theories to guide interventions. Lack of documentation of theory use has significant implications for the value accorded to occupational therapy skills in health care. A larger study is recommended to increase external generalizability of the findings.     

Evaluating the effect of educational media exposure on aggression in early childhood

Preschool-aged children (M = 42.44 months-old, SD = 8.02) participated in a short-term longitudinal study investigating the effect of educational media exposure on social development (i.e., aggression and prosocial behavior) using multiple informants and methods. As predicted, educational media exposure significantly predicted increases in both observed and teacher reported relational aggression across time. Follow-up analyses showed that educational media exposure also significantly predicted increases in parent reported relational aggression across more than a two year period. Results replicate and extend prior research that has demonstrated links between educational media exposure and relational aggression, but not physical aggression, during early childhood.