Toward a new conceptualization and operationalization of risk perception within the genetic counseling domain

The purpose of this paper is twofold. First, it provides an historical overview of studies of risk, risk perception, and decision making under risk within the genetic counseling domain. Second, it proposes an alternative conceptualization and operationalization for the study of risk perception. The conceptualization involves probability, adversity, incompleteness, and ambiguity. Prior studies of risk perception focus on the recurrence risk and operationalize risk perception by asking for interpretations of the magnitude of the probability of the outcome. Their focus is on the probability of a particular outcome. We formulate the problem in terms of a gamble and suggest that risk perception be operationalized in terms of the riskiness of the gamble. Our focus is on the riskiness of a decision option which entails two or more outcomes.     

The asymptotic posterior normality of the latent trait in an IRT model

It has long been part of the item response theory (IRT) folklore that under the usual empirical Bayes unidimensional IRT modeling approach, the posterior distribution of examinee ability given test response is approximately normal for a long test. Under very general and nonrestrictive nonparametric assumptions, we make this claim rigorous for a broad class of latent models.This research was partially supported by Office of Naval Research Cognitive and Neural Sciences Grant N0014-J-90-1940, 442-1548, National Science Foundation Mathematics Grant NSF-DMS-91-01436, and the National Center for Supercomputing Applications. We wish to thank Kumar Joag-dev and Zhiliang Ying for enlightening suggestions concerning the proof of the basic result.The authors wish to thank Kumar Joag-Dev, Brian Junker, Bert Green, Paul Holland, Robert Mislevy, and especially Zhiliang Ying for their useful comments and discussions.     

Themes in Therapist Development During the First Three Months of Clinical Experience

The results of a qualitative research study designed to better understand the developmental processes active in beginning therapists during the first three months of clinical contact is reported. Thirteen beginning therapists were asked to complete a monthly log describing experiences impacting their clinical work and themselves as therapists during their first three months of client contact. Data analysis revealed that the primary developmental theme active during this period of time is the development of therapist confidence. Two additional themes, the development of an internal gauge on which to evaluate current experiences and the development of boundaries around the self as a professional, were also found to be active during this time. These additional themes support the development of therapist confidence. Implications for training and research are identified.     

Application of the bootstrap methods in factor analysis

A Monte Carlo experiment is conducted to investigate the performance of the bootstrap methods in normal theory maximum likelihood factor analysis both when the distributional assumption is satisfied and unsatisfied. The parameters and their functions of interest include unrotated loadings, analytically rotated loadings, and unique variances. The results reveal that (a) bootstrap bias estimation performs sometimes poorly for factor loadings and nonstandardized unique variances; (b) bootstrap variance estimation performs well even when the distributional assumption is violated; (c) bootstrap confidence intervals based on the Studentized statistics are recommended; (d) if structural hypothesis about the population covariance matrix is taken into account then the bootstrap distribution of the normal theory likelihood ratio test statistic is close to the corresponding sampling distribution with slightly heavier right tail.This study was carried out in part under the ISM cooperative research program (91-ISM · CRP-85, 92-ISM · CRP-102). The authors would like to thank the editor and three reviewers for their helpful comments and suggestions which improved the quality of this paper considerably.     

Calibration of sensory and cognitive judgments: A single model for both

In a recent issue of this journal, Winman and Juslin (34 , 135–148, 1993) present a model of the calibration of subjective probability judgments for sensory discrimination tasks. They claim that the model predicts a pervasive underconfidence bias observed in such tasks, and present evidence from a training experiment that they interpret as supporting the notion that different models are needed to describe judgment of confidence in sensory and in cognitive tasks. The model is actually part of the more comprehensive decision variable partition model of subjective probability calibration that was originally proposed in Ferrell and McGoey (Organizational Behavior and Human Performance, 26 , 32–53, 1980). The characteristics of the model are described and it is demonstrated that the model does not predict underconfidence, that it is fully compatible with the overconfidence frequently found in calibration studies with cognitive tasks, and that it well represents experimental results from such studies. It is concluded that only a single model is needed for both types of task.     

A compensatory approach to optimal selection with mastery scores

A Bayesian approach for simultaneous optimization of test-based decisions is presented using the example of a selection decision for a treatment followed by a mastery decision. A distinction is made between weak and strong rules where, as opposed to strong rules, weak rules use prior test scores as collateral data. Conditions for monotonicity of optimal weak and strong rules are presented. It is shown that under mild conditions on the test score distributions and utility functions, weak rules are always compensatory by nature. The authors are indebted to Wilbert Kallenberg for his valuable comments and to Jan Gulmans for providing the data for the empirical example. The names of the authors are alphabetical; they are equally responsible for the contents of this paper.     

A study of the foundations of ethical decision making of clinical medical ethicists

A study of clinical medical ethicists was conducted to determine the various philosophical positions they hold with respect to ethical decision making in medicine and their various positions' relationship to the subjective-objective controversy in value theory. The study consisted of analyzing and interpreting data gathered from questionnaires from 52 clinical medical ethicists at 28 major health care centers in the United States. The study revealed that most clinical medical ethicists tend to be objectivists in value theory, i.e., believe that value judgments are knowledge claims capable of being true or false and therefore expressions of moral requirements and normative imperatives emanating from an external value structure or moral order in the world. In addition, the study revealed that most clinical medical ethicists are consistent in the philosophical foundations of their ethical decision making, i.e., in decision making regarding values they tend not to hold beliefs which are incompatible with other beliefs they hold about values.     

Simulation of Preference Information in an Interactive Reference Point‐Based Method for the Bi‐Objective Inventory Routing Problem

In the research area of multiple criteria decision making, very few publications exist that explicitly design the simulation of a decision maker (DM) in an interactive approach. For this reason, we outline some methods widely used in the literature to identify common assumptions of simulating the DM's responses and the required input preference information. Our paper aims at covering the identified gap by introducing experimental concepts. Such concepts are used for theoretical analyses of a combined search‐and‐decision‐making procedure. Simulating the DM is a fruitful idea because the algorithm can be tested without integrating a human decision maker. Finally, we conduct experiments based on the proposed settings for a multiobjective inventory routing problem, which is a relevant and challenging logistic problem. Copyright © 2014 John Wiley & Sons, Ltd.     

Adversary effects and the tactics of violent offenders

We examine the implication of adversary effects for target choice, lethal intent, and the use of weapons and allies in violent incidents. Adversary effects refer to the tendency of offenders to make tactical decisions based on the coercive power of victims and potential victims. Using the victim's gender as a proxy for coercive power, we analyzed violent incidents from the National Incident‐Based Reporting System (2005–2014). The sample included over six million assaults, robberies, and homicides. Consistent with adversary effects, offenders who attack males (vs. females) are more likely to (a) kill victims; (b) use guns, knives, blunt objects, poison, and automobiles; (c) use male (but not female) allies; and (d) use multiple allies. The evidence for target choice is mixed: unarmed female offenders, but not unarmed male offenders, are more likely to target females than males. The evidence shows how a simple theoretical principle can parsimoniously account for basic patterns of violence in society related to gender, weapons, and group violence.     

Choosing what to choose from: Preference for inclusion over exclusion when constructing consideration sets from large choice sets

Decision making is a two‐stage process, consisting of, first, consideration set construction and then final choice. Decision makers can form a consideration set from a choice set using one of two strategies: including the options they wish to further consider or excluding those they do not wish to further consider. The authors propose that decision makers have a relative preference for an inclusion (vs. exclusion) strategy when choosing from large choice sets and that this preference is driven primarily by a lay belief that inclusion requires less effort than exclusion, particularly in large choice sets. Study 1 demonstrates that decision makers prefer using an inclusion (vs. exclusion) strategy when faced with large choice sets. Study 2 replicates the effect of choice set size on preference for consideration set construction strategy and demonstrates that the belief that exclusion is more effortful mediates the relative preference for inclusion in large choice sets. Studies 3 and 4 further support the importance of perceived effort, demonstrating a greater preference for inclusion in large choice sets when decision makers are primed to think about effort (vs. accuracy; Study 3) and when the choice set is perceived as requiring more effort because of more information being presented about each alternative (vs. more alternatives in the choice set; Study 4). Finally, Study 5 manipulates consideration set construction strategy, showing that using inclusion (vs. exclusion) in large choice sets leads to smaller consideration sets, greater confidence in the decision process, and a higher quality consideration set.