The Case for Rules in Reasoning

A number of theoretical positions in psychology—including variants of case-based reasoning, instance-based analogy, and connectionist models—maintain that abstract rules are not involved in human reasoning, or at best play a minor role. Other views hold that the use of abstract rules is a core aspect of human reasoning. We propose eight criteria for determining whether or not people use abstract rules in reasoning, and examine evidence relevant to each criterion for several rule systems. We argue that there is substantial evidence that several different inferential rules, including modus ponens, contractual rules, causal rules, and the law of large numbers, are used in solving everyday problems. We discuss the implications for various theoretical positions and consider hybrid mechanisms that combine aspects of instance and rule models.     

Momentary mood and coping processes in TMD pain.

Temporomandibular dysfunction (TMD) pain, like many chronic pain problems, appears to be multiply determined. Patients with TMD pain of at least 6 months duration (N = 30) were administered questionnaires measuring dispositional coping styles and appraisals to explore the dynamic interactions of the pain and coping process. Patients were then issued handheld computers that prompted them to record their momentary pain and coping processes 4 times per day for 7 days. Hierarchical linear regression models using both the dispositional and momentary predictors indicated that momentary pain was a function both of dispositional tendency to catastrophize and of momentary measures of catastrophization, self-efficacy, and mood states. Results were seen as supporting a situational model of intervention for chronic TMD pain.     

Conceptual Hierarchies in a Flat Attractor Network: Dynamics of Learning and Computations

The structure of people's conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical ( Collins & Quillian, 1969 ). For example, superordinate concepts ( vegetable ) are assumed to reside at a higher level than basic-level concepts ( carrot ). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts ( vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory.     

A new perspective on visual word processing efficiency

As a fundamental part of our daily lives, visual word processing has received much attention in the psychological literature. Despite the well established advantage of perceiving letters in a word or in a pseudoword over letters alone or in random sequences using accuracy, a comparable effect using response times has been elusive. Some researchers continue to question whether the advantage due to word context is perceptual. We use the capacity coefficient, a well established, response time based measure of efficiency to provide evidence of word processing as a particularly efficient perceptual process to complement those results from the accuracy domain.     

Traits in Transition: The Structure of Parent‐Reported Personality Traits from Early Childhood to Early Adulthood

The present research was conducted to map the hierarchical structure of youths' personality traits, to identify the foundational level of this structure, and to test whether the meanings of some youth personality dimensions shift with age. We addressed these issues by analyzing personality parent reports describing a cross‐sectional sample of 16,000 children, adolescents, and young adults (ages 3 to 20). These parent reports were made using a broadband measure of youths' personal characteristics, the common‐language California Child Q‐Set. Analyses of the full sample and comparisons of 16 age groups supported three main conclusions. First, the hierarchical structure of youths' personality traits both resembles and differs from the adult personality hierarchy in important ways. Second, a set of six dimensions—Extraversion, Agreeableness, Conscientiousness, Neuroticism, Openness to Experience, and Activity—may constitute the foundational level of the youth personality hierarchy from middle childhood through adolescence. This “Little Six” structure represents a union of the most prominent personality and temperament dimensions. Third, the meanings of some youth personality dimensions (e.g., Activity, Conscientiousness) shift systematically with age. These findings advance our understanding of when and how personality structure develops during the first two decades of life.     

The Fundamental Theorem of World Theory

The fundamental principle of the theory of possible worlds is that a proposition p is possible if and only if there is a possible world at which p is true. In this paper we present a valid derivation of this principle from a more general theory in which possible worlds are defined rather than taken as primitive. The general theory uses a primitive modality and axiomatizes abstract objects, properties, and propositions. We then show that this general theory has very small models and hence that its ontological commitments—and, therefore, those of the fundamental principle of world theory—are minimal.     

Predicting Response to Intensive Multimodal Inpatient Treatment: A Comparison of Single- and Multiple-Class Growth Modeling Approaches

In a modest body of research, personality functioning assessed via performance-based instruments has been found to validly predict treatment outcome and, to some extent, differential response to treatment. However, state-of-the-science longitudinal and mixture modeling techniques, which are common in many areas of clinical psychology, have rarely been used. In this article, we compare multilevel growth curve modeling (MLM) and latent class growth modeling (LCGM) approaches with the same data set to illustrate the different research questions that can be addressed by each method. Global Assessment of Functioning (GAF) scores collected at 6 points during the course of a long-term multimodal inpatient treatment of 58 severely and persistently mentally ill adults were used to model the trajectory of treatment outcome. Pretreatment Rorschach-based markers of personality functioning and other markers of psychiatric severity were examined as covariates in each modeling approach. The results of both modeling approaches generally indicated that more psychologically impaired clients responded less favorably to treatment. The LCGM approach revealed 2 unique trajectories of improvement (a persistently low group and a higher starting, improving group). Personality functioning and baseline psychiatric variables significantly predicted group membership and the rate of change within the groups. A side-by-side examination of these 2 methods was found to be useful in predicting differential treatment response with personality functioning variables.