Lay Theories Concerning Causes and Treatment of Depression

This study compared perceptions of the causes of, therapies for, and means of coping with, depression between two groups of currently nondepressed adults: one with a history of major depression and one with no history of depression. Currently nondepressed participants were selected so that effects of past experience of depression could be distinguished from those of current mood. Recovered depressed participants (RD) (n = 25) and Never depressed participants (ND) (n = 25) recruited via newspaper advertisements completed self-report measures of (a) the perceived utility of either professional or self-help coping strategies for managing their own experiences of depression; (b) likely effectiveness of several major therapies for depression; and (c) perceived accuracy of several etiological theories of depression. RD participants rated depression as being less amenable to everyday self-help methods of coping and more in need of professional intervention. However, RD and ND subgroups did not differ significantly in their perceptions of the plausibility of etiological theories of depression in general, nor in their ratings of the likely helpfulness of major therapies.     

Steep Cliff Arguments

In recent philosophical debates a number of arguments have been used which have so much in common that it is useful to study them as having a similar structure. Many arguments – Searle's Chinese Room, for example – make use of thought experiments in which we are told a story or given a narrative context such that we feel we are in comfortable surroundings. A new notion is then introduced which clashes with our ordinary habits and associations. As a result, we do not bother to investigate seriously the new notion any further. I call such an arrangement, which is perhaps a variation of the fallacy of presumption, a Steep Cliff argument. One remedy for the misdirection of a Steep Cliff argument is to tell a counterstory from the point of view of the rejected notion.     

Content Analysis of Cognitive Bias: Development of a Standardized Measure

The purpose of this research was to develop a standardized content analytic measure of cognitive bias as conceptualized in Beck's (1987) cognitive theory of depression. In a pilot study it was determined that a written stimulus format was preferable to an audiotaped stimulus format with respect to comprehensibility. Valence and expectancy ratings collected in this pilot study also served as the basis for selection of items for the final measure, balancing positive and negative, expected and unexpected events. In study 2 open-ended written responses to questions about the main cause of each event, and the justifications for these attributions, were coded for indices of bias, defined (as in Cook & Peterson, 1986) as justifications that fail to cite covariation of the ascribed cause with the effect. Cognitive bias scores in Study 2 showed internal consistency (positive item-remainder correlations) and high interrater reliability. As predicted, justifications of attributions for expected events were more biased and less rational than were justifications of attributions for unexpected events.     

Further Support for a Hierarchical Model of Affect: Reply to Green and Salovey

Green and Salovey agree with us that happiness and sadness are strongly bipolar, and that Positive and Negative Activation are not. However, Green and Salovey subscribe to the two-dimensional circumplex, a model we find wanting. Actually, the problems they discuss arise from the limitations of the circumplex rather than from issues fundamental to affective structure. And they do not consider the evidence, reported in our target article, that supports an alternative to the circumplex: a three-level hierarchical model. In this reply, we take a closer look at the empirical findings supporting this model, and we emphasize its heuristic promise.     

Distinguishing Language from Thought: Experimental Evidence That Syntax Is Lexically Rather Than Conceptually Represented

It is generally assumed that syntax is represented linguistically rather than conceptually, consistent with the more general view that language and thought are coded separately. This claim is widely defended on logical grounds, but it has received little experimental support. In the present study, we asked Spanish and English speakers to make semantic and syntactic categorizations for pictures and their corresponding names. Consistent with past results, latencies to semantically categorize pictures and words were similar. The new finding is that participants were faster to make syntactic decisions for words compared with pictures, suggesting that syntactic features such as grammatical gender and the count-mass distinction are more closely linked to lexical than conceptual representations.     

Sponsored research in the counseling psychology literature

Elliott and Shewchuk (1996) assert that counseling psychology should have considerable potential to influence national healthcare and public policy. A mechanism for realizing this potential entails being responsive to national, state and private funding initiatives for reaearch and other programmatic activities. To examine the extent to which counseling psychology resarch reflects an involvement in these initiatives, we studied the rate of sponsored research in three journals traditionally associated with mainstream counseling psychology research. We compared this rate with that observed in oher applied and theoretically oriented psychological journals. In comparison with the research published in the other outlets, results indicated that the mainstream counseling psychology literature has a disproportionately low level of sponsorship from national and federal sources. The scant representation of federally-funded research in the counseling psychology literature may effectively preclude full participation in addressing and setting national funding priorities and other health care and public policies germane to the field. Several issues are raised and discussed in light of these findings.     

Knowledge level learning and the power law: A soar model of skill acquisition in scheduling

Zusammenfassung. Das hier vorgestellte Modell lernt graduell, Planungsaufgaben aus der Klasse der Maschinenbelegungsprobleme (job-shop-scheduling problems) zu lösen. Mit Hilfe des Chunking-Mechanismus von Soar wird episodisches Wissen über die Belegungsreihenfolge von Aufträgen auf Maschinen memoriert. Bei der Entwicklung des Modells wurden zahlreiche qualitative (z. B. Transfereffekte) und quantitative Befunde (z. B. Bearbeitungszeiten) aus einer früheren empirischen Untersuchung berücksichtigt. In einer Validierungsstudie wurden dieselben Aufgaben von 14 Probanden und dem Modell bearbeitet. Die Passung von Simulationsdaten und empirischen Ergebnissen fiel insgesamt gut aus. Allerdings löst das Modell die Aufgaben schneller und zeigt auch einen etwas besseren Lernverlauf als die Probanden. Das Modell liefert eine Erklärung für das Rauschen, das typischerweise bei Bearbeitungszeiten zu beobachten ist: es handelt sich um erworbenes Wissen, das mehr oder weniger gut und auch unterschiedlich häufig auf neue Situationen übertragen wird. Der Lernverlauf der Probanden entspricht nur für aggregierte Daten einer Potenzfunktion (power law). Der vorgestellte Mechanismus zeigt, wie ein symbolisches Modell der Informationsverarbeitung graduelle Verhaltensänderungen generiert und wie der offensichtliche Erwerb allgemeiner Prozeduren ohne explizites Lernen von deklarativen Regeln erfolgen kann. Es wird nahegelegt, daß es sich hier um die Modellierung einer Form impliziten Lernens handelt. Summary. The model presented here gradually learns how to perform a job-shop scheduling task. It uses Soar's chunking mechanism to acquire episodic memories about the order to schedule jobs. The model was based on many qualitative (e.g., transfer effects) and quantitative (e.g., solution time) regularities found in previously collected data. The model was tested with new data where scheduling tasks were given to the model and to 14 subjects. The model generally fit these data with the restrictions that the model performs the task (in simulated time) faster than the subjects, and its performance improves somewhat more quickly than the subjects' performance. The model provides an explanation of the noise typically found in problem solving times - it is the result of learning actual pieces of knowledge that transfer more or less to new situations but rarely by an average amount. Only when the data are averaged (i.e., over subjects) does the smooth power law appear. This mechanism demonstrates how symbolic models can exhibit a gradual change in behavior and how the apparent acquisition of general procedures can be performed without resorting to explicit declarative rule generation. We suggest that this may represent a type of implicit learning.     

The puzzle of language evolution

Linguistics must again concentrate on the evolutionary nature of language, so that language models are more realistic with respect to human natural languages and have a greater explanatory force. Multi-agent systems are proposed as a possible route to develop such evolutionary models and an example is given of a concrete experiment in the origins and evolution of word-meaning based on a multi-agent approach.