Ripples of contempt: aversive responses to others (mis)fortunes

Motivation and Emotion - In this short commentary we argue that feelings of contempt play a major role in schadenfreude (joy in the misfortunes of others) and “reverse...     

Evolving informational credentials: the (mis)attribution of believable facts to credible sources

Three studies demonstrate that individuals often rely on a "belief force equals credible source" heuristic to make source judgments, wherein they assume that statements they believe originate from credible sources. In Study 1, participants who were exposed to a statement many times (and hence believed it) were more likely to attribute it to Consumer Reports than to the National Enquirer. In Study 2, participants read a murder investigation article containing evidence against two suspects from credible and noncredible sources. When participants believed a particular suspect to be guilty, they misattributed evidence incriminating that suspect to the high-credibility source. Study 3 demonstrated that this phenomenon occurs because individuals assume their beliefs are true and that true beliefs come from credible sources; when participants were given feedback that their beliefs were incorrect, the relationship between beliefs and source inferences did not occur.     

The (mis)reporting of statistical results in psychology journals

In order to study the prevalence, nature (direction), and causes of reporting errors in psychology, we checked the consistency of reported test statistics, degrees of freedom, and p values in a random sample of high- and low-impact psychology journals. In a second study, we established the generality of reporting errors in a random sample of recent psychological articles. Our results, on the basis of 281 articles, indicate that around 18% of statistical results in the psychological literature are incorrectly reported. Inconsistencies were more common in low-impact journals than in high-impact journals. Moreover, around 15% of the articles contained at least one statistical conclusion that proved, upon recalculation, to be incorrect; that is, recalculation rendered the previously significant result insignificant, or vice versa. These errors were often in line with researchers’ expectations. We classified the most common errors and contacted authors to shed light on the origins of the errors.     

A learning approach to the treatment of homosexuality

‘Aversive’ techniques in the treatment of homosexuality provide practical and ethical difficulties for the therapist. A technique involving ‘imaginary’ aversive therapy and a discrimination learning task is described. It is felt that such an approach following on classical desensitization of neurotic disturbances which may underly the homosexual disorder, offers hope of early symptom removal and lasting improvement.     

Debiasing the hindsight bias: The role of accessibility experiences and (mis)attributions

Two studies tested the role of accessibility experiences and attributions in debiasing the hindsight bias. Participants listed 4 or 12 thoughts about how a college football game, or the 2000 US Presidential election, might have turned out differently. Listing 12 thoughts was experienced as difficult, suggesting to participants that there were few ways in which the event could have turned out otherwise. Hindsight biases increased under this condition, unless participants attributed the difficulty of the thought generation to their own lack of knowledge, which resulted in a trend in the opposite direction. The interplay of accessible content, accessibility experiences and attribution in mental simulation is discussed.     

The ideomotor approach to imitative learning (IMAIL) in infancy: Challenges and future perspectives

The article presents the ideomotor approach to imitative learning (IMAIL). According to IMAIL, imitation rests on the acquisition of bidirectional action–effect associations through the observations of others’ actions and their sensory consequences. The article first outlines the challenges and demands that motivated the development of the theory. Then, it describes the theory in greater detail and presents empirical evidence supporting IMAIL. Finally, it concludes by discussing challenges and avenues for further research.     

A metacognitive approach to "implicit" and "explicit" evaluations: comment on Gawronski and Bodenhausen (2006)

A metacognitive model (MCM) is presented to describe how automatic (implicit) and deliberative (explicit) measures of attitudes respond to change attempts. The model assumes that contemporary implicit measures tap quick evaluative associations, whereas explicit measures also consider the perceived validity of these associations (and other factors). Change in explicit measures is greater than implicit measures when new evaluative associations are formed and old associations are rejected. Implicit measure change is greater than explicit when newly formed evaluative associations are rejected. When implicit and explicit evaluations conflict, implicit ambivalence can occur. The authors relate the MCM to the associative-propositional evaluation model and explain how the MCM builds on the attitude strength assumptions of the elaboration likelihood model of persuasion.     

Evaluating the efficacy of a program to enhance college students' self-regulation learning processes and learning strategies

The present study examines the efficacy of a program designed to enhance college students'learning processes and study strategies. The program was organised around a number of letters written by a freshman, Gervásio (Rosário, Nú?ez, & González-Pienda, 2006), telling about his new experiences, troubles, and successes in the university. This intervention program is intended to promote a series of strategies (cognitive, meta-cognitive, and supportive) which allow students to manage their learning processes in a more proficient, successful, and autonomous way. The collected data suggest that students who had the opportunity to follow the program significantly improved their declarative knowledge about learning strategies, reduced their use of surface approaches to study, and extended the newly acquired skills to new and different tasks and assignments.     

Filling in the gaps: using testing and restudy to promote associative learning

Although testing has been shown to potentiate subsequent learning [Izawa, C. (1966). Reinforcement-test sequences in paired-associate learning. Psychological Reports, 18, 879–919.], the mechanisms that influence this effect are not entirely understood. The present research examined the relationship between associative binding and test-potentiation effects. We hypothesised that test-potentiation effects would be most pronounced when participants could easily extract the relationship among word groupings. Towards that end, we compared three-word groupings, or triads, that were either semantically related or unrelated. Participants engaged in repeated study, repeated testing, or engaged in interpolated study and test prior to a final test. Final test performance was greatest for participants who engaged in interpolated study and test on related triads. The results support three primary conclusions: (1) testing aids in associative binding; (2) associative binding is facilitated by retrieval practice and restudy pairings; and (3) pre-existing associations facilitate test-potentiation effects.     

The (mis)measurement of body image: ten strategies to improve assessment for applied and research purposes

Body image is a multifaceted construct consisting of a variety of measured dimensions. Research in the area has mushroomed in recent years, a phenomenon paralleled by an explosion in the assessments developed to measure some aspect of the construct. Unfortunately, these developments have not always been guided by a clear-cut attention to measurement issues. Assessment errors specific to the field of body image and also germane to basic psychological measurement strategies have characterized much of the work in the area. This article outlines 10 such issues with accompanying examples and suggestions for avoiding such pitfalls. Attention to these seemingly minor methodological details should result in a more consistent conceptualization of body image, utilization of appropriate measures in specific contexts, and engender more valid comparisons of findings across disparate studies.     

On the (mis)categorization of unattractive brides and attractive prostitutes: extending evaluative congruency effects to social category activation

Numerous studies have shown that social categorization is a flexible process that partly depends on contextual variables. However, little is known about the role of affect in people's access to categorical dimensions. We investigated the hypothesis that social category activation is facilitated on evaluatively congruent dimensions. Two studies provide support for this evaluative-matching hypothesis, in which social categorization was found to be faster and more accurate for evaluatively congruent categories (i.e., unattractive foreigners, unattractive prostitutes, attractive fellow-citizens and attractive brides) than for evaluatively incongruent categories (i.e., attractive foreigners, attractive prostitutes, unattractive fellow-citizens and unattractive brides). We discuss the theoretical and practical implications of these findings.     

Efficacy of objects,pictures and words in a simple learning task(1)

Adult subjects were required to memorise positions associated with twelve common objects, their pictures and their names. Both written and spoken names were used. It was found that learning was fastest with the objects and slowest with verbal symbols, and that pictures occupied an intermediate position. The data suggest that the errors observed are partly due to differential forgetting of various types of stimuli and partly perhaps to differential difficulty in making deductions from them.     

A new approach to the formulation and testing of learning models

It is argued that current attempts to model human learning behavior commonly fail on one of two counts: either the model assumptions are artificially restricted so as to permit the application of mathematical techniques in deriving their consequences, or else the required complex assumptions are imbedded in computer programs whose technical details obscure the theoretical content of the model. The first failing is characteristic of so-called mathematical models of learning, while the second is characteristic of computer simulation models. An approach to model building which avoids both these failings is presented under the title of a black-box theory of learning. This method permits the statement of assumptions of any desired complexity in a language which clearly exhibits their theoretical content.Section II of the paper is devoted to the problem of testing and comparing alternative learning theories. The policy advocated is to abandon attempts at hypothesis testing. It is argued that, in general, we not only lack sufficient data and sufficiently powerful techniques to test hypotheses, but that the truth of a model is not really the issue of basic interest. A given model may be true in the sense that on the basis of available evidence we cannot statistically reject it, but not interesting in the sense that it provides little information about the processes underlying behavior. Rather, we should accept or reject models on the basis of how much information they provide about the way in which subjects respond to environmental structure. This attitude toward model testing is made precise by introducing a formal measure of the information content of a model. Finally, it is argued that the statistical concept of degrees-of-freedom is misleading when used in the context of model testing and should be replaced by a measure of the information absorbed from the data in estimating parameters.I would like to express my indebtedness to Ernest W. Adams and Julian Feldman for their guidance and encouragement of the research reported here.Much of the research reported here was conducted at the University of California, Berkeley, and incorporated in a Ph.D. dissertation in Logic and the Methodology of Science [15]. The research was supported in part by the Computer Institute for Social Science Research, Michigan State University.