Basis of metamemory judgments for text with multiple‐choice,essay and recall tests

Accuracy of metamemory for text was compared for multiple‐choice, essay and recall tests. Essay and recall tests were scored with Latent Semantic Analysis (LSA), number of correct idea units and number of word matches. Each measure was correlated with college students' predictions and posttest confidence judgments across texts to determine metamemory accuracy. Metamemory accuracy varied for different types of tests with multiple‐choice tests generally producing greater accuracy than essay tests. However, metamemory accuracy for essay and recall tests depended on the measure used to score them. Number of correct idea units produced the highest metamemory accuracy, word matches produced an intermediate level, and LSA produced the lowest accuracy. Students used the quantity of output in their judgments, so performance measures that related most strongly to quantity matched judgments better than measures based on answer quality. The results are compatible with an accessibility account of judgments about performance on text. Copyright © 2008 John Wiley & Sons, Ltd.     

Computational models of inductive reasoning using a statistical analysis of a Japanese corpus

Existing computational models of human inductive reasoning have been constructed based on psychological evaluations concerning the similarities or relationships between entities. However, the costs involved in collecting psychological evaluations for the sheer number of entities that exist mean that they are prohibitively impractical. In order to avoid this problem, the present article examines three types of models: a category-based neural network model, a category-based Bayesian model, and a feature-based neural network model. These models utilize the results of a statistical analysis of a Japanese corpus computing co-occurrence probabilities for word pairs, rather than using psychological evaluations. Argument strength ratings collected by a psychological experiment were found to correlate well with simulations for the category-based neural network model.     

Semantic distance norms computed from an electronic dictionary (WordNet).

WordNet, an electronic dictionary (or lexical database), is a valuable resource for computational and cognitive scientists. Recent work on the computing of semantic distances among nodes (synsets) in WordNet has made it possible to build a large database of semantic distances for use in selecting word pairs for psychological research. The database now contains nearly 50,000 pairs of words that have values for semantic distance, associative strength, and similarity based on co-occurrence. Semantic distance was found to correlate weakly with these other measures but to correlate more strongly with another measure of semantic relatedness, featural similarity. Hierarchical clustering analysis suggested that the knowledge structure underlying semantic distance is similar in gross form to that underlying featural similarity. In experiments in which semantic similarity ratings were used, human participants were able to discriminate semantic distance. Thus, semantic distance as derived from WordNet appears distinct from other measures of word pair relatedness and is psychologically functional. This database may be downloaded from www.psychonomic.org/archive/.     

The helping orientations inventory: Measuring propensities to provide autonomy and dependency help

Research on helping behavior distinguishes between giving recipients the tools to solve problems for themselves (autonomy‐oriented help) and direct solutions not requiring recipients' involvement (dependency‐oriented help). Across three studies, we examined whether individuals can be characterized by dispositional propensities toward offering autonomy‐oriented and/or dependency‐oriented help. In initial studies, factor analyses revealed the two hypothesized Helping Orientations Inventory scales along with an additional scale capturing opposition to helping, all acceptable in internal consistency and test–retest reliability (Studies 1a–1c). Next, we found that the three scales related in distinct ways to constructs from the intergroup (e.g., social dominance orientation) and interpersonal (e.g., empathic concern) helping literatures (Studies 1d and 1e). Additionally, these orientations predicted satisfaction with volunteer behavior (Study 2) and interest in future volunteering (Study 3). Overall, people vary in their helping orientations, and these orientations implicate a range of variables relevant to intergroup and interpersonal helping.     

False memory for associated word lists in individuals and collaborating groups

Using the Deese/Roediger-McDermott (DRM) paradigm, we investigated recall of presented and nonpresented associated words by collaborating groups, nominal groups, and individuals. In Experiment 1, participants recalled individually and then recalled in collaborating groups. Nominal groups made up of individual recall produced more presented and nonpresented associated words than did collaborating groups. Collaborating groups recalled more presented words than did individuals, but not more nonpresented words. In Experiment 2, collaborating groups versus individuals was a between-subjects variable, and everyone made two recall attempts. For recall, the pattern was the same as that in Experiment 1, in that collaborating groups recalled more presented words than did individuals but about the same number of nonpresented words. In a DRM paradigm, collaborating groups were able to produce more presented words than were individuals, without increasing their false recall.     

A database of associative strengths from the strength-sampling model: A theory-based supplement to the Nelson,McEvoy, and Schreiber word association norms

The strength-sampling model of free association (Nelson, McEvoy, & Dennis, 2000) claims that the probability of word association in free-association norms results from a sampling process. For a given cue word, each response word has an underlying distribution of strength values. In the free-association task, presentation of the cue word activates a random sample of strengths, one for each response. The highest strength wins, and its response is reported. In the present work, gradient descent was used to compute the theoretical mean strengths for each cue-response pair in the Nelson, McEvoy, and Schreiber (2004) norms. The resulting database may be downloaded from www.psychonomic.org/archive/.     

The recognized benefits of negative thinking/affect in depression and anxiety: Developing a scale

Negative thinking/affect (NTA) in depression and anxiety is an important target of clinical intervention. However, individuals recognize the benefit of NTA. There is a need to develop a scale for empirical studies of NTA. Two‐hundred and fifty‐nine Japanese university students were assigned to answer: (a) the state in the past week (positive affect (PA) and Center for Epidemiologic Studies Depression Scale), (b) the current state (PA and State‐Trait Anxiety Inventory‐State (STAI‐S)), and (c) the usual state (PA and STAI‐Trait), after completing the Recognized Benefit of NTA Scale (RBNTA). Another 291 students completed the Rosenberg Self‐Esteem Scale and the Revised Life Orientation Test, after completing the RBNTA. Two weeks later, 76 participants completed the RBNTA. The RBNTA with nine subscales was developed after comparing the indices of fitness from 14 different factor solutions. The internal and test‐retest reliability and content validity were confirmed. Correlation analyses revealed that the recognition of trying to obtain benefits/avoid costs tends to associate with positive/negative affect and that most of such recognitions did not associate with self‐esteem and optimism.     

A Pilot Study Addressing the Impact of Religious Practice on Quality of Life of Breast Cancer Patients During Chemotherapy

The aim of this preliminary study was to investigate whether religious practice can modify quality of life (QoL) in BC patients during chemotherapy. QoL and religion practice questionnaire (RPQ) scores were evaluated in a sample of BC patients in different moments. Before chemotherapy initiation, women with lower physical and social functional scores displayed higher RPQ scores. On the other hand, low RPQ patients worsened some QoL scores over time. Body image acceptance was positively correlated with religious practice and specifically praying activity. This preliminary study suggests the importance of religion in coping with cancer chemotherapy.     

Childhood Adversity and Adulthood Subjective Well-Being: Evidence from Japan

In this study, we examined the impact of childhood interpersonal adversity on adulthood subjective well-being (SWB), with a focus on the mediating and moderating effects of social support and socioeconomic status (SES). We concentrated on parental maltreatment (abuse and neglect) and bullying in school as childhood adversity variables and on perceived happiness and self-rated health as adulthood SWB measures. Our empirical analysis was based on micro data from a survey in municipalities in and around the Tokyo metropolitan area (N = 3,292). We obtained four key findings. First, the experience of childhood adversity had a substantial negative impact on adulthood SWB. Second, social support and SES significantly mediated the impact of childhood adversity. Third, however, a large proportion of the impact of childhood adversity remained unexplained by their mediation effects. Fourth, social support and SES did not moderate the impact of childhood adversity. Hence, we can conclude that childhood adversity affects adulthood SWB in a relatively independent manner rather than being substantially mediated or moderated by social support or SES. Accordingly, social policies should aim at reducing incidents of childhood maltreatment and bullying in addition to helping people enhance levels of social support and SES in later life.     

A neural network simulator for supercomputers

Connectionist modeling is computationally intensive. Until parallel computers become more widely available, supercomputing resources can be exploited. This paper describes a neural network simulator (NNS) written in FORTRAN for supercomputers. The present simulation engine consists of code for the backpropagation method of changing weights in connectionist models. A file interface reports simulation results in a variety of formats. The file interface also contains an interpreter for an input file through which the network structure is defined, the problem is represented, and various parameters are set. The input-file syntax is described in detail. NNS has been used both as an instructional aid and as a research tool. A simulation of “recovery of unrehearsed associations” is used to illustrate the use of the input file and to demonstrate the performance of NNS. Versions of NNS have been written for the Cray X-MP/48 and for the IBM 3090.