Individual differences and weight bias: Do people with an anti-fat bias have a pro-thin bias?

While levels of weight bias vary among individuals, it is not clear why one person possesses stronger anti-fat attitudes than another person. This investigation examined whether individual differences commonly associated with greater anti-fat bias are also associated with a greater preference for thinness among people of varying levels of weight. Young adults (62% women; 84% Caucasian) recruited from psychology classes (N = 308) rated four male and female figures with approximate BMIs of 18.5, 25, 30, and 40, on measures of dislike and personality characteristics and completed measures assessing weight controllability, attitudes toward the obese, and perceptual reliance. Greater negative attitudes, weight controllability beliefs, and perceptual reliance were positively associated with greater dislike and negative personality attributes among obese/severely obese figures, but inversely related among low normal weight figures. Individuals who judge others based on physical features or who view obesity as controllable evidence greater weight bias and a stronger preference for thin body types.     

Putting category learning in order: Category structure and temporal arrangement affect the benefit of interleaved over blocked study

Recent research in inductive category learning has demonstrated that interleaved study of category exemplars results in better performance than does studying each category in separate blocks. However, the questions of how the category structure influences this advantage and how simultaneous presentation interacts with the advantage are open issues. In this article, we present three experiments. The first experiment indicates that the advantage of interleaved over blocked study is modulated by the structure of the categories being studied. More specifically, interleaved study results in better generalization for categories with high within- and between-category similarity, whereas blocked presentation results in better generalization for categories with low within- and between-category similarity. In Experiment 2, we present evidence that when presented simultaneously, between-category comparisons (interleaved presentation) result in a performance advantage for high-similarity categories, but no differences were found for low-similarity categories. In Experiment 3, we directly compared simultaneous and successive presentation of low-similarity categories. We again found an overall benefit for blocked study with these categories. Overall, these results are consistent with the proposal that interleaving emphasizes differences between categories, whereas blocking emphasizes the discovery of commonalities among objects within the same category.     

Multiple group membership influences face-recognition: Recall and neurological evidence

The limited face-recognition research involving targets categorizable on multiple dimensions has provided contradictory evidence as to how partial-ingroup members are processed and recognized. This research demonstrates that partial-ingroup members are recognized in a manner distinct from double-ingroup and double-outgroup targets. Specifically, when race and university-affiliation are crossed, university-affiliation does not influence recognition for own-race targets, but does for other-race targets, in that other-race/own-university targets are recalled more accurately than other-race/other-university targets. The neurological mechanisms involved in the effect are explored through the inclusion of electroencephalography.     

Age group differences in self-reported aggressive driving perpetration and victimization

Aim

This study examined whether the predictors of self-reported aggressive driving perpetration and victimization vary across age groups.

Method

Based on data from a general-population telephone survey conducted from July 2002 through June 2005, three groups of drivers were examined: 18–34 year-olds (N = 1522), 35–54 year-olds (N = 2726), and 55 years of age or older (N = 1883). For each age group sample, logistic regression analyses examined self-reported aggressive driving perpetration and victimization in the last 12 months by measures of driving exposure, heavy drinking, cannabis use, and drinking-driving, while controlling for demographic factors.

Results

The prevalence of aggressive driving perpetration within the past year was highest for the youngest age group (51%), followed by the middle-aged group (37%), and then the oldest age group (18%). The same pattern of results was found for prevalence of aggressive driving victimization (54%, 47%, and 31%, respectively). Controlling for demographic factors, the predictors of perpetration were generally consistent across the age groups. The logistic regression model for the youngest drivers revealed that those who reported stressful driving, heavy drinking, and cannabis use had significantly increased odds of reporting perpetration of aggressive driving. For middle-aged and older drivers, stressful driving, driving on busy roads, cannabis use, and driving after drinking were associated with perpetration. In addition, increased mileage contributed to perpetration in the oldest group. The findings for victimization by aggressive driving were similar. The logistic regression model for the youngest age group identified stressful driving, cannabis use, and higher annual mileage as being associated with victimization. For the oldest age group, these same variables were significant predictors of victimization, in addition to driving on busy roads. The logistic regression for the middle-aged group identified the same predictors as that of the oldest age group; however, interestingly driving after drinking was found to predict lower victimization among middle-aged drivers.

Conclusions

Although the prevalence of aggressive driving perpetration and victimization declined with age, the factors that contributed to aggressive driving remained generally stable across the lifespan. The results suggest that efforts to reduce aggressive driving among young drivers may prove to be effective for drivers from all age groups.     

A Computer-Aided Affective Content Analysis of Nanotechnology Newspaper Articles

This paper explores the application of an affective content analysis to a selection of nanotechnology news articles gathered from selected newspapers. Thematic content analyses dominate current efforts to mine large text collections of popular science media; the addition of an affective analysis element can yield useful information to supplement future content analysis efforts. Using Whissell’s Dictionary of Affect in Language, the analysis rates news articles gathered over a twenty-two year period for their pleasantness, activeness, and imagery, determining the mean affective tone in each category for the entire collection, four ‘content themes’ (business, national security, health, and environment), and the change in affective tone over the twenty-two year period these articles represent. Whereas the entire collection analyzed as a whole rates very similarly to the average found for everyday English language use and the ‘content themes’ show similar results, the change in affective tone over the years has been both significant and striking. A sample of results from three years of the twenty-two year period is then qualitatively explored to demonstrate to the reader the connection between the quantitative results of the Dictionary and the qualitative effect of the article’s word use and phrasing. The paper ends with a review of the technique’s success, implications for policymaking and public dialogue, and avenues for future use.     

Role of serial order in the impact of talker variability on short-term memory: testing a perceptual organization-based account

In two experiments, we examined the impact of the degree of match between sequential auditory perceptual organization processes and the demands of a short-term memory task (memory for order vs. item information). When a spoken sequence of digits was presented so as to promote its perceptual partitioning into two distinct streams by conveying it in alternating female (F) and male (M) voices (FMFMFMFM)—thereby disturbing the perception of true temporal order—recall of item order was greatly impaired (as compared to recall of item identity). Moreover, an order error type consistent with the formation of voice-based streams was committed more quickly in the alternating-voice condition (Exp. 1). In contrast, when the perceptual organization of the sequence mapped well onto an optimal two-group serial rehearsal strategy—by presenting the two voices in discrete clusters (FFFFMMMM)—order, but not item, recall was enhanced (Exp. 2). The results are consistent with the view that the degree of compatibility between perceptual and deliberate sequencing processes is a key determinant of serial short-term memory performance. Alternative accounts of talker variability effects in short-term memory, based on the concept of a dedicated phonological short-term store and a capacity-limited focus of attention, are also reviewed.     

TRACX: a recognition-based connectionist framework for sequence segmentation and chunk extraction

Individuals of all ages extract structure from the sequences of patterns they encounter in their environment, an ability that is at the very heart of cognition. Exactly what underlies this ability has been the subject of much debate over the years. A novel mechanism, implicit chunk recognition (ICR), is proposed for sequence segmentation and chunk extraction. The mechanism relies on the recognition of previously encountered subsequences (chunks) in the input rather than on the prediction of upcoming items in the input sequence. A connectionist autoassociator model of ICR, truncated recursive autoassociative chunk extractor (TRACX), is presented in which chunks are extracted by means of truncated recursion. The performance and robustness of the model is demonstrated in a series of 9 simulations of empirical data, covering a wide range of phenomena from the infant statistical learning and adult implicit learning literatures, as well as 2 simulations demonstrating the model's ability to generalize to new input and to develop internal representations whose structure reflects that of the items in the input sequence. TRACX outperforms PARSER (Perruchet & Vintner, 1998) and the simple recurrent network (SRN, Cleeremans & McClelland, 1991) in matching human sequence segmentation on existing data. A new study is presented exploring 8-month-olds' use of backward transitional probabilities to segment auditory sequences.     

Effects of electromyostimulation on knee extensors and flexors strength and steadiness in older adults

It is known that electromyostimulation (EMS) alone or superimposed over voluntary contraction (EV) can effectively improve muscle strength. However, the effect of this type of training on the ability to control force production at submaximal levels is unknown. The authors examined the effects of EV training on steadiness in force production of knee extensors and flexors in older adults. Forty participants, including 20 men and 20 women, 60-77 years of age, were randomly allocated into a control group (CG) and an electromyostimulation superimposed over voluntary contraction (EVG) group. The EVG performed 30 bilateral isometric knee extension and flexion contractions per session, 3 training sessions per week, for 6 weeks. The variations in force production, expressed in absolute (standard deviation [SD]) and relative (coefficient of variation [CV]) terms, were assessed in isometric contractions at 5%, 15% and 25% maximal voluntary contraction (MVC) levels. Results indicated that MVC increased in knee extension and flexion in EVG (p < .05) after the training; steadiness CV also improved at 15% MVC in knee flexion (p < .05) but no significant changes were found in knee extension and steadiness SD. The training-induced changes in MVC were not correlated to steadiness CV that might indicate different mechanisms underlying these adaptations.     

Evaluating a brief measure of social self-efficacy among U.S. adolescents

Preliminary data were collected to evaluate the performance of a social self-efficacy measure among 4,061 public high school adolescents. Principal-axis factor analysis was followed by a 4-way between-groups analysis of variance (ANOVA) to test for differences in the Total score means on selected demographic estimates and their interactions. Relations between the Total score and selected risk behaviors were examined through a series of one-way ANOVAs and the Tukey HSD test. Factor analysis results suggested a one-factor model best explained the factor structure of the scale items (factor loading range = .64 - .77, eigenvalue = 4.05, h(2) = .51). Females reported a significantly higher mean Total social self-efficacy rating than males, while White students reported a significantly higher mean Total social self-efficacy rating than Black and Asian students. Statistically significant lower mean Total social self-efficacy ratings were also noted for those who reported physical fighting, avoiding school, and being bullied.