Cognitive behavior therapy and dialectical behavior therapy for treating obese emotional eaters

This study describes the treatment of obese individuals who rated high on emotional eating using four case studies that involved 22 sessions of either cognitive behavioral therapy (CBT) or dialectical behavioral therapy (DBT). Outcomes measures relating to weight, body mass index, emotional eating, depression, anxiety, and stress were all assessed with each participant prior to each baseline (three weekly sessions), during treatment and posttherapy. At the 8-week follow-up, the two cases that had received DBT had lost 10.1% and 7.6% of their initial body weight, whereas the two cases that had received CBT had lost 0.7% and 0.6% of their initial body weight. The two DBT cases also exhibited reductions in emotional distress, frequency of emotional eating or quantity of food eating in response to emotions, whereas the two CBT cases showed no overall reductions in these areas. Important processes from all four cases are described as are the implications to clinicians for developing more effective interventions for obese clients who engage in emotional eating.

Sympathy for the devil [Book reviewed : "Tasmanian Devil: A Unique and Threatened Animal" by David Owen and David Pemberton]

Two representations have dominated public perceptions of the largest living marsupial carnivore, the Tasmanian devil. One is the voracious, hurricane-like innocent savage Taz of Looney Tunes cartoon fame. The other, familiar in nineteenth- and twentieth-century rural Tasmania, is the ferocious predator and scavenger that wantonly kills livestock — and perhaps even people, should they become immobilized in the wilderness at night. Devils can take prey nearly three times their size and eat more than a third of their body weight in a sitting. Even so, it is hard to imagine how this species, being only slightly larger than a fox terrier, could be so maligned in name and image...

Updating and verification for multi-scale finite element model of structure behavior

The method on concurrent multi-scale model of structural behavior (CMSM-of-SB) for the purpose of structural health monitoring including model updating and validating has been studied. The detailed process of model updating and validating is discussed in terms of reduced scale specimen of the steel box girder in longitudinal stiffening truss of a long span bridge. Firstly, some influence factors affecting the accuracy of the CMSM-of-SB including the boundary restraint regidity, the geometry and material parameters on the toe of the weld and its neighbor are analyzed using sensitivity method. Then, sensitivity-based model updating technology is adopted to update the developed CMSM-of-SB and model verification is carried out through calculating and comparing stresses on different locations under various loading from dynamic characteristic and static response. It can be concluded that the CMSM-of-SB based on the substructure method is valid.

The thermal behavior of kaolinite intercalation complexes : a review

The kaolinite intercalation and its application in polymer-based functional composites have attracted great interest, both in industry and in academia fields, since they frequently exhibit remarkable improvements in materials properties compared with the virgin polymer or conventional micro and macro-composites. Also of significant interest regarding the kaolinite intercalation complex is its thermal behavior and decomposition. This is because heating treatment of intercalated kaolinite is necessary for its further application, especially in the field of plastic and rubber industry. Although intercalation of kaolinite is an old and ongoing research topic, there is a limited knowledge available on kaolinite intercalation with different reagents, the mechanism of intercalation complex formation as well as on thermal behavior and phase transition. This review attempts to summarize the most recent achievements in the thermal behavior study of kaolinite intercalation complexes obtained with the most common reagents including potassium acetate, formamide, dimethyl sulfoxide, hydrazine and urea. At the end of this paper, the further work on kaolinite intercalation complex was also proposed.

Education for strategic environmental behavior

This article reviews four bodies of research that shed light on how to promote active care for the environment in children and youth: research on sources of proenvironmental behavior, socialization for democratic skills and values, the development of a personal sense of competence, and the development of collective competence. The article begins with an overview of studies of formative childhood experiences reported by environmental activists and educators, followed by correlational and experimental studies with young people regarding factors associated with their taking action for the environment. Because behaviors with the largest potential benefits for the environment require political engagement, the article also reviews experiences associated with young people’s interest and engagement in public issues. Action for the environment in the home or in public arena like schools and communities requires a personal sense of competence and a sense of collective competence, or confidence in one’s ability to achieve goals by working with a group. Therefore experiences that promote the development of these assets are summarized as well. The conclusion compares major findings in these different fields and discusses implications for environmental educators.

Predictors of young people’s charitable intentions to donate money : an extended theory of planned behavior perspective

An extended theory of planned behavior (TPB) was used to predict young people’s intentions to donate money to charities in the future. Students (N = 210; 18-24 years) completed a questionnaire assessing their attitude, subjective norm, perceived behavioral control [PBC], moral obligation, past behavior and intentions toward donating money. Regression analyses revealed the extended TPB explained 61% of the variance in intentions to donate money. Attitude, PBC, moral norm, and past behavior predicted intentions, representing future targets for charitable giving interventions.

Effects of impulsive sensation seeking, aggression and risk-taking behavior on the vulnerability of motorcyclists

While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood.The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. To explore the rider behavior, a questionnaire containing 61-items of impulsive sensation seeking, aggression, and risk-taking behavior was developed. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk has been developed. Results show that crash-involved motorcyclists score higher in all three behavioral traits. Aggressive and high risk-taking motorcyclists are more likely to fall under the high vulnerable group while impulsive sensation seeking is not found to be significant. Defining personality types from aggression and risk-taking behavior, “Extrovert” and “Follower” personality type of motorcyclists are more prone to crashes. The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business

The influence of motorcyclist behavior in crash involvement

Introduction: In Singapore, motorcycle crashes account for 50% of traffic fatalities and 53% of injuries. While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood. The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. Methods: To explore the rider behavior, a 61-item questionnaire examining sensation seeking (Zuckerman et al., 1978), impulsiveness (Eysenck et al., 1985), aggressiveness (Buss & Perry, 1992), and risk-taking behavior (Weber et al., 2002) was developed. A total of 240 respondents with at least one year riding experience form the sample that relate behavior to their crash history, traffic penalty awareness, and demographic characteristics. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk was developed. Results and Discussions: Crash-involved motorcyclists scored higher in impulsive sensation seeking, aggression and risk-taking behavior. Aggressive and high risk-taking motorcyclists were respectively 1.30 and 2.21 times more likely to fall under the high crash involvement group while impulsive sensation seeking was not found to be significant. Based on the scores on risk-taking and aggression, the motorcyclists were clustered into four distinct personality combinations namely, extrovert (aggressive, impulsive risk-takers), leader (cautious, aggressive risk-takers), follower (agreeable, ignorant risk-takers), and introvert (self-consciousness, fainthearted risk-takers). “Extrovert” motorcyclists were most prone to crashes, being 3.34 times more likely to involve in crash and 8.29 times more vulnerable than the “introvert”. Mediating factors like demographic characteristics, riding experience, and traffic penalty awareness were found not to be significant in reducing crash risk. Conclusion: The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business.

Validation of a food behavior questionnaire for male blue collar workers

During nutrition intervention programs, some form of dietary assessment is usually necessary. This dietary assessment can be for: initial screening; development of appropriate programs and activities; or, evaluation. Established methods of dietary assessment are not always practical, nor cost effective in such interventions, therefore an abbreviated dietary assessment tool is needed. The Queensland Nutrition Project developed such a tool for male Blue Collar Workers, the Food Behaviour Questionnaire, consisting of 27 food behaviour related questions. This tool has been validated in a sample of 23 men, through full dietary assessment obtained via food frequency questionnaires and 24 hour dietary recalls. Those questions which correlated poorly with the full dietary assessment were deleted from the tool. In all, 13 questions was all that was required to distinguish between high and low dietary intakes of particular nutrients. Three questions when combined had correlations with refined sugar between 0.617 and 0.730 (p<0.005); four questions when combined had correlations with dietary fibre as percentage of energy of 0.45 (p<0.05); five questions when combined had a correlation with total fat of 0.499 (p<0.05); and, 4 questions when combined had a correlation with saturated fat of between 0.451 and 0.589 (p<0.05). A significant correlation could not be found for food behaviour questions with respect to dietary sodium. Correlations for fat as a function of energy could not be found.

A toolbox for animal call recognition

Monitoring the natural environment is increasingly important as habit degradation and climate change reduce theworld’s biodiversity.We have developed software tools and applications to assist ecologists with the collection and analysis of acoustic data at large spatial and temporal scales.One of our key objectives is automated animal call recognition, and our approach has three novel attributes. First, we work with raw environmental audio, contaminated by noise and artefacts and containing calls that vary greatly in volume depending on the animal’s proximity to the microphone. Second, initial experimentation suggested that no single recognizer could dealwith the enormous variety of calls. Therefore, we developed a toolbox of generic recognizers to extract invariant features for each call type. Third, many species are cryptic and offer little data with which to train a recognizer. Many popular machine learning methods require large volumes of training and validation data and considerable time and expertise to prepare. Consequently we adopt bootstrap techniques that can be initiated with little data and refined subsequently. In this paper, we describe our recognition tools and present results for real ecological problems.