Healthy and Sustainable Food Shopping: A Survey of Intentions and Motivations

Objectives: To determine the relationship between sustainable and healthy food shopping behavior comparing general motivation with the immediate intention to act. Method: We conducted an online survey of 144 staff at the Cork Institute of Technology, Ireland, using a questionnaire based on the Theory of Planned Behavior and the Self-Determination Theory to compute the Behavioral Intention score and the Relative Autonomy Index in relation to healthy and sustainable grocery shopping. Results: The intention to shop healthy food was higher (p < 0.001, Cohen's d = 0.56) than the intention to shop in a sustainable way. A significant intention-action gap was observed for both healthy (p < 0.001, Cohen's d = 0.97) and sustainable grocery shopping (p < 0.001, Cohen's d = 1.78). While there was a significant correlation (p < 0.001) between the longer-term motivations to act in a healthy and sustainable way, this association was not significant (p = 0.16) for the more short-term Behavioral Intention scores. Conclusion and Implications: Health was identified as a more important driver for dietary behavior compared to sustainability. While longer-term motivation shows a stronger correlation between healthy and sustainable grocery shopping, short-term intentions do not follow this pattern as strongly. A significant intention-action gap exists for both, which is stronger for sustainability than for health

A theory‐driven design framework for smartphone applications to support healthy and sustainable grocery shopping

Modeling behavior has been a core topic of Psychology and the Social Sciences since their respective inception as academic disciplines. This has resulted in a fractured landscape of different theories, all addressing different aspects of behavior. At the same time the need to formalize the design of computer and smartphone applications has spawned the field of User Experience (UX). With the convergence of everyday behavior and the use of mobile devices the overlap between these two fields becomes ever more important. In this paper we present a comprehensive model of behavior, integrating five well-established theories, with the aim of creating a design framework for smartphone applications that foster motivation and promote the execution of a target behavior. The operationalization of the approach is demonstrated by showing how to design and implement a prototypical application to support healthy and sustainable grocery shopping behavior. While the framework proposed is not limited to this application, it is used to exemplify the relation with previous design approaches, and the concrete implications of the model-derived framework on its implementation. Our view is that both areas of research can benefit from each other: findings from behavioral theory can inform application design, while at the same time the ubiquitous integration of mobile applications allows to dynamically apply, operationalize, and implement behavioral models into everyday life

A jigsaw puzzle framework for homogenization of high porosity foams

An approach to homogenization of high porosity metallic foams is explored. The emphasis is on the \Alporas{} foam and its representation by means of two-dimensional wire-frame models. The guaranteed upper and lower bounds on the effective properties are derived by the first-order homogenization with the uniform and minimal kinematic boundary conditions at heart. This is combined with the method of Wang tilings to generate sufficiently large material samples along with their finite element discretization. The obtained results are compared to experimental and numerical data available in literature and the suitability of the two-dimensional setting itself is discussed.Comment: 11 pages, 7 figures, 3 table

The more, the better? Learning rate and self-pacing in neurofeedback enhance cognitive performance in healthy adults

Real time electroencephalogram (EEG) based neurofeedback has been shown to be effective in regulating brain activity, thereby modifying cognitive performance and behavior. Nevertheless, individual variations in neurofeedback learning rates limit the overall efficacy of EEG based neurofeedback. In the present study we investigated the effects of learning rate and control over training realized by self-pacing on cognitive performance and electrocortical activity. Using a double-blind design, we randomly allocated 60 participants to either individual upper alpha (IUA) or sham neurofeedback and subsequently to self- or externally paced training. Participants receiving IUA neurofeedback improved their IUA activity more than participants receiving sham neurofeedback. Furthermore, the learning rate predicted enhancements in resting-state activity and mental rotation ability. The direction of this linear relationship depended on the neurofeedback condition being positive for IUA and negative for sham neurofeedback. Finally, self-paced training increased higher-level cognitive skills more than externally paced training. These results underpin the important role of learning rate in enhancing both resting-state activity and cognitive performance. Our design allowed us to differentiate the effect of learning rate between neurofeedback conditions, and to demonstrate the positive effect of self-paced training on cognitive performance in IUA neurofeedback

The more, the better? Learning rate and self-pacing in neurofeedback enhance cognitive performance in healthy adults

Real time electroencephalogram (EEG) based neurofeedback has been shown to be effective in regulating brain activity, thereby modifying cognitive performance and behavior. Nevertheless, individual variations in neurofeedback learning rates limit the overall efficacy of EEG based neurofeedback. In the present study we investigated the effects of learning rate and control over training realized by self-pacing on cognitive performance and electrocortical activity. Using a double-blind design, we randomly allocated 60 participants to either individual upper alpha (IUA) or sham neurofeedback and subsequently to self- or externally paced training. Participants receiving IUA neurofeedback improved their IUA activity more than participants receiving sham neurofeedback. Furthermore, the learning rate predicted enhancements in resting-state activity and mental rotation ability. The direction of this linear relationship depended on the neurofeedback condition being positive for IUA and negative for sham neurofeedback. Finally, self-paced training increased higher-level cognitive skills more than externally paced training. These results underpin the important role of learning rate in enhancing both resting-state activity and cognitive performance. Our design allowed us to differentiate the effect of learning rate between neurofeedback conditions, and to demonstrate the positive effect of self-paced training on cognitive performance in IUA neurofeedback

The forbidden candyfruit. Or the dilemma of wanting tasty foods and a slim body at the same time

editorial reviewe

Perseverative Thinking in Depression and Anxiety

The current study investigated the impact of worry and brooding as moderators of the tripartite model of depression and anxiety (TMDA). We hypothesized that both types of perseverative thinking would moderate the association between negative affectivity (NA) and both anxiety and depression. Complete data sets for this questionnaire survey were obtained from 537 students. Participants’ ages ranged from 16 to 49 years with a mean age of 21.1 years (SD = 3.6). Overall, results from path analyses supported the assumptions of the TMDA, in that NA was a non-specific predictor for both depression and anxiety whilst lack of positive affectivity (PA) was related to depression only. Unexpectedly, perseverative thinking had an effect on the dependency of negative and positive affectivity. Worry was a significant moderator for the path NA–anxiety. All other hypothesized associations were only marginally significant. Alternative pathways as well as methodological implications regarding similarities and differences of the two types of perseverative thinking are discussed