Influence of Quadrato Motor Training on Salivary proNGF and proBDNF

Previous studies demonstrated exercise-induced modulation of neurotrophins, such as Nerve Growth Factor (NGF) and Brain-Derived Neurotrophic Factor (BDNF). Yet, no study that we are aware of has examined their change as a function of different training paradigms. In addition, the understanding of the possible training-induced relationship between NGF and BDNF change is still lacking. Consequently, in the current study we examined the effect of a Walking Training (WT) and of Quadrato Motor Training (QMT) on NGF and BDNF precursors (proNGF and proBDNF). QMT is a specifically structured sensorimotor training that involves sequences of movements based on verbal commands, that was previously reported to improve spatial cognition, reflectivity, creativity as well as emotion regulation and general self-efficacy. In addition, QMT was reported to induce electrophysiological and morphological changes, suggesting stimulation of neuroplasticity processes. In two previous independent studies we reported QMT-induced changes in the salivary proNGF and proBDNF levels. Our present results demonstrate that following 12 weeks of daily QMT practice, proNGF level increases while proBDNF showed no significant change. More importantly, while no correlation between the two neurotrophins prior to training was detectable, there was a significant correlation between change in proNGF and proBDNF levels. Taken together the current results suggest that the two neurotrophins undergo a complex modulation, likely related to the different pathways by which they are produced and regulated. Since variations of these neurotrophins have been previously linked to depression, stress and anxiety, the current study may have practical implications and aid in understanding the possible physiological mechanisms that mediate improved well-being, and the dynamic change of neurotrophins as a result of training

Human-Computer Interaction in Health and Wellness: Research and Publication Opportunities

In this introduction, we address three distinct aspects of the special issue topic “human-computer interaction (HCI) in health and wellness”. First, we assess the trajectory of HCI research in health topics in top HCI journals during the 1995-2012 period. We then contrast this overall publication trajectory with the health sector component of gross domestic product (GDP)—applied as a proxy measure of social need—across seven countries that are top producers of HCI research. Second, we describe how one can use the human-technology innovation framework to understand the range of settings in which HCI research in health topics can be conducted. Grounded in this framework, we propose a structure to categorize health related HCI publication and to identify gaps in this research. Third, we apply the proposed structure to categorize and introduce five papers chosen to represent the special issue topic

Contrôle de gestion et légitimité dans le secteur public : revue bibliométrique

Pour assurer une amélioration de la performance de la gestion publique, le NMP, et par l’inspiration du secteur privé, a contribué à l'introduction des pratiques de contrôle de gestion dans les organismes publics, par une série de réformes institutionnelles. Toutefois, la mise en œuvre effective des systèmes de contrôle de gestion dans ce secteur s'avère être une mission délicate, entravée de plusieurs obstacles dont la remise en cause de la légitimité de cette fonction. Et c’est pour cette raison que les contrôleurs de gestion publique sont menés à déployer un nombre de stratégies de légitimation pour faire preuve de leur légitimité fonctionnelle et personnelle. Provenant de cette problématique centrale, qu’est la légitimité du contrôle de gestion dans le secteur public, cet article vise à analyser la production scientifique liant entre les concepts de légitimité et de contrôle de gestion ; revue bibliométrique qui s’est basée sur le Web Of Science comme source de données, et qui a exploité le logiciel VOSViewer et les traitements bibliométriques qu’il assure, notamment l’analyse co-auteur, l’analyse de citation, l’analyse de co-citation et celle de la co-occurrence des mots clés. &nbsp

Moods and Their Relevance to Systems Usage Models within Organizations: An Extended Framework

Traditionally, information systems (IS) usage models have examined user behavior within a cognitive framework, that is, these models suggest that a user’s cognition influences his/her IS usage behavior. Research over the past three decades has shown that mood, one’s global feeling state at a given time, can significantly impact a person’s cognitive processes. Mood effects on cognition are particularly relevant to organizational settings. Because moods are pervasive, they provide a stable context for cognitive processes that influence behavior at work; therefore, the inclusion of mood in individual IS usage models that support organizational tasks is both relevant and necessary. Because positive mood can enhance performance under certain circumstances, mood management is also relevant to IS usage models. Thus, we highlight how moods can be managed via IS and propose a model that takes into account users’ moods at the time they work with a system. This model provides an extended framework for incorporating relevant mood literature into current IS usage behavioral models. With this model, researchers can examine certain aspects of the model (such as how IS design can influence user feeling states or how users’ moods can impact their behavior), or conduct more comprehensive research using the entire model. This model can contribute to theory by providing a more complete picture of user behavior, and contribute to practice by helping mangers plan for desired outcomes

Using Audio Augmented Reality to Support Decision Making

Audio augmented reality (AR) is becoming increasingly popular as a medium for communicating additional layers of information about a user’s environment. This extended abstract reports the preliminary results of a study examining the impact of an audio AR enabled mobile decision aid, FoodGlance, on users’ decision quality as well as their overall experience of the decision-making process. Research shows that people often find nutrition facts labels confusing and difficult to use [1]. FoodGlance was designed to make it easier for people to choose healthy products based on their dietary needs and preferences. FoodGlance uses OCR technology to extract textual information from nutrition fact labels and then translates it into simple feedback [2]. In this study, the feedback was provided in three different ways: audio AR, visual, and the combination of the two. Audio AR was provided via Bose glasses. Visual feedback, consistent with our previous study, was displayed as a pop-up on the smartphone showing thumbs up (good amount) or thumps down (bad amount) for sugar, fat, and protein separately [2]. For this study we used the FDA’s 5-20 percent daily value rule to design feedback. The feedback engine in FoodGlance, however, is not limited to this rule and can be modified by users