Does a brief mindfulness intervention counteract the detrimental effects of ego-depletion in basketball free throw under pressure?

Research has shown that a brief mindfulness intervention may counteract the depleting effects of an emotion suppression task upon a subsequent psychological task that requires self-control. However, the effects of a brief mindfulness intervention on perceptual–motor tasks particularly in stressful situations have not yet been examined. The purpose of this study was to investigate whether a brief mindfulness intervention can counteract the detrimental effects of ego-depletion in basketball free throw performance under pressure. Seventy-two basketball players (mean age = 28.6 ± 4.0 yrs) were randomly assigned to one of the following 4 groups: depletion/mindfulness, no depletion/mindfulness, depletion/no mindfulness and control (no depletion/no mindfulness). The mindfulness intervention consisted of a 15-min breathe and body mindfulness audio exercise, while the control condition (no mindfulness) listened to an audio book. A modified Stroop color-word task was used to manipulate self–control and induce ego depletion. Participants performed 30 free throws before and after the experimental manipulations. Results showed that basketball players’ free throw performance decreased after ego-depletion, but when ego-depletion was followed by the mindfulness intervention, free throw performance was maintained at a level similar to the control group. Our results indicate that a brief mindfulness intervention mitigates the effects of ego depletion in a basketball free-throw task

Toward Order-of-Magnitude Cascade Prediction

When a piece of information (microblog, photograph, video, link, etc.) starts to spread in a social network, an important question arises: will it spread to "viral" proportions -- where "viral" is defined as an order-of-magnitude increase. However, several previous studies have established that cascade size and frequency are related through a power-law - which leads to a severe imbalance in this classification problem. In this paper, we devise a suite of measurements based on "structural diversity" -- the variety of social contexts (communities) in which individuals partaking in a given cascade engage. We demonstrate these measures are able to distinguish viral from non-viral cascades, despite the severe imbalance of the data for this problem. Further, we leverage these measurements as features in a classification approach, successfully predicting microblogs that grow from 50 to 500 reposts with precision of 0.69 and recall of 0.52 for the viral class - despite this class comprising under 2\% of samples. This significantly outperforms our baseline approach as well as the current state-of-the-art. Our work also demonstrates how we can tradeoff between precision and recall.Comment: 4 pages, 15 figures, ASONAM 2015 poster pape