We show that both, explicit and implicit digital behavioral markers can be harnessed for the assessment. In this paper, we investigate whether implicit as well as explicit digital behavioral markers, proposed by prior work, for social anxiety can be used for predicting the level of social anxiety. The characteristics of the movement behavior in-game can be harnessed for the development of digital behavioral markers for the assessment of social anxiety. But recent research suggested digital behavioral markers as a way to deliver cheap and easily accessible digital assessment for social anxiety: As earlier work shows, players with social anxiety show similar behaviors in virtual worlds as in the physical world, including tending to walk farther around other avatars and standing farther away from other avatars. However, socially anxious individuals who seek help face many barriers stemming from geography, fear, or disparities in access to systems of care. The burden of social anxiety can be reduced through accessible assessment that leads to treatment. Although essential, some individuals face major challenges in forming and maintaining social relationships due to the experience of social anxiety. Social relationships are essential for humans neglecting our social needs can reduce wellbeing or even lead to the development of more severe issues such as depression or substance dependency. We conclude by making recommendations for, and noting obstacles to, experimental studies of skill development in digital games. Learning-curve analysis provides the foundation for direct experiments on the factors that affect skill development, which are necessary for a cross-domain cognitive theory of skill. We review existing research on skill development using data from digital games, showing how such work can confirm, challenge, and extend existing claims about the psychology of expertise. Learning-curve analysis allows learning rate, initial performance, and asymptotic performance to be separated out, and so can serve as a tool for reconciling the multiple factors that may affect learning. We argue that existing work, although promising, has yet to take advantage of the potential of game data for understanding skill acquisition, and that to realize this potential, future studies can use the fit of formal learning curves to individual data as a theoretical anchor. Players’ digital traces create data that track the development of skill from novice to expert levels. ![]() Gaming is a domain of profound skill development. Consequently, self-relevant avatars may be used when an increase in commitment is desirable such as in therapeutic or training settings. These results indicate that increasing the degree to which people identify with a cognitive task may induce them to exert greater, reactive inhibitory control. In those participants, the degree of subjectively experienced that self-relevance was associated with improvement in stopping performance over the course of the experiment. In both experiments, the manipulation of self-relevance was effective in a majority of participants as indicated by self-report on the Player-Identification-Scale, and the effect was strongest in participants that completed the self-relevance block first. Each participant completed one block of trials with enhanced self-relevance and one block without enhanced self-relevance, with block order counterbalanced. Both methods create a motivational pull that has been shown to increase motivation and identification. Self-relevance was manipulated by allowing participants to customize their game avatar (Experiment 1) or by introducing a premade, self-referential avatar (Experiment 2). We measured stopping capabilities usingĪ gamified version of the stop-signal paradigm. ![]() We test the influence of self-relevance on stopping specifically if increased self-relevance enhances reactive response inhibition. ![]() One important aspect of cognitive control is the ability to stop a response in progress and motivational aspects, such as self-relevance, which may be able to influence this ability.
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