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Social anxiety is a prevalent problem that affects many people with varying severity; digital exposure therapy-which involves controlled exposure to simulations of feared social situations alongside cognitive restructuring-can help treat patients with anxieties. However, the need to personalize exposure scenarios and simulate audiences are barriers to treating social anxieties through digital exposure. In this paper, we propose game streaming as an exposure therapy paradigm for social anxiety, supporting it with data from two studies. We first propose a framework describing requirements for exposure therapy and how game streaming can fulfill them. We select demand and performance visibility from these characteristics to showcase how to manipulate them for experiences of gradual exposure. With Study 1, we provide evidence for these characteristics and support for the framework by showing that a game's demand affected expected fear of streaming games. In Study 2, we show that the prospect of streaming led to elevated fear, a necessary property for effective exposure therapy. Further, we show that the effect of streaming on expected fear was similar for participants who can be considered socially anxious. These findings provide evidence for the essential effect of exposure therapy, which serves as a first step towards the validation of streaming as a social anxiety treatment. Our paper provides an initial, important step towards a novel, broadly applicable, and widely accessible digital approach for the treatment of social anxiety.

Dysfunctional cognitions are a crucial part of depression. Cognitive therapy aims to modify dysfunctional beliefs. Typically, dysfunctional beliefs are questioned, and patients are trained to think of alternative functional beliefs. We developed a computer-assisted, avatar-based adjunct for cognitive therapy that aims to reduce dysfunctional beliefs and symptom severity. Besides, it aims to promote alternative functional beliefs. In a randomized controlled trial with 34 patients diagnosed with major depression currently undergoing inpatient treatment at the university psychiatric hospital in Regensburg, Germany, participants were randomly assigned to receive either treatment as usual (TAU) or computer-assisted avatar-based treatment for dysfunctional beliefs (CAT-DB) in addition to TAU. In CAT-DB participants are faced with a virtual avatar expressing their personal dysfunctional beliefs. Participants are asked to contradict these and express alternative functional beliefs. Assessments of conviction of dysfunctional beliefs, functional beliefs and symptom severity were done shortly before the intervention (pre-treatment), right after the intervention (post-treatment) and 14 days later (follow-up). The reduction in conviction of dysfunctional beliefs and symptom severity, and the increase in conviction of alternative functional beliefs at post-treatment and follow-up were significantly greater for the group receiving CAT-DB. Our study provides an indication in favor of the effectiveness of CAT-DB for depressive patients. It is a simple tool that could support classical cognitive therapy. Further studies at different centres, with larger sample sizes and varying therapeutic contexts are required to prove the effectiveness of our intervention.

Digital biomarkers of mental health issues offer many advantages, including timely identification for early intervention, ongoing assessment during treatment, and reducing barriers to assessment stemming from geography, age, fear, or disparities in access to systems of care. Embedding digital biomarkers into games may further increase the reach of digital assessment. In this study, we explore game-based digital biomarkers for social anxiety, based on interaction with a non-player character (NPC). We show that social anxiety affects a player's accuracy and their movement path in a gaming task involving an NPC. Further, we compared first versus third-person camera perspectives and the use of customized versus predefined avatars to explore the influence of common game interface factors on the expression of social anxiety through in-game movements. Our findings provide new insights about how game-based digital biomarkers can be effectively used for social anxiety, affording the benefits of early and ongoing digital assessment.

Because of its capacity to alter the perception of the surrounding environment, mixed reality technology (MR) has potential for in-the-wild management of anxiety���both chronic (e.g., anxiety disorders) and acute (e.g., situation-induced anxiety). Recently, several components of Cognitive Behavioural Therapy leverage these technologies as part of ongoing cognitive restructuring or as part of relaxation or exposure experiences. However, while most of these researchers focus on the promising benefits of these technologies, a deeper discussion on the potential harm through the misuse of these techniques is still missing. To ignite a conversation about the two sides of the same coin of MR for mental health, we present several scenarios where mixed reality approaches might be used to deceive users rather to support them.

Emphasis effects - visual changes that make certain elements more prominent - are commonly used in information visualization to draw the user's attention or to indicate importance. Although theoretical frameworks of emphasis exist (that link visually diverse emphasis effects through the idea of visual prominence compared to background elements), most metrics for predicting how emphasis effects will be perceived by users come from abstract models of human vision which may not apply to visualization design. In particular, it is difficult for designers to know, when designing a visualization, how different emphasis effects will compare and how to ensure that the user's experience with one effect will be similar to that with another. To address this gap, we carried out two studies that provide empirical evidence about how users perceive different emphasis effects, using three visual variables (colour, size, and blur/focus) and eight strength levels. Results from gaze tracking, mouse clicks, and subjective responses in our first study show that there are significant differences between different kinds of effects and between levels. Our second study tested the effects in realistic visualizations taken from the MASSVIS dataset, and saw similar results. We developed a simple predictive model from the data in our first study, and used it to predict the results in the second; the model was accurate, with high correlations between predictions and real values. Our studies and empirical models provide new information for designers who want to understand how emphasis effects will be perceived by users.

A single abstract from the DHd-2015 Book of Abstracts., Sofern eine editorische Arbeit an dieser Publikation stattgefunden hat, dann bestand diese aus der Eliminierung von Bindestrichen in Überschriften, die aufgrund fehlerhafter Silbentrennung entstanden sind, der Vereinheitlichung von Namen der Autor*innen in das Schema "Nachname, Vorname" und/oder der Trennung von Überschrift und Unterüberschrift durch die Setzung eines Punktes, sofern notwendig., {"references":["http://gams.uni-graz.at/o:dhd2015.abstracts-gesamt","https://github.com/DHd-Verband/DHd-Abstracts-2015"]}