From Initial Encounter With Mid-Air Haptic Feedback to Repeated Use: The Role of the Novelty Effect in User Experience.

Mid-air haptic (MAH) feedback is an interesting means to provide augmented haptic feedback for gesture-based technology as it enables a sense of touch without physical contact with an actuator. Although quite some work already investigated the user experience (UX) of MAH feedback during initial encounter, we are not aware of studies testing the UX after repeated use, with regard to both pragmatic and hedonic UX, as well as emotional reactions. In this article, we tested how the UX of MAH feedback changed over the course of five weeks by collecting both questionnaire as well as interview data of 31 participants.

Complex affect dynamics add limited information to the prediction of psychological well-being.

Over the years, many studies have demonstrated a relation between emotion dynamics and psychological well-being. Because our emotional life is inherently time-dynamic, affective scientists argue that, next to how positive or negative we feel on average, patterns of emotional change are informative for mental health. This growing interest initiated a surge in new affect dynamic measures, each claiming to capture a unique dynamical aspect of our emotional life, crucial for understanding well-being.

Depressive Symptoms and Category Learning: A Preregistered Conceptual Replication Study.

We present a fully preregistered, high-powered conceptual replication of Experiment 1 by Smith, Tracy, and Murray (1993). They observed a cognitive deficit in people with elevated depressive symptoms in a task requiring flexible analytic processing and deliberate hypothesis testing, but no deficit in a task assumed to require more automatic, holistic processing. Specifically, they found that individuals with depressive symptoms showed impaired performance on a criterial-attribute classification task, requiring flexible analysis of the attributes and deliberate hypothesis testing, but not on a family-resemblance classification task, assumed to rely on holistic processing.

Sensitivity to the prototype in children with high-functioning autism spectrum disorder: An example of Bayesian cognitive psychometrics.

We present a case study of hierarchical Bayesian explanatory cognitive psychometrics, examining information processing characteristics of individuals with high-functioning autism spectrum disorder (HFASD). On the basis of previously published data, we compare the classification behavior of a group of children with HFASD with that of typically developing (TD) controls using a computational model of categorization. The parameters in the model reflect characteristics of information processing that are theoretically related to HFASD.