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. Our results showed that MAH feedback significantly increased the enjoyment, engagement, valence and arousal of the emotional response. However, the added value of valence was due to a novelty effect as it was only significantly elevated during initial use, and not after repeated use. Interestingly, the added value of MAH feedback in terms of enjoyment, engagement and arousal remained elevated over the course of five weeks. Moreover, the interview data hinted at substantial individual differences underlying the global trends from the questionnaire data, showing the importance of combining quantitative and qualitative data when testing the UX of MAH feedback.

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-being1. Because our emotional life is inherently time-dynamic2-6, affective scientists argue that, next to how positive or negative we feel on average, patterns of emotional change are informative for mental health7-10. 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. Although this accumulation suggests scientific progress, researchers have not always evaluated (a) how different affect dynamic measures empirically interrelate and (b) what their added value is in the prediction of psychological well-being. Here, we address these questions by analysing affective time series data from 15 studies (n = 1,777). We show that (a) considerable interdependencies between measures exist, suggesting that single dynamics often do not convey unique information, and (b) dynamic measures have little added value over mean levels of positive and negative affect (and variance in these affective states) when predicting individual differences in three indicators of well-being (life satisfaction, depressive symptoms and borderline symptoms). Our findings indicate that conventional emotion research is currently unable to demonstrate independent relations between affect dynamics and psychological well-being.

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. Because we expect individual differences in the model's parameters, as well as differences between HFASD and TD children, we use a hierarchical explanatory approach. A first analysis suggests that children with HFASD are less sensitive to the prototype. A second analysis, involving a mixture component, reveals that the computational model is not appropriate for a subgroup of participants, which implies parameter estimates are not informative for these children. Focusing only on the children for whom the prototype model is appropriate, no clear difference in sensitivity between HFASD and TD children is inferred.

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. While deficits in tasks requiring flexible hypothesis testing are commonly observed in people diagnosed with a major depressive disorder, these deficits are much less commonly observed in people with merely elevated depressive symptoms, and therefore Smith et al.'s (1993) finding deserves further scrutiny. We observed no deficit in performance on the criterial-attribute task in people with above average depressive symptoms. Rather, we found a similar difference in performance on the criterial-attribute versus family-resemblance task between people with high and low depressive symptoms. The absence of a deficit in people with elevated depressive symptoms is consistent with previous findings focusing on different tasks.