Infinite scrolling on social media platforms is designed to encourage prolonged engagement, leading users to spend more time than desired, which can provoke negative emotions. Interventions to mitigate infinite scrolling have shown initial success, yet users become desensitized due to the lack of contextual relevance. Understanding how contextual factors influence intervention effectiveness remains underexplored. We conducted a 7-day user study (N=72) investigating how these contextual factors affect users' reactance and responsiveness to interventions during infinite scrolling. Our study revealed an interplay, with contextual factors such as being at home, sleepiness, and valence playing significant roles in the intervention's effectiveness. Low valence coupled with being at home slows down the responsiveness to interventions, and sleepiness lowers reactance towards interventions, increasing user acceptance of the intervention. Overall, our work contributes to a deeper understanding of user responses toward interventions and paves the way for developing more effective interventions during infinite scrolling.

Automated Urban Air Mobility (UAM) can improve passenger transportation and reduce congestion, but its success depends on passenger trust. While initial research addresses passengers' information needs, questions remain about how to simulate air taxi flights and how these simulations impact users and interface requirements. We conducted a between-subjects study (N=40), examining the influence of motion fidelity in Virtual-Reality-simulated air taxi flights on user effects and interface design. Our study compared simulations with and without motion cues using a 3-Degrees-of-Freedom motion chair. Optimizing the interface design across six objectives, such as trust and mental demand, we used multi-objective Bayesian optimization to determine the most effective design trade-offs. Our results indicate that motion fidelity decreases users' trust, understanding, and acceptance, highlighting the need to consider motion fidelity in future UAM studies to approach realism. However, minimal evidence was found for differences or equality in the optimized interface designs, suggesting personalized interface designs.

The introduction of Highly Automated Vehicles (HAVs) has the potential to increase the independence of blind and visually impaired people (BVIPs). However, ensuring safety and situation awareness when exiting these vehicles in unfamiliar environments remains challenging. To address this, we conducted an interactive workshop with N=5 BVIPs to identify their information needs when exiting an HAV and evaluated three prior-developed low-fidelity prototypes. The insights from this workshop guided the development of PathFinder, a multimodal interface combining visual, auditory, and tactile modalities tailored to BVIP's unique needs. In a three-factorial within-between-subject study with N=16 BVIPs, we evaluated PathFinder against an auditory-only baseline in urban and rural scenarios. PathFinder significantly reduced mental demand and maintained high perceived safety in both scenarios, while the auditory baseline led to lower perceived safety in the urban scenario compared to the rural one. Qualitative feedback further supported PathFinder's effectiveness in providing spatial orientation during exiting.

Urban Air Mobility (UAM) emerges as a potential solution to urban congestion. However, as it lacks integration with existing transportation systems, methods to study its impact are necessary. Traditional empirical approaches are insufficient to study large-scale effects in this not-yet-real context. We developed UAM-SUMO, an extension of the SUMO simulation platform, to simulate the impact of UAM on public transportation, particularly how air taxis affect traffic flow and mode choices. We detail the modifications to SUMO and the UAM operation parameters. We open-source our code at https://github.com/M-Colley/uam-sumo and present a proof-of-concept data collection and analysis for Ingolstadt, Germany.

Mixed Reality (MR) integrates virtual objects with the real world, offering potential but raising concerns about misuse through dark patterns. This study explored the effects of four dark patterns, adapted from prior research, and applied to MR across three targets: places, products, and people. In a two-factorial within-subject study with 74 participants, we analyzed 13 videos simulating MR experiences during a city walk. Results show that all dark patterns significantly reduced user comfort, increased reactance, and decreased the intention to use MR glasses, with the most disruptive effects linked to personal or monetary manipulation. Additionally, the dark patterns of Emotional and Sensory Manipulation and Hiding Information produced similar impacts on the user in MR, suggesting a re-evaluation of current classifications to go beyond deceptive design techniques. Our findings highlight the importance of developing ethical design guidelines and tools to detect and prevent dark patterns as immersive technologies continue to evolve.

Augmented Reality (AR) can alter environments and steer attention. While prior work dominantly focuses on exploring performances of augmentations, this work aims to understand the societal impact of AR in complex social situations. Focusing on prosocial helping behaviour, we created two scenarios and designed five augmentations aiming to motivate a user to help. We wanted to understand (1) the impact on situation perception and (2) the impact on the social structure. In an online video experiment (n=294), we found that augmenting can impact anxiety about the situation and significantly increase the perceived reason to help being directed towards the augmentation. Similarly, we found that the helped rated the "reason" and "thankfulness" significantly higher towards AR than the helper, creating a disagreement around agency and responsibility. We discuss the implications of AR in complex social structures and how responsibility and agency will become important when embedding AR in our social lives.

Today's social media (SM) platforms are toolkits consisting of features with different use cases, some strongly related to habitual and regretful use. Especially Infinite Scrolling (IS) has been reported to make users feel like they are being caught in a loop, regretfully elongating SM sessions. We investigated and defined this loop while unveiling the processes that make users break it. Based on a one-week-long field study (N=46), we unfolded and categorized general reasons for leaving social media and related those to IS. In light of our findings, we argue that SM interventions should not only focus on the app but incorporate the user's context, as most reasons to break SM sessions were not related to the app but the user's general context. Our findings and prior work also indicate the coexistence of multiple loops, which we define as inner (intra-session) loops surrounded by an outer (habitual) loop.