AR You on Track? Investigating Effects of Augmented Reality Anchoring on Dual-Task Performance While WalkingWith the increasing spread of AR head-mounted displays suitable for everyday use, interaction with information becomes ubiquitous, even while walking. However, this requires constant shifts of our attention between walking and interacting with virtual information to fulfill both tasks adequately. Accordingly, we as a community need a thorough understanding of the mutual influences of walking and interacting with digital information to design safe yet effective interactions. Thus, we systematically investigate the effects of different AR anchors (hand, head, torso) and task difficulties on user experience and performance. We engage participants (n=26) in a dual-task paradigm involving a visual working memory task while walking. We assess the impact of dual-tasking on both virtual and walking performance, and subjective evaluations of mental and physical load. Our results show that head-anchored AR content least affected walking while allowing for fast and accurate virtual task interaction, while hand-anchored content increased reaction times and workload.2025JRJulian Rasch et al.LMU MunichFull-Body Interaction & Embodied InputAR Navigation & Context AwarenessCHI
Virtual Body Swapping: A VR-Based Approach to Embodied Third-Person Self-Processing in Mind-Body TherapyVirtual reality (VR) offers various opportunities for innovative therapeutic approaches, especially regarding self-related mind-body interventions. We introduce a VR body swap system enabling multiple users to swap their perspectives and appearances and evaluate its effects on virtual sense of embodiment (SoE) and perception- and cognition-based self-related processes. In a self-compassion-framed scenario, twenty participants embodied their personalized, photorealistic avatar, swapped bodies with an unfamiliar peer, and reported their SoE, interoceptive awareness (perception), and self-compassion (cognition). Participants' experiences differed between bottom-up and top-down processes. Regarding SoE, their agency and self-location shifted to the swap avatar, while their top-down self-identification remained with their personalized avatar. Further, the experience positively affected interoceptive awareness but not self-compassion. Our outcomes offer novel insights into the SoE in a multiple-embodiment scenario and highlight the need to differentiate between the different processes in intervention design. They raise concerns and requirements for future research on avatar-based mind-body interventions.2024NDNina Döllinger et al.University of WürzburgImmersion & Presence ResearchIdentity & Avatars in XRVR Medical Training & RehabilitationCHI
52 Weeks Later: Attitudes Towards COVID-19 Apps for Different Purposes Over TimeThe COVID-19 pandemic has prompted countries around the world to introduce smartphone apps to support disease control efforts. Their purposes range from digital contact tracing to quarantine enforcement to vaccination passports, and their effectiveness often depends on widespread adoption. While previous work has identified factors that promote or hinder adoption, it has typically examined data collected at a single point in time or focused exclusively on digital contact tracing apps. In this work, we conduct the first representative study that examines changes in people’s attitudes towards COVID-19-related smartphone apps for five different purposes over the first 1.5 years of the pandemic. In three survey rounds conducted between Summer 2020 and Summer 2021 in the United States and Germany, with approximately 1,000 participants per round and country, we investigate people’s willingness to use such apps, their perceived utility, and people’s attitudes towards them in different stages of the pandemic. Our results indicate that privacy is a consistent concern for participants, even in a public health crisis, and the collection of identity-related data significantly decreases acceptance of COVID-19 apps. Trust in authorities is essential to increase confidence in government-backed apps and foster citizens’ willingness to contribute to crisis management. There is a need for continuous communication with app users to emphasize the benefits of health crisis apps both for individuals and society, thus counteracting decreasing willingness to use them and perceived usefulness as the pandemic evolves.2023MKMarvin Kowalewski et al.COVID-19 + CSCWCSCW
Are Embodied Avatars Harmful to our Self-Experience? The Impact of Virtual Embodiment on Body AwarenessVirtual Reality (VR) allows us to replace our visible body with a virtual self-representation (avatar) and to explore its effects on our body perception. While the feeling of owning and controlling a virtual body is widely researched, how VR affects the awareness of internal body signals (body awareness) remains open. Forty participants performed moving meditation tasks in reality and VR, either facing their mirror image or not. Both the virtual environment and avatars photorealistically matched their real counterparts. We found a negative effect of VR on body awareness, mediated by feeling embodied in and changed by the avatar. Further, we revealed a negative effect of a mirror on body awareness. Our results indicate that assessing body awareness should be essential in evaluating VR designs and avatar embodiment aiming at mental health, as even a scenario as close to reality as possible can distract users from their internal body signals.2023NDNina Döllinger et al.University of WürzburgImmersion & Presence ResearchIdentity & Avatars in XRCHI
Impact of Annotator Demographics on Sentiment Dataset LabelingAs machine learning methods become more powerful and capture more nuances of human behavior, biases in the dataset can shape what the model learns and is evaluated on. This paper explores and attempts to quantify the uncertainties and biases due to \textit{annotator} demographics when creating sentiment analysis datasets. We ask $>$1000 crowdworkers to provide their demographic information and annotations for multimodal sentiment data and its component modalities. We show that demographic differences among annotators impute a significant effect on their ratings, and that these effects also occur in each component modality. We compare predictions of different state-of-the-art multimodal machine learning algorithms against annotations provided by different demographic groups, and find that changing annotator demographics can cause $>$4.5\% in accuracy difference when determining positive versus negative sentiment. Our findings underscore the importance of accounting for crowdworker attributes, such as demographics, when building datasets, evaluating algorithms, and interpreting results for sentiment analysis.2022YDZijian Ding et al.Data, Bias and FairnessCSCW
Impact of Annotator Demographics on Sentiment Dataset LabelingAs machine learning methods become more powerful and capture more nuances of human behavior, biases in the dataset can shape what the model learns and is evaluated on. This paper explores and attempts to quantify the uncertainties and biases due to \textit{annotator} demographics when creating sentiment analysis datasets. We ask $>$1000 crowdworkers to provide their demographic information and annotations for multimodal sentiment data and its component modalities. We show that demographic differences among annotators impute a significant effect on their ratings, and that these effects also occur in each component modality. We compare predictions of different state-of-the-art multimodal machine learning algorithms against annotations provided by different demographic groups, and find that changing annotator demographics can cause $>$4.5\% in accuracy difference when determining positive versus negative sentiment. Our findings underscore the importance of accounting for crowdworker attributes, such as demographics, when building datasets, evaluating algorithms, and interpreting results for sentiment analysis.2022YDYi Ding et al.Data, Bias and FairnessCSCW
There Is No First- or Third-Person View in Virtual Reality: Understanding the Perspective ContinuumModern games make creative use of First- and Third-person perspectives (FPP and TPP) to allow the player to explore virtual worlds. Traditionally, FPP and TPP perspectives are seen as distinct concepts. Yet, Virtual Reality (VR) allows for flexibility in choosing perspectives. We introduce the notion of a perspective continuum in VR, which is technically related to the camera position and conceptually to how users perceive their environment in VR. A perspective continuum enables adapting and manipulating the sense of agency and involvement in the virtual world. This flexibility of perspectives broadens the design space of VR experiences through deliberately manipulating perception. In a study, we explore users' attitudes, experiences and perceptions while controlling a virtual character from the two known perspectives. Statistical analysis of the empirical results shows the existence of a perspective continuum in VR. Our findings can be used to design experiences based on shifts of perception.2022MHMatthias Hoppe et al.LMU MunichImmersion & Presence ResearchIdentity & Avatars in XRCHI