Evidence for Shifting Cognitive Strategies when Icons Appear in Unexpected Locations.

OBJECTIVE: The present study examines the cognitive effects of placing icons in unexpected spatial locations within websites. BACKGROUND: Prior research has revealed evidence for cognitive conflict when web icons occur in unexpected locations (e.g., cart, top left), generally consistent with a dynamical systems models. Here, we compare the relative strength of evidence for both dual and dynamical systems models. METHODS: Participants clicked on icons located in either expected (e.g., cart, top right) or unexpected (e.g., cart, top left) locations while mouse trajectories were continuously recorded. Trajectories were classified according to prototypes associated with each cognitive model. The dynamical systems model predicts curved trajectories, while the dual-systems model predicts straight and change of mind trajectories. RESULTS: Trajectory classification revealed that curved trajectories increased (+11%), while straight and change of mind trajectories decreased (-12%) when target icons occurred in unexpected locations (p < .001). CONCLUSION: Rather than employing a single cognitive strategy, users shift from a primarily dual-systems to dynamical systems strategy when icons occur in unexpected locations. APPLICATION: Potential applications of this work include the assessment of cognitive impacts such as mental workload and cognitive conflict during real-time interaction with websites and other screen-based interfaces, personalization and adaptive interfaces based on an individual's cognitive strategy, and data-driven A/B testing of alternative interface designs.

Political affiliation moderates subjective interpretations of COVID-19 graphs.

We examined the relationship between political affiliation, perceptual (percentage, slope) estimates, and subjective judgements of disease prevalence and mortality across three chart types. An online survey (N = 787) exposed separate groups of participants to charts displaying (a) COVID-19 data or (b) COVID-19 data labeled 'Influenza (Flu)'. Block 1 examined responses to cross-sectional mortality data (bar graphs, treemaps); results revealed that perceptual estimates comparing mortality in two countries were similar across political affiliations and chart types (all ps > .05), while subjective judgements revealed a disease x political party interaction (p < .05). Although Democrats and Republicans provided similar proportion estimates, Democrats interpreted mortality to be higher than Republicans; Democrats also interpreted mortality to be higher for COVID-19 than Influenza. Block 2 examined responses to time series (line graphs); Democrats and Republicans estimated greater slopes for COVID-19 trend lines than Influenza lines (p < .001); subjective judgements revealed a disease x political party interaction (p < .05). Democrats and Republicans indicated similar subjective rates of change for COVID-19 trends, and Democrats indicated lower subjective rates of change for Influenza than in any other condition. Thus, while Democrats and Republicans saw the graphs similarly in terms of percentages and line slopes, their subjective interpretations diverged. While we may see graphs of infectious disease data similarly from a purely mathematical or geometric perspective, our political affiliations may moderate how we subjectively interpret the data.

Patient Preference for Telehealth Background Shapes Impressions of Physicians and Information Recall: A Randomized Experiment.

Introduction: Telehealth is increasing rapidly as a health care delivery platform, but we lack empirical evidence regarding how telehealth environments can affect patient experiences. The present research determined how physician's telehealth backgrounds affect various patient outcomes. Methods: Participants viewed a 30-s video of a physician with one of six different virtual backgrounds and reported various socioemotional and cognitive responses to the mock telehealth experience. Results: Although the telehealth background manipulation did not impact participants' socioemotional or cognitive responses, participants' subjective perceptions of the telehealth backgrounds were related to important clinical outcomes, such as their ability to remember critical information from the appointment and overall satisfaction with the experience. Discussion: Telehealth environments may result in tradeoffs between patient experience, subjective impressions of clinicians, and information recall. Conclusions: A physician's telehealth background can have measurable impact on patients' telehealth experiences, suggesting a need for careful background selection and design.

Virtual environments to study emotional responses to clinical communication: A scoping review.

OBJECTIVE: This scoping review explores the potential for virtual environments (VE) to evaluate emotional outcomes in clinical communication research. Authors representing multiple disciplines use review results to propose potential research opportunities and considerations. METHODS: We utilized a structured framework for scoping reviews. We searched four literature databases for relevant articles. We applied multidisciplinary perspectives to synthesize relevant potential opportunities for emotion-focused communications research using VE. RESULTS: Twenty-one articles met inclusion criteria. They applied different methodological approaches, including a range of VE technologies and diverse emotional outcome measures, such as psychophysiological arousal, emotional valence, or empathy. Major research topics included use of virtual reality to provoke and measure emotional responses, train clinicians in communication skills, and increase clinician empathy. CONCLUSION: Researchers may leverage VE technologies to ethically and systematically examine how characteristics of clinical interactions, environments, and communication impact emotional reactions and responses among patients and clinicians. Variability exists in how VE technologies are employed and reported in published literature, and this may limit the internal and external validity of the research. However, virtual reality can provide a low-cost, low-risk, experimentally controlled, and ecologically valid approach for studying clinician-patient communication. PRACTICE IMPLICATIONS: Future research should leverage psychophysiological measures to further examine emotional responses during clinical communication scenarios and clearly report virtual environment characteristics to support evaluation of study conclusions, study replicability, and meta-analyses.

Probing the invariant structure of spatial knowledge: Support for the cognitive graph hypothesis.

We tested four hypotheses about the structure of spatial knowledge used for navigation: (1) the Euclidean hypothesis, a geometrically consistent map; (2) the Neighborhood hypothesis, adjacency relations between spatial regions, based on visible boundaries; (3) the Cognitive Graph hypothesis, a network of paths between places, labeled with approximate local distances and angles; and (4) the Constancy hypothesis, whatever geometric properties are invariant during learning. In two experiments, different groups of participants learned three virtual hedge mazes, which varied specific geometric properties (Euclidean Control Maze, Elastic Maze with stretching paths, Swap Maze with alternating paths to the same place). Spatial knowledge was then tested using three navigation tasks (metric shortcuts on empty ground plane, neighborhood shortcuts with visible boundaries, route task in corridors). They yielded the following results: (a) Metric shortcuts were insensitive to detectable shifts in target location, inconsistent with the Euclidean hypothesis. (b) Neighborhood shortcuts were constrained by visible boundaries in the Elastic Maze, but not in the Swap Maze, contrary to the Neighborhood and Constancy hypotheses. (c) The route task indicated that a graph of the maze was acquired in all environments, including knowledge of local path lengths. We conclude that primary spatial knowledge is consistent with the Cognitive Graph hypothesis. Neighborhoods are derived from the graph, and local distance and angle information is not embedded in a geometrically consistent map.

Wormholes in virtual space: From cognitive maps to cognitive graphs.

Humans and other animals build up spatial knowledge of the environment on the basis of visual information and path integration. We compare three hypotheses about the geometry of this knowledge of navigation space: (a) 'cognitive map' with metric Euclidean structure and a consistent coordinate system, (b) 'topological graph' or network of paths between places, and (c) 'labelled graph' incorporating local metric information about path lengths and junction angles. In two experiments, participants walked in a non-Euclidean environment, a virtual hedge maze containing two 'wormholes' that visually rotated and teleported them between locations. During training, they learned the metric locations of eight target objects from a 'home' location, which were visible individually. During testing, shorter wormhole routes to a target were preferred, and novel shortcuts were directional, contrary to the topological hypothesis. Shortcuts were strongly biased by the wormholes, with mean constant errors of 37° and 41° (45° expected), revealing violations of the metric postulates in spatial knowledge. In addition, shortcuts to targets near wormholes shifted relative to flanking targets, revealing 'rips' (86% of cases), 'folds' (91%), and ordinal reversals (66%) in spatial knowledge. Moreover, participants were completely unaware of these geometric inconsistencies, reflecting a surprising insensitivity to Euclidean structure. The probability of the shortcut data under the Euclidean map model and labelled graph model indicated decisive support for the latter (BFGM>100). We conclude that knowledge of navigation space is best characterized by a labelled graph, in which local metric information is approximate, geometrically inconsistent, and not embedded in a common coordinate system. This class of 'cognitive graph' models supports route finding, novel detours, and rough shortcuts, and has the potential to unify a range of data on spatial navigation.