Emotion regulation unveiled through the categorical lens of attachment.

BACKGROUND: Emotion regulation, the process by which individuals manage and modify their emotional experiences, expressions, and responses to adaptively navigate and cope with various situations, plays a crucial role in daily life. Our study investigates the variations in emotion regulation strategies among individuals with different attachment styles (AS). Specifically, we examine how individuals with secure, anxious, avoidant, and fearful attachment styles effectively utilize cognitive reappraisal and expressive suppression to regulate their emotions. METHODS: A total of n = 98 adults were instructed to attend, reappraise, or suppress their emotions while viewing negative and neutral images from the International Affective Picture System (IAPS) in an experimental emotion regulation task. After completing the task, participants rated the valence and arousal elicited by the images. Attachment styles were measured using the ECR-12 questionnaire and then categorized into four AS. RESULTS: Our study revealed that individuals with secure AS (n = 39) effectively reduced displeasure through cognitive reappraisal but experienced levels of displeasure with expressive suppression. Anxious AS (n = 16) individuals successfully reduced displeasure using cognitive reappraisal but struggled to regulate arousal and effectively use expressive suppression. Avoidant AS (n = 24) individuals could reduce displeasure with both strategies but experienced high arousal during suppression attempts. Fearful AS (n = 19) individuals effectively regulated both displeasure and arousal using either strategy. However, Secure AS individuals showed superior reappraisal efficacy, significantly reducing arousal levels compared to the Fearful AS group. Both Secure and Avoidant AS groups experienced higher valence during reappraisal relative to a baseline, indicating a decrease in displeasure. CONCLUSIONS: Individuals with different AS exhibit variations in the effectiveness of their use of emotion regulation strategies. Our findings reinforce the significance of AS in shaping emotion regulation processes and emphasize the need for tailored approaches to support individuals with different attachment orientations.

Geo-Storylines: Integrating Maps into Storyline Visualizations.

Storyline visualizations are a powerful way to compactly visualize how the relationships between people evolve over time. Real-world relationships often also involve space, for example the cities that two political rivals visited together or alone over the years. By default, Storyline visualizations only show implicitly geospatial co-occurrence between people (drawn as lines), by bringing their lines together. Even the few designs that do explicitly show geographic locations only do so in abstract ways (e.g., annotations) and do not communicate geospatial information, such as the direction or extent of their political campains. We introduce Geo-Storylines, a collection of visualisation designs that integrate geospatial context into Storyline visualizations, using different strategies for compositing time and space. Our contribution is twofold. First, we present the results of a sketching workshop with 11 participants, that we used to derive a design space for integrating maps into Storylines. Second, by analyzing the strengths and weaknesses of the potential designs of the design space in terms of legibility and ability to scale to multiple relationships, we extract the three most promising: Time Glyphs, Coordinated Views, and Map Glyphs. We compare these three techniques first in a controlled study with 18 participants, under five different geospatial tasks and two maps of different complexity. We additionally collected informal feedback about their usefulness from domain experts in data journalism. Our results indicate that, as expected, detailed performance depends on the task. Nevertheless, Coordinated Views remain a highly effective and preferred technique across the board.

A Comparison of Visualizations for Identifying Correlation over Space and Time.

Observing the relationship between two or more variables over space and time is essential in many domains. For instance, looking, for different countries, at the evolution of both the life expectancy at birth and the fertility rate will give an overview of their demographics. The choice of visual representation for such multivariate data is key to enabling analysts to extract patterns and trends. Prior work has compared geo-temporal visualization techniques for a single thematic variable that evolves over space and time, or for two variables at a specific point in time. But how effective visualization techniques are at communicating correlation between two variables that evolve over space and time remains to be investigated. We report on a study comparing three techniques that are representative of different strategies to visualize geo-temporal multivariate data: either juxtaposing all locations for a given time step, or juxtaposing all time steps for a given location; and encoding thematic attributes either using symbols overlaid on top of map features, or using visual channels of the map features themselves. Participants performed a series of tasks that required them to identify if two variables were correlated over time and if there was a pattern in their evolution. Tasks varied in granularity for both dimensions: time (all time steps, a subrange of steps, one step only) and space (all locations, locations in a subregion, one location only). Our results show that a visualization's effectiveness depends strongly on the task to be carried out. Based on these findings we present a set of design guidelines about geo-temporal visualization techniques for communicating correlation.