Robin Welsch

Cosmetic items have become one of the most profitable monetization strategies in games. Like fashion in the physical world, their value is socially constructed and tied to visibility, prestige, and identity signalling. This raises questions about whether psychological factors influence cosmetic spending behaviour. Therefore, we conducted a cross-sectional survey with 199 in-game cosmetic purchasers. We assessed trait social anxiety, avatar and self-perception, actual spending for cosmetics, Big Five personality traits, and cosmetic purchase motivation. Through structural equation modelling, we found that, among cosmetic purchasers, trait social anxiety and status motivation showed the strongest association with spending amounts, with reward motives playing a secondary role. However, qualitative findings focused more on aesthetic appeal and economic considerations as primary stated motives, while social and community influences were less central. These findings suggest that individual psychological differences may warrant important design consideration for in-game cosmetics highlighting the multi-layered influences on previous purchase decisions.

Psychologists have a long history of engaging in the intersection of human and technology and have contributed to the field of Human–Computer Interaction (HCI). This scoping review explores how psychological theories have been applied in HCI in European research during the last decade and identifies future research opportunities. As HCI is a multidisciplinary field that applies psychology, we explore how humans and human needs are understood in HCI. After searching for mentions of “psychological theory or psychological theories,” 119 articles were identified, and 29 articles were found eligible. The authors were from 13 European countries, Germany and the United Kingdom being the most frequent ones. The reviewed papers demonstrate how emerging technologies and interaction modalities broaden the need for integrating psychology into HCI. Self-determination theory (SDT) was the most frequently applied psychological theory, but many other theories were used, covering several important aspects of human behavior such as motivation, behavior change, emotion, mental health, and social interaction.

People face challenges with complex search tasks daily; chat-based large language models have the potential to assist search by helping with query formulation and content navigation, for instance. However, there is a lack of user research on integrating AI chat and traditional search to enhance Information Retrieval (IR) for the general public. This study explores how younger (25 participants) and older (22 participants) adults utilize these two platforms to retrieve information. Through two IR tasks, quality- and quantity-oriented tasks, focused on gathering evidence related to various countries’ CO ₂ emissions, younger users spent more time, issued more queries, and explored more external web pages than older adults in both tasks. In contrast, despite reporting less familiarity with AI chat, older adults relied more on chat to complete their tasks. They submitted longer queries for the quality task and reached the first query faster for the quantity task than their younger counterparts, reflecting a top-down IR strategy. In the end, task outcomes were similar for the two groups, indicating AI chat’s capability to support IR. Drawing from our study results and relevant literature, we propose five design requirements to harness the synergic value of search and AI chat in supporting IR.

Generative AI tools for image creation are now mainstream, yet we know little about when and why observers judge them as “creative”. Previous human-robot interaction research suggests that revealing the creation process can raise perceived machine creativity and points that observer differences may moderate this effect. We take these observations from physical robots to the bigger domain of virtual text-to-image diffusion systems by manipulating perceptual evidence (PE), i.e., interface-visible cues about the generation process. We report two preregistered online experiments looking into PE and observer individual differences. Study 1 (N=298) used a within-subjects manipulation comparing Product (final image only) to Product+Process (adding a short animation of the denoising process). Study 2 (N=295) added a between-subjects tutorial (diffusion vs. control) in a 2x2 mixed design. The tutorial briefly explained how diffusion models generate images, intended to raise system-specific literacy. Contrary to previous work, confirmatory analyses found no average effect of showing Process on creativity, and no tutorial effect. Exploratory analyses revealed that general AI literacy moderated the PE contrast, i.e., at lower literacy, observing process tended to lower creativity ratings; at higher literacy, it tended to raise them. Moreover, attitudes toward AI and art interest were positively associated with creativity ratings. Thematic analysis of open-ended responses indicated potential reasons for the lack of overall PE effect. Taken together, these converging quantitative and qualitative findings indicate that individual differences systematically shape creativity judgments of text-to-image GenAI and, in our setting, exert stronger and more reliable influence than PE alone. For design, this implies that process visualizations could help some audiences more than others. Interfaces that adapt to literacy and attitudes, or that pair process views with contextual explanation calibrated to user background, could be more likely to shift judgments than one-size-fits-all depictions of generation.