Martin Dechant

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.

In everyday behaviour, the ability to stop an already initiated action is critical for ensuring both your safety and that of others; for example, when stopping a reaching movement towards a hot stove-top after realising it is hot. Neuroscientific evidence points towards the critical role of several regions in the right prefrontal cortex in the coordination and execution of this response inhibition—specifically the right inferior frontal gyrus (rIFG) and the right dorsolateral prefrontal cortex (rDLPFC). The present study investigated the effects of different transcranial magnetic stimulation (TMS) protocols on stop-signal task (SST) performance. We hypothesized that TMS over one or both of these areas would be detrimental to performance. However, contrary to our hypothesis, TMS significantly facilitated performance regardless of the stimulation condition. We applied both frequentist and Bayesian methods to assess the robustness of these effects, revealing consistent reductions in stop-signal reaction time (SSRT) across active conditions. Our results add to the growing body of results that suggest TMS effects may not be as straight-forward as usually assumed and that so-called “inhibitory protocols” can facilitate performance. This result could be explained by a shift in the signal-to-noise ratio depending on the pre-activation of the area. Put differently, TMS may have primed task-related activity in the target areas to a level that was optimal for task performance. Alternatively, the observed effect may reflect an (over)compensation by other parts of the network or disruption of competing resources. Future studies may provide further support for these hypotheses.

Background: Digital interventions have been proposed as a solution to meet the growing demand for mental health support. Large language models (LLMs) have emerged as a promising technology for creating more personalized and adaptive mental health chatbots. While LLMs generate responses based on statistical patterns in training data rather than through conscious reasoning, they can be designed to support important psychological processes. Prospection—the ability to envision and plan for future outcomes—represents a transdiagnostic process altered across various mental health conditions that could be effectively targeted through such interventions. We designed “Future Me,” an LLM-powered chatbot designed to facilitate future-oriented thinking and promote goal pursuit using evidence-based interventions including visualization, implementation intentions, and values clarification. Objective: This study aims to understand how users engage with Future Me, evaluate its effectiveness in supporting future-oriented thinking, and assess its acceptability across different populations, with particular attention to postgraduate students’ stress management needs. We also seek to identify design improvements that could enhance the chatbot’s ability to support users’ mental well-being. Methods: In total, 2 complementary studies were conducted. Study 1 (n=20) examined how postgraduate students used Future Me during a single guided session, followed by semistructured interviews. Study 2 (n=14) investigated how postgraduate students interacted with Future Me over a 1-week period, with interviews before and after usage. Both studies analyzed conversation transcripts and interview data using thematic analysis to understand usage patterns, perceived benefits, and limitations. Results: Across both studies, participants primarily engaged with Future Me to discuss career or education goals, personal obstacles, and relationship concerns. Users valued Future Me’s ability to provide clarity around goal-setting (85% of participants), its nonjudgmental nature, and its 24/7 accessibility (58%). Future Me effectively facilitated self-reflection (80%) and offered new perspectives (70%), particularly for broader future-oriented concerns. However, both studies revealed limitations in the chatbot’s ability to provide personalized emotional support during high-stress situations, with participants noting that responses sometimes felt formulaic (50%) or lacked emotional depth. Postgraduate students specifically emphasized the need for greater context awareness during periods of academic stress (58%). Overall, 57% of requests occurred outside office hours, dropping from 40 on day 1 to 12 by day 7. Conclusions: Future Me demonstrates promise as an accessible tool for promoting prospection skills and supporting mental well-being through future-oriented thinking. However, effectiveness appears context-dependent, with prospection techniques more suitable for broader life decisions than acute stress situations. Future development should focus on creating more adaptive systems that can adjust their approach based on the user’s emotional state and immediate needs. Rather than attempting to replicate human therapy entirely, chatbots like Future Me may be most effective when designed as complementary tools within broader support ecosystems, offering immediate guidance while facilitating connections to human support when needed.

Borderline personality disorder (BPD) is characterized by pervasive difficulties with self-image, interpersonal relationships, emotion regulation and impulse control. Impulsive behaviors can be assessed using tasks such as the stop-signal task (SST). Traditional SSTs are repetitive and cognitively demanding, requiring sustained attention and effort over extended periods. This can be challenging, particularly for clinical populations who often experience difficulties with attention, emotional regulation, and frustration tolerance. In this study, we examined whether a gamified version of the SST (gSST) could effectively differentiate inhibitory control in patients with BPD compared to healthy controls (HC), and explored associations between behavioral performance and self-reported impulsivity. Fifty participants (25 BPD, 25 HC) completed the gSST and the UPPS-P impulsivity questionnaire. Patients with BPD showed significantly faster reaction times, more choice errors, and shorter stop-signal delays, indicating impairments in both proactive and reactive inhibition. However, no significant group difference emerged for the primary measure, the stop-signal reaction time (SSRT). The SSRT correlated positively with self-reported positive urgency across the sample, suggesting a link between emotionally driven impulsivity and inhibitory control as assessed with a gSST. These findings highlight the potential of gamified cognitive tasks to provide sensitive, engaging, and ecologically valid measures of impulsivity, with implications for both clinical assessment and personalized intervention strategies in BPD.

BACKGROUND The growing demand for mental health support has led to exploration of digital interventions to bridge the gap between available resources and those seeking help. Large language models (LLMs) have emerged as a promising technology for creating more personalized and adaptive mental health chatbots. Prospection—the ability to envision and plan for future outcomes—represents a transdiagnostic process altered across various mental health conditions that could be effectively targeted through such interventions. OBJECTIVE To investigate how people use "Future Me," an LLM-powered chatbot designed to facilitate future-oriented thinking, and what types of support they seek from it; to examine how Future Me enables future-oriented thinking; to assess its acceptability and usability across different user groups; to understand postgraduate students' specific perceptions and needs regarding chatbot-based stress management; and to identify how chatbot design can be improved to better address users' mental wellbeing needs. METHODS Two complementary studies were conducted. Study 1 (n = 20) examined how postgraduate students used Future Me during a single guided session, followed by semi-structured interviews. Study 2 (n=14) investigated how postgraduate students interacted with Future Me over a one-week period, with interviews before and after usage. Both studies analyzed conversation transcripts and interview data using thematic analysis to understand usage patterns, perceived benefits, and limitations. RESULTS Across both studies, participants primarily engaged with Future Me to discuss career/education goals, personal obstacles, and relationship concerns. Users valued the chatbot's ability to provide clarity around goal-setting, its non-judgmental nature, and its 24/7 accessibility. Future Me effectively facilitated self-reflection and offered new perspectives, particularly for broader future-oriented concerns. However, both studies revealed limitations in the chatbot's ability to provide personalized emotional support during high-stress situations, with participants noting that responses sometimes felt formulaic or lacked emotional depth. Postgraduate students specifically emphasized the need for greater context awareness during periods of academic stress. CONCLUSIONS Future Me demonstrates promise as an accessible tool for promoting prospection skills and supporting mental wellbeing through future-oriented thinking. However, effectiveness appears context-dependent, with prospection techniques more suitable for broader life decisions than acute stress situations. Future development should focus on creating more adaptive systems that can adjust their approach based on the user's emotional state and immediate needs. Rather than attempting to replicate human therapy entirely, chatbots like Future Me may be most effective when designed as complementary tools within broader support ecosystems, offering immediate guidance while facilitating connections to human support when needed.

Flexible working, including in resource-constrained settings such as long-haul flights, poses considerable challenges. While research in mixed reality (MR) offers the potential for enhancing experiences of working on airplanes (WoA), what input modalities and interactions might be suitable for such workspaces is under-explored. To address this gap, we created four design probes and demonstrated their interactions within MR for WoA using a branching decision-based interactive video. 24 participants engaged in the think-aloud study with the video where they selected which probe to watch based on personal preference and order. The follow-up interview further solidified their general preferences for intuitive and friction-free inputs, revealed strong concerns about reliability, discreetness, and portability, and showed high enthusiasm for interactive video. Based on these findings, we contribute a context-driven design space of input modalities for WoA in MR, extending the understanding of design opportunities for inputs with MR in confined spaces.

Hypersexualization of women video game characters through unrealistic body proportions and revealing clothes is common. Previous work suggested that overexposure to sexualized women characters can harm players, through increased self-objectification and higher rape myth acceptance; however, there have been inconsistencies across studies that we suggest may stem from variations in the study design and other visual characteristics of the characters, such as relying heavily on stereotypes reinforced by colour schemes (e.g., blonde princess). To address this, we designed a text-based game prototype and four identical women characters who varied only in their colour scheme (gold/red or purple/black) and amount of sexualization (through bikini armour and exaggerating body proportions). We measure attributes assigned to the avatar, avatar appeal, rape myth acceptance and self-objectification. 82 participants participated in our online-study in 2021. Most participants found the non-sexualized character versions more appealing than the sexualized characters and were more likely to assign ‘manipulativeness’ to the sexualized character. When presented with the sexualized characters, participants demonstrated higher rape myth acceptance, and more self-objectification.

Failure is an integral element of most games, and while some players may benefit from external support, such as cheat codes, to prompt self-soothing, most games lack supportive elements. We asked participants (N=88) to play Anno 1404 in single-player mode, and presented a money-generating cheat code in a challenging situation, also measuring the personality trait of action-state orientation, which explains differences in self-regulation ability (i.e., self-soothing) in response to threats of failure. Individuals higher in state orientation were more likely to take the offer, and used the cheat code more frequently. The cheat code also acted as an external support, as differences in experienced pressure between action- and state-oriented participants vanished when it was used. We found no negative consequences of using external support in intrinsic motivation, needs satisfaction, flow, or performance. We argue that external support mechanisms can help state-oriented players to self-regulate in gaming, when faced with failure.