An appraisal-based chain-of-emotion architecture for affective language model game agents.

The development of believable, natural, and interactive digital artificial agents is a field of growing interest. Theoretical uncertainties and technical barriers present considerable challenges to the field, particularly with regards to developing agents that effectively simulate human emotions. Large language models (LLMs) might address these issues by tapping common patterns in situational appraisal. In three empirical experiments, this study tests the capabilities of LLMs to solve emotional intelligence tasks and to simulate emotions. It presents and evaluates a new Chain-of-Emotion architecture for emotion simulation within video games, based on psychological appraisal research. Results show that it outperforms control LLM architectures on a range of user experience and content analysis metrics. This study therefore provides early evidence of how to construct and test affective agents based on cognitive processes represented in language models.

A data-driven approach for examining the demand for relaxation games on Steam during the COVID-19 pandemic.

The COVID-19 pandemic has been a major source of stress for a majority of people that might have negative long-term effects on mental health and well-being. In recent years, video games and their potential positive effects on stress relief have been researched and "relaxation" has been an important keyword in marketing a certain kind of video game. In a quasi-experimental design, this study investigated the increase of average daily player peak (ADPPs) for the COVID period compared to the pre-COVID period and if this increase was significantly larger for relaxing games in contrast to non-relaxing games. Results showed a medium-sized increase of ADPPs over all types of games but no difference between relaxing games and non-relaxing games. These results are discussed in regards to their potential of presenting gaps between the current theoretical models of the influence of video games on mental health and actual observed player behaviour.

Endocannabinoid concentrations in hair and mental health of unaccompanied refugee minors.

Altered activity of the endocannabinoid (EC) system has been linked to dysregulated stress-reactivity and the development of trauma-related psychopathology. The EC system, with its main components anandamide (AEA), 2-arachidonoyl-glycerol (2-AG) and other N-acyl-ethanolamides, is considered to be a buffer system that protects against the negative effects of traumatic experiences on mental health. Recently, the use of hair analyses, a method to gain information on long-term cumulative system activity, has been introduced to the study of ECs. Here, we seek to extend current knowledge on the potential use of hair EC concentrations as a marker of trauma-related psychological symptoms as well as psychological resources. Ninety-one male URM from Syria and Afghanistan (mean age = 17.4 years) living in group homes of the Child Protection Services in Leipzig, Germany, completed assessments on traumatic life events (TLE), PTSD symptoms, depression, anxiety and somatic symptoms as well as on self-efficacy and prosocial behavior. Scalp-near 3 cm hair segments were obtained and EC concentrations quantified using liquid chromatography tandem mass spectrometry. Analyses revealed relatively week and inconsistent associations of hair ECs and psychological symptoms, with only a positive correlation between 2-AG and depression. Concerning prosocial behavior and self-efficacy positive relationships were found with oleoylethanolamide (OEA), stearoylethanolamide (SEA), and palmitoylethanolamide (PEA). Our findings add data concerning the utility of hair EC analyses for PNE research but on a whole fail to reveal a clear association pattern between hair ECs and mental health in URM.