Video Games and Attitude Change: A Meta-analysis

Despite extensive research on attitudes and a rapid growth of the video game market, there is currently no meta-analysis mapping the link between narrative video games and attitude change. Here, we present such meta-analysis. The findings suggest that narrative video games affect players’ attitudes towards the topics depicted in games. This effect was present in studies focused on changes in both implicit (g = 0.36, k = 18) and explicit attitudes (g = 0.24, k = 101), with longer intervention duration and game mechanics such as stereotyping and meaningful feedback resulting in larger implicit attitude change. Regarding the robustness of the underlying evidence, half of the included studies were judged to be at high risk of bias. On the other hand, the impact of publication bias in this literature was found to be negligible. Altogether, this meta-analysis provides evidence that video games shape how we think about events they represent.

Lack of affective priming indicates attitude-behaviour discrepancy for COVID-19 affiliated words

The ongoing novel coronavirus (COVID-19) pandemic has resulted in the enforcement of national public health safety measures including precautionary behaviours such as border closures, movement restrictions, total or partial lockdowns, social distancing, and face mask mandates in order to reduce the spread of this disease. The current study uses affective priming, an indirect behavioural measure of implicit attitude, to evaluate COVID-19 attitudes. Explicitly, participants rated their overall risk perception associated with contracting COVID-19 significantly lower compared to their perception of necessary precautions and overall adherence to public health measures. During baseline trials, participants explicitly rated COVID-19 affiliated words as unpleasant, similar to traditional unpleasant word stimuli. Despite rating the COVID-19 affiliated words as unpleasant, affective priming was not observed for congruent prime-target COVID-19 affiliated word pairs when compared to congruent prime-target pleasant and unpleasant words. Overall, these results provide quantitative evidence that COVID-19 affiliated words do not invoke the same implicit attitude response as traditional pleasant and unpleasant word stimuli, despite conscious explicit rating of the COVID-19 words as unpleasant. This reduction in unpleasant attitude towards COVID-19 related words may contribute towards decreased fear-related behaviours and increased incidences of risky-behaviour facilitating the movement of the virus.

Humanoid robots are perceived as an evolutionary threat

In the grand challenges of successful social encounters with socially sophisticated robots and shaping the future development of robots in socially acceptable ways, we need to quantify people perception to the robots. The critical assumption at the perception to humanoid robots, namely that people perceive humanoid robots as an evolutionary threat, has not been directly confirmed. We assume the existence of behavioral and neural automaticity for humanoid robots that were previously only evident for evolutionary threats. Here, we observed a monocular advantage for the perception of humanoid robots the same as an evolutionary threat (i.e., snakes). Our neuroimaging analysis indicated that unconscious presentation of humanoid robot vs. human images led to significant left amygdala activation that was associated with negative implicit attitude to humanoid robots. After successfully weakening negative attitude, the left amygdala response to unconscious presentation of humanoid robot images decreased, and the decrease of left amygdala response was positively associated with the decrease of negative attitude. Our results reveal that processing of information about humanoid robots displays automaticity with regard to recruitment of visual pathway and amygdala activation. Our findings that humans may perceive humanoid robots as an evolutionary threat will guide the future direction of robots development and bring us closer to interacting with socially sophisticated robots.

The Four Deadly Sins of Implicit Attitude Research

In this article, we describe four theoretical and methodological problems that have impeded implicit attitude research and the popular understanding of its findings. The problems all revolve around assumptions made about the relationships among measures (indirect vs. versus direct), constructs (implicit vs. explicit attitudes), cognitive processes (e.g., associative vs. propositional), and features of processing (automatic vs. controlled). These assumptions have confused our understandings of exactly what we are measuring, the processes that produce implicit evaluations, the meaning of differences in implicit evaluations across people and contexts, the meaning of changes in implicit evaluations in response to intervention, and how implicit evaluations predict behavior. We describe formal modeling as one means to address these problems, and provide illustrative examples. Clarifying these issues has important implications for our understanding of who has particular implicit evaluations and why, when those evaluations are likely to be particularly problematic, how we might best try to change them, and what interventions are best suited to minimize the effects of implicit evaluations on behavior.