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This preregistered, randomized controlled experiment attempts to distil the effects of Moral Foundational Framing on attitudes and behaviours towards refugees in the UK. First, moral foundations were found to robustly predict both attitudes and behaviours practised towards refugees. Next, a degree of support was found for the effectiveness of moral foundational framing in adjusting attitudes, but not behaviour, toward refugees in the UK. Individuals who scored highly on certain morals were susceptible to influence by moral foundational framing, but not always in ways that may have been expected. We conclude that the robust relationship found between moral foundations and attitudes towards refugees stresses the importance of actively shaping moral foundations. This notion is strengthened by the comparatively less robust effects of framing. Findings could be used to inform the practice of individuals interested in influencing opinion and behaviour, particularly in support of refugee acceptance.

Hyper-realistic masks present a new challenge to security and crime prevention. We have recently shown that people’s ability to differentiate these masks from real faces is extremely limited. Here we consider individual differences as a means to improve mask detection. Participants categorized single images as masks or real faces in a computer-based task. Experiment 1 revealed poor accuracy (40%) and large individual differences (5–100%) for high-realism masks among low-realism masks and real faces. Individual differences in mask categorization accuracy remained large when the Low-realism condition was eliminated (Experiment 2). Accuracy for mask images was not correlated with accuracy for real face images or with prior knowledge of hyper-realistic face masks. Image analysis revealed that mask and face stimuli were most strongly differentiated in the region below the eyes. Moreover, high-performing participants tracked the differential information in this area, but low-performing participants did not. Like other face tasks (e.g. identification), hyper-realistic mask detection gives rise to large individual differences in performance. Unlike many other face tasks, performance may be localized to a specific image cue.