British journal of psychology最新文献

Self-cues such as one's own name or face attract attention, reflecting a bias for stimuli connected to self to be prioritized in cognition. Recent evidence suggests that even external voices can elicit this self-prioritization effect; in a voice-label matching task, external voices assigned to the Self-identity label ‘you’ elicited faster responses than those assigned to ‘friend’ or ‘stranger’ (Payne et al., Br. J. Psychology, 112, 585-610). However, it is not clear whether external voices assigned to Self are prioritized over participants' own voices. We explore this issue in two experiments. In Exp 1 (N = 35), a voice-label matching task comprising three external voices confirmed that reaction time and accuracy are improved when an external voice cue is assigned to Self rather than Friend or Stranger. In Exp 2 (N = 90), one of the voice cues was replaced with a recording of the participant's own voice. Reaction time and accuracy showed a consistent advantage for the participant's own-voice, even when it was assigned to the ‘friend’ or ‘stranger’ identity. These findings show that external voices can elicit self-prioritization effects if associated with Self, but they are not prioritized above individuals' own voices. This has implications for external voice production technology, suggesting own-voice imitation may be beneficial.

Human migration is an increasingly common phenomenon and migrants are at risk of disadvantageous treatment. We reasoned that migrants may receive differential treatment by locals based on the closeness of their facial features to the host average. Residents of Türkiye, the country with the largest number of refugees currently, served as participants. Because many of these refugees are of Arabic origin, we created target facial stimuli varying along the axis connecting Turkish and Arabic morphological prototypes (excluding skin colour) computed using geometric morphometrics and available databases. Participants made judgements of two universal dimensions of social perception–warmth and competence–on these faces. We predicted that participants judging faces manipulated towards the Turkish average would provide higher warmth and competence ratings compared to judging the same faces manipulated towards the Arabic average. Bayesian statistical tools were employed to estimate parameter values in multilevel models with intercorrelated varying effects. The findings did not support the prediction and revealed raters (as well as target faces) to be an important source of variation in social judgements. In the absence of simple cues (e.g. skin colour, group labels), the effect of facial morphology on social judgements may be much more complex than previously assumed.

Striving towards perfection is an important concept of study, given its heterogenous associations with both positive and negative outcomes. To address this matter, recent work has emphasized the need to differentiate between striving towards perfection (perfectionism) and excellence (excellencism). However, the applicability of this differentiation in adolescence remains largely unexplored, despite this life phase being particularly sensitive for the development of perfectionism. To better understand striving towards perfection in adolescence, we examined the psychometric properties of the German Scale of Perfectionism and Excellencism (SCOPE) and evaluated the nomological net with the Big Five and self-esteem in 788 German adolescents (M_age = 15.49 years; 50% female). The results underscored the distinctiveness of the different strivings in adolescents but pointed to mixed evidence regarding convergent and discriminant validities. Notably, striving towards perfection was related to lower levels of openness and self-esteem but higher levels of neuroticism, whereas striving towards excellence was related to higher levels of every trait except neuroticism. Finally, most results remained consistent across genders and school types. We discuss how the differentiation between perfectionism and excellencism deepens our understanding of adolescents' perfectionistic strivings and how it might inform future research across different psychological fields.

An important development in the study of face impressions was the introduction of dominance and trustworthiness as the primary and potentially orthogonal traits judged from faces. We test competing predictions of recent accounts that address evidence against the independence of these judgements. To this end we develop a version of recent 'deep models of face impressions' better suited for data-efficient experimental manipulation. In Study 1 (N = 128) we build impression models using 15 times less ratings per dimension than previously assumed necessary. In Study 2 (N = 234) we show how our method can precisely manipulate dominance and trustworthiness impressions of face photographs and observe how the effects' pattern of the cues of one trait on impressions of the other differs from previous accounts. We propose an altered account that stresses how a successful execution of the two judgements' functional roles requires impressions of trustworthiness and dominance to be based on cues of both traits. Finally we show our manipulation resulted in larger effect sizes using a broader array of features than previous methods. Our approach lets researchers manipulate face stimuli for various face perception studies and investigate new dimensions with minimal data collection.

Individuals diagnosed with autism, attachment disorders, emotionally unstable personality disorder (EUPD) or complex post-traumatic stress disorder (CPTSD) can present with similar features. This renders differential and accurate diagnosis of these conditions difficult, leading to diagnostic overshadowing and misdiagnosis. The purpose of this study was to explore professionals' perspectives on the differential diagnosis of autism, attachment disorders and CPTSD in young people; and of autism, CPTSD and EUPD in adults. A co-produced three-round Delphi study gathered information through a series of questionnaires from 106 international professionals with expertise in assessing and/or diagnosing at least one of these conditions. To provide specialist guidance and data triangulation, working groups of experts by experience, clinicians and researchers were consulted. Delphi statements were considered to have reached consensus if at least 80% of participants were in agreement. Two hundred and seventy-five Delphi statements reached consensus. Overlapping and differentiating features, methods of assessment, difficulties encountered during differential diagnosis and suggestions for improvements were identified. The findings highlight current practices for differential diagnosis of autism, attachment disorders, CPTSD and EUPD in young people and adults. Areas for future research, clinical and service provision implications, were also identified.

Recent studies employing the spatial interference paradigm reveal qualitative differences in congruency effects between gaze and arrow targets. Typically, arrows produce a standard congruency effect (SCE), with faster responses when target direction aligns with its location. Conversely, gaze targets often lead to a reversed congruency effect (RCE), where responses are slower in similar conditions. We explored this dissociation using the Conditional Accuracy Function (CAF) to assess accuracy across reaction time bins. Using a hierarchical linear mixed modelling approach to compare cropped eyes, and full faces as social stimuli, and arrows as non-social stimuli, we synthesized findings from 11 studies, which led to three distinct models. The results showed that with non-social targets, incongruent trials exhibited lower accuracy rates in the first bin than in subsequent bins, while congruent trials maintained stable accuracy throughout the distribution. Conversely, social targets revealed a dissociation within the fastest responses; alongside a general reduction in accuracy for both congruency conditions, congruent trials resulted in even lower accuracy rates than incongruent ones. These results suggest with gaze targets that additional information, perhaps social, in addition to the automatic capture by the irrelevant target location, is being processed during the earlier stages of processing.

Emerging evidence highlights the role of social comparison in competition and cooperation, yet the dynamics among competitiveness, cooperativeness, and social comparison orientation (SCO) remain underexplored. In the present study, we sought to unravel these complex interplays employing graphical Gaussian models (GGMs) and characterize the network structures utilizing cross-sectional data derived from 1073 Chinese participants. A pre-registered independent sample (n = 1348) served to examine the replicability and robustness of our initial findings. Moreover, we explored the Bayesian networks (i.e., directed acyclic graphs) to delve into their probabilistic directed dependencies. Our analysis identified an interpersonal co-opetition network where SCO bridges competitiveness and cooperativeness, emphasizing the key influence of the desire to surpass others. We also found a significant gender effect on the levels of these orientations but not on the network patterns. Additionally, the replication sample offered validation for the resultant network structure and its key nodes. In sum, these findings provide a new insight into the symbiotic relationship between competitiveness and cooperativeness within the framework of social comparison, offering significant theoretical and practical implications.

Touch plays a crucial role in providing humans with information from the external environment and can be perceived by humans as positively or negatively valenced. It is well documented that touch can differentially influence social functions, but very little is known about how touch can modulate (meta)cognition. Utilizing a within-subject design, participants were exposed to (a) positive, (b) negative, and (c) no touch, alongside encoding of emotionally valenced (positive and negative) images. After a 20-minute delay, participants completed a Yes/No recognition task to investigate how touch influenced memory-related decision components (e.g. criterion, confidence). Results showed that, compared to the control condition, both positive and negative touch were associated with overall lower confidence ratings, a less liberal response bias and slower response times. Interestingly, for correct recognitions, only negative touch (vs. no touch) led to inappropriately lower confidence and slower response times while both confidence and response time remained unaltered in positive touch. Our findings provide the first evidence that positive and negative touch differentially interact with metacognitive memory-related decisions. Altered metacognitive judgements after being touched could have significant consequences in applied settings, such as situations of eyewitness testimony.

Artificial intelligence (AI) can enhance human communication, for example, by improving the quality of our writing, voice or appearance. However, AI mediated communication also has risks-it may increase deception, compromise authenticity or yield widespread mistrust. As a result, both policymakers and technology firms are developing approaches to prevent and reduce potentially unacceptable uses of AI communication technologies. However, we do not yet know what people believe is acceptable or what their expectations are regarding usage. Drawing on normative psychology theories, we examine people's judgements of the acceptability of open and secret AI use, as well as people's expectations of their own and others' use. In two studies with representative samples (Study 1: N = 477; Study 2: N = 765), we find that people are less accepting of secret than open AI use in communication, but only when directly compared. Our results also suggest that people believe others will use AI communication tools more than they would themselves and that people do not expect others' use to align with their expectations of what is acceptable. While much attention has been focused on transparency measures, our results suggest that self-other differences are a central factor for understanding people's attitudes and expectations for AI-mediated communication.