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Importance of transgender nuances in research and advocacy: Reply to Morgenroth (2025) and Tate (2025)

In their responses to our paper ‘Conceptualizing transgender experiences in psychology: Do we have a “true” gender?’ (The British Journal of Psychology, 2024, 115, 723), Tate (2025) and Morgenroth (2025) provide reflections on the importance of nuance when researching gender and in transgender advocacy. In this reply, I note where this paper is situated in the literature and engage in a discussion of the role of definitions in transgender advocacy. Over-reliance on an individual's true gender when evaluating transgender people's legitimacy may exclude individuals whose gender is not understandable as ‘true’ to a cisgender majority. I suggest that a broad definition of transgender can allow legitimization to arise from transgender identification and gender self-categorization alongside broader experiences of body and gender.

Language about gender/sex should be used intentionally and flexibly

In their paper, ‘Conceptualizing transgender experiences in psychology: Do we have a ‘true’ gender?’ Jackson and Bussey (British Journal of Psychology, 115, 723) critique the idea of having a ‘true’ gender and propose that the term ‘transgender experience’ may be more appropriate than ‘transgender identity’. In this commentary, I reflect on the usefulness of the terms transgender identity and transgender experience and argue that both hold value and can contribute to a more nuanced discussion of gender/sex. I use the discussion of these two terms as a springboard to make a broader point: As researchers, we should use language about gender/sex flexibly and intentionally. As psychologists, we are trained to use clear operationalizations for the constructs we study, yet it is often unclear whether authors refer to biological sex, gender identity, social perception, or socialization when they speak of ‘women’ and ‘men’. I encourage researchers to be more mindful in their language use and to engage with the nuanced terms that gender scholars (including Jackson and Bussey) have put forward when discussing gender/sex – both in the context of transgender identities and experiences and when discussing cisgender identities and experiences.

The global prevalence of emotional eating in overweight and obese populations: A systematic review and meta‐analysis

This systematic review aims to investigate the current prevalence of emotional eating and its associated factors in overweight and obese populations. We included studies that (1) reported prevalence of emotional eating; (2) were in the context of weight gain or overweight and obesity; (3) used a validated psychometric tool to assess emotional eating; (4) were published as an internationally referred journal article and (5) were reported in the English language. Articles were searched on eight electronic databases (CINAHL, EMBASE, PsychINFO, ProQuest, PubMed, Scopus, The Cochrane Library and Web of Science) from the journals' inception to 11 April 2024. A total of 18 studies, representing a total of 21,237 people, were included in the review. Our study suggested that emotional eating is significantly prevalent at 44.9%. High heterogeneity observed (I 2: 98.7%) can be attributed to differences in measurement tools for emotional eating, but not differences in geographical regions. By providing insight to the current prevalence of emotional eating and its relevant factors, this study outlines the steps to take in future research and practice to tackle emotional eating and related health issues like obesity. There is a need to develop standardized measurement tools for emotional eating, and further investigate sociodemographic factors.

Nuance and specificity always matter—Especially for all the meanings of ‘gender’: A reply to Jackson and Bussey (2024)

Jackson and Bussey (The British Journal of Psychology, 2024, 115, 723) present the provocative argument that the concept of a “true gender” is not a useful conceptual object for psychology. While the article does make 2 valid and worthwhile points, the remainder of that article lacks necessary nuance in developing its general conclusion.

New evidence finds young people in Mainland China are now bicultural

This study reports new evidence that young people in Mainland China are now bicultural. We followed the established method of testing biculturalism by priming participants with images from two different cultures and measuring whether those images activate different thought styles. First, we replicated findings from 25 years ago that college students in Hong Kong are bicultural (Study 1). Next, we found that priming Mainland Chinese college students with Chinese culture increased external attributions (which are more common in China), whereas priming American culture increased internal attributions (which are more common in the US; Study 2). Next, we tested a “negative control” group that we expected should not respond to bicultural primes. Older adults who were born before China's Reform and Opening policy in 1978 showed no evidence of biculturalism (Study 3). This new evidence extends biculturalism to Mainland China, and it provides a crucial negative control test for biculturalism research.

Editorial Acknowledgement

Issue Information

Orthographic character complexity modulates dynamic neural activity in skilled handwriting

Handwriting is an outstanding case of a highly complex and efficient fine motor skill. However, little is known about its neural underpinnings during continuous handwriting production. In the present study, we examined the effects of orthographic character complexity (i.e. the stroke number of a Chinese character) on both neural and behavioural activities during an EEG-based naturalistic fluent sentence-handwriting task from 102 adult Chinese native speakers. For each written character, the interval between finishing the preceding character and its onset (inter-character interval) as well as the amplitudes of the onset-synchronized event-related potential (ERP) in pre- and post-onset time windows was defined as dependent variables. The effects of character complexity and other confounding factors were analysed with linear mixed models. Character complexity increased the inter-character interval and significantly affected ERP amplitudes in both pre- and post-onset time windows. The ERP pattern in the pre-event time window exhibited a dipole-like activation in the left motor cortex, and its amplitude increased with character complexity in line with the documented relationship between the lateralized readiness potential and motor complexity. This study demonstrates the feasibility of studying neurocognitive processes in complex naturalistic motor tasks and extends our knowledge about the dynamic pattern of handwriting-related neural activities.

Perceiving visual events uses optical information that reflects dynamics rather than resembles appearance

This study investigates the optical information for visual event perception. Events are objects in motion, with properties like shape, weight and surface material influencing the dynamics that shape movements and optics. The progressive transformation of visible textures, known as visual kinaesthetic information, specifies movements and objects. Four experiments tested whether events could be perceived using only visual kinaesthetic information. Participants identified their own walking from point-light displays (Experiment 1), from simulated environmental texture transformations as a result of their walking (Experiment 2), and from videos shot by a head-mounted camera during outdoor walking (Experiment 3); and distinguishing strangers from footages captured by their head-mounted cameras (Experiment 4). In Experiments 2–4, the displays did not resemble the outline of a person or look like walking but revealed the physical relations between the walker and the environment as a result of their movement. Regardless, participants were able to recognize themselves and distinguish strangers. Thus, observers are able to perceive events using visual kinaesthetic information that stems from dynamics. The one-to-one correspondences between object property, dynamics, kinematics and optical information are governed by the laws of physics, and unaffected by the event's appearance or viewing perspectives.

Involuntary remembering and ADHD: Do individuals with ADHD symptoms experience high volumes of involuntary memories in everyday life?

Spontaneous mind wandering has been implicated as a feature of attention-deficit/hyperactivity disorder (ADHD) and researchers have wondered if spontaneous remembering is also a feature of ADHD. In this study, we compared spontaneous cognition, principally involuntary autobiographical memories, in participants who scored inside the ADHD range on BAARS-IV to those who scored outside of the ADHD range. In Study 1, participants reported their involuntary memories and spontaneous thoughts on a laboratory measure of involuntary memory (the vigilance task), as well as estimated their daily involuntary memory frequencies on a separate questionnaire. The results showed that ADHD range participants did not differ from non-ADHD range participants in reports of involuntary memories and spontaneous thoughts on the vigilance task, but ADHD range participants estimated higher daily involuntary memory frequencies than non-ADHD range participants on the questionnaire. Additionally, on the questionnaire, ADHD participants reported that their involuntary memories were less positive and more repetitive than non-ADHD participants. In Study 2, participants recorded their naturally occurring involuntary memories in a structured diary for 48 hours. The results showed that ADHD range participants had more involuntary memories than non-ADHD range participants, and they also reported that they experienced them as less positive.

Differential diagnosis of autism, attachment disorders, complex post‐traumatic stress disorder and emotionally unstable personality disorder: A Delphi study

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.

Positive and negative touch differentially modulate metacognitive memory judgements for emotional stimuli

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.

Unpacking interplays between competitiveness, cooperativeness, and social comparison orientation: A network psychometric approach and replication

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.

A new way to conceptualize intolerance of uncertainty among adolescents: Embracing the network perspective

Intolerance of uncertainty (IU), a pivotal transdiagnostic risk factor in psychopathology, is defined as a dispositional incapacity to withstand uncertainty distress, driving maladaptive cognitive, emotional and behavioural reactions to uncertainty. However, the intricate interplay among these components, particularly in adolescents, remains underexplored; yet understanding this interplay is crucial for supporting mental health. To address this gap, we employed a network approach to conceptualize IU in 5672 non-clinical Chinese adolescents (M age = 14.13 years, SDage = 1.96 years, range = 10–19 years, 46.6% boys), combining graphical Gaussian models (GGM) and directed acyclic graphs (DAG). Our analyses revealed a tripartite network comprising cognitive, behavioural and emotional components. Notably, ‘frustration’ and ‘work with hindrance’ emerged as key drivers, while ‘catastrophizing belief’ served as a critical bridge linking different components. These findings underscore the importance of alleviating uncertainty-induced frustration and enhancing coping skills for behavioural impediments to mitigate adolescent IU. Additionally, therapeutic interventions should prioritize modifying and re-evaluating catastrophizing beliefs related to uncertainty.

Facial basis of stereotypes: Judgements of warmth and competence based on cross‐group typicality/distinctiveness of faces

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.

Who tends to be a perfectionistic adolescent? Distinguishing perfectionism from excellencism and investigating the links with the Big Five and self‐esteem

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.

Listen to yourself! Prioritization of self‐associated and own voice cues

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.

Inter‐brain synchrony is associated with greater shared identity within naturalistic conversational pairs

Inter-brain synchrony occurs between individuals who feel connected socially, but how synchrony relates to felt connectedness under naturalistic social interaction has remained enigmatic. We hypothesized that inter-brain synchrony between naturally interacting individuals might be associated with the internalization of a social identity, a link between an individual's personal identity and the social group to which the individual belongs. A convenience sample of sixty participants were split into dyads and interacted naturalistically on a social task. Through mapping EEG oscillatory waveforms onto a conceptual model categorizing the formation of a social identity within a naturalistic conversation, greater inter-brain synchrony was observed in the emergent stage within the formation of a social identity compared to earlier stages, where a social identity was not present. We provide evidence for greater neural synchrony related to higher socio-psychological connectedness during the development of social identity under naturalistic social interaction.

Daily effects of a brief compassion‐focused intervention for self‐compassion

Interventions for increasing self-compassion are typically assessed through retrospective reports, which may not accurately capture everyday self-compassionate behaviour. Our study addresses this using experience sampling to evaluate a brief compassion-focused intervention's effects on needs for self-compassion, awareness of opportunities for self-compassion, self-compassionate behaviour and emotional responses to one's distress in daily life. Results indicated that the intervention was associated with less likelihood of reporting needs and opportunities for self-compassion but with no difference in self-compassionate actions or emotional experience. When participants acted self-compassionately, they reported more positive emotional experiences after needing self-compassion. This underscores the disparity between retrospective and ecological assessments, emphasizing the need for interventions to be evaluated in real-life contexts.

The role of surface and structural similarities in the retrieval of realistic perceptual events

This study investigated whether structural similarities (i.e. abstract frames, e.g. once bitten twice shy) can prevail over surface similarities (i.e. contexts, e.g. restaurant) in driving the retrieval of realistic events involving dynamic, multimodal and perceptually crowded data. After watching an initial set of video clips, participants had to indicate whether a new video clip, that shared surface similarities with an initial event and structural similarities with another one, elicited a retrieval. The results of Experiment 1A showed that retrieval was more likely to be elicited by structural rather than by surface similarities. Experiment 1B confirmed that the surface similarities manipulated in this study were strong enough to elicit substantial retrievals when the competing structural match was neutralized. The pattern of results obtained in Experiment 1A remained unchanged when the number of unrelated video clips within the initial set was increased. The findings suggest that structurally based retrievals still prevail when familiar structures underlie realistic perceptual events. They open new perspectives regarding the settings that promote structurally based retrievals in educational contexts where unfamiliar principles are introduced.

Mapping the maze: A network analysis of social–emotional skills among children and adolescents with social–emotional difficulties

Developing social–emotional skills is crucial for all children and adolescents, particularly those experiencing social and emotional difficulties. This study used network analysis to identify the central skills and network association of different social–emotional skills and investigated how these networks differ between childhood and adolescence. Data were obtained from the 2019 Survey on Social and Emotional Skills by the Organization for Economic Co-operation and Development. Our study focused on the bottom quartile of participants aged 10 and 15 years, including 7737 and 7439 individuals from each age group. Optimism and cooperation consistently emerged as the central skills of social–emotional competence across both age groups. When comparing network structures, there was a significant difference between children and adolescents. The connectivity of social–emotional networks was stronger among adolescents, indicating closer skill associations. Understanding these developmental differences is important for educators and practitioners to more effectively support the social–emotional development of children and adolescents experiencing social–emotional difficulties.

Exploring the spatial interference effects elicited by social and non‐social targets: A conditional accuracy function approach

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.

Leading by example: Experimental evidence that therapist lived experience disclosures can model the path to recovery for clients

A common guideline for self-disclosure is that therapists should only share recovered personal experiences with clients (i.e., no longer distressing). However, theoretical rationale and empirical support for this claim is limited. Drawing on identity leadership theorizing, we investigated whether recovery disclosures are beneficial to the extent that they signal a therapist's aspirational prototypicality (i.e., embodiment of an aspirational identity for clients). Across two experimental studies (N = 545), we recruited clients, therapists and general population adults. Participants read a group therapy for depression vignette in which the therapist disclosed: nothing, professional experience with depression, current depression, recovered depression or recovered anxiety. Participants rated the prototypicality of the therapist, the extent to which they perceived the therapist positively, the therapist's expertness and the expected prognosis for therapy. Contrary to our hypotheses, the type of disclosure did not significantly affect positive perceptions, expertness or expected prognosis ratings. However, the therapist disclosing a recovered and relevant condition (recovered depression) was rated as significantly more aspirationally prototypical than the other therapists. Given prior evidence that group therapists are more effective when viewed as aspirationally prototypical, our findings suggest that recovery disclosures may represent one way therapists can signal their prototypicality and enhance their effectiveness.

Undoing Whiteness in Disability Studies: The Special Education System and British South Asian Mothers By Sana Rizvi, Palgrave Macmillan. 2021. VII+224 pp; €44.99 (eBook). ISBN: 9783030795733; DOI:

Beyond the screen: Dissecting the nexus of victimization and cyberhate among adolescents through excessive internet use, online interactions with strangers and parental restrictions

Prior research has established that being a target of offline and online victimization might function as a significant risk factor that increases the likelihood of adolescents' involvement in cyberhate. Yet, relatively little is known about the mediating and moderating mechanisms underlying this relationship. To fill this important gap in knowledge, the present study aims to examine (1) whether excessive Internet use and contact with unknown people online act as sequential mediators in the relationship between overall victimization and youth's involvement in cyberhate; and (2) whether restrictive parental mediation has any role to play in moderating this relationship. The findings suggest that adolescents who experience victimization are more likely to turn to using the Internet excessively, and consequently interact with strangers online, which in turn makes them more prone to becoming victim to cyberhate or spreading hateful content online themselves. Moreover, restrictive parental mediation was shown to exacerbate the link between excessive Internet use and adolescents' contacts with unknown people online, thereby putting them at higher risk of cyberhate involvement. The current study emphasizes the need for a balanced approach to parental mediation – one that fosters open communication, trust and the development of digital literacy skills.

Fostering sustainability in higher education: Leveraging human behavior in organizations By Elise L. Amel, Christie M. Manning, Catherine S. Daus, Makayla Quinn, Cham, Switzerland: Springer. 2023. £109.99, ISBN 9783031505546

Artificial intelligence chatbots mimic human collective behaviour

Artificial Intelligence (AI) chatbots, such as ChatGPT, have been shown to mimic individual human behaviour in a wide range of psychological and economic tasks. Do groups of AI chatbots also mimic collective behaviour? If so, artificial societies of AI chatbots may aid social scientific research by simulating human collectives. To investigate this theoretical possibility, we focus on whether AI chatbots natively mimic one commonly observed collective behaviour: homophily, people's tendency to form communities with similar others. In a large simulated online society of AI chatbots powered by large language models (N = 33,299), we find that communities form over time around bots using a common language. In addition, among chatbots that predominantly use English (N = 17,746), communities emerge around bots that post similar content. These initial empirical findings suggest that AI chatbots mimic homophily, a key aspect of human collective behaviour. Thus, in addition to simulating individual human behaviour, AI-powered artificial societies may advance social science research by allowing researchers to simulate nuanced aspects of collective behaviour.

Psychology and gender: An advanced reader By Sadhana Avinash Natu (Ed.), London: Routledge India. 2024. 222 pp. ₹1295. ISBN: 9781032518732

The reliability of UFO witness testimony By V.‐J. Ballester Olmos & Richard W. Heiden (Eds.), Turin: Upiar Press. 2023. pp. 711

Personality psychology: A new perspective By Janek Musek, Switzerland: Springer Nature AG. 2024. Ebook £96.29. ISBN 978‐3‐031‐55308‐0

Bridging minds and machines: Unmasking the limits in text‐based automatic personality recognition for enhanced psychology–AI synergy

Text-based automatic personality recognition (APR) operates at the intersection of artificial intelligence (AI) and psychology to determine the personality of an individual from their text sample. This covert form of personality assessment is key for a variety of online applications that contribute to individual convenience and well-being such as that of chatbots and personal assistants. Despite the availability of good quality data utilizing state-of-the-art AI methods, the reported performance of these recognition systems remains below expectations in comparable areas. Consequently, this work investigates and identifies the source of this performance limit and attributes it to the flawed assumptions of text-based APR. These insights are obtained via a large-scale comprehensive benchmark and analysis of text data from five corpora with diverse characteristics and complementary personality models (Big Five and Dark Triad) applied to an assortment of AI methods ranging from hand-crafted linguistic features to data-driven transformers. Finally, the work concludes by identifying the open problems that can help navigate the limitations in text-based automatic personality recognition to a great extent.

Face and voice identity matching accuracy is not improved by multimodal identity information

Identity verification from both faces and voices can be error-prone. Previous research has shown that faces and voices signal concordant information and cross-modal unfamiliar face-to-voice matching is possible, albeit often with low accuracy. In the current study, we ask whether performance on a face or voice identity matching task can be improved by using multimodal stimuli which add a second modality (voice or face). We find that overall accuracy is higher for face matching than for voice matching. However, contrary to predictions, presenting one unimodal and one multimodal stimulus within a matching task did not improve face or voice matching compared to presenting two unimodal stimuli. Additionally, we find that presenting two multimodal stimuli does not improve accuracy compared to presenting two unimodal face stimuli. Thus, multimodal information does not improve accuracy. However, intriguingly, we find that cross-modal face-voice matching accuracy predicts voice matching accuracy but not face matching accuracy. This suggests cross-modal information can nonetheless play a role in identity matching, and face and voice information combine to inform matching decisions. We discuss our findings in light of current models of person perception, and consider the implications for identity verification in security and forensic settings.

The token undermining effect: When and why adding a small reward to a dated outcome makes it less preferred

The mere token strategy, which adds a small reward (token) to an option to increase attractiveness, is widely used in the consumer field. However, we conducted six studies that seek to confirm the ‘token undermining effect’, where adding a small token to a sooner and smaller reward (SS) paired with a later and larger reward (LL) decreases the preference for the SS. The results showed that the effect persists across various choice sets, participant populations, reward amounts, delays, outcome properties and regardless of whether the scenarios are incentivized. However, an important boundary condition was that the token must share the same nature as the original option. Furthermore, we used mouse cursor tracking methods to examine the underlying process of attention allocation and demonstrated that adding a small token to the SS leads individuals to allocate more attention to the magnitude dimension than to the delay dimension, ultimately decreasing their preference for the SS. Therefore, managers and policymakers should use the mere token strategy with caution as it could backfire.

Sounds of the future and past

We report evidence of sound symbolism for the abstract concept of time across seven experiments (total N = 825). Participants associated the future and past with distinct phonemes (Experiment 1). In particular, using nearly 8000 pseudowords, we found associations between the future and high front vowels and voiced fricatives/affricatives, and between the past and /θ/ and voiced stops (Experiment 2). This association was present not only among English speakers but also by speakers of a closely related language (German) and those of a more distantly related language (Hungarian; Experiment 3). This time-sound symbolism does not appear to be due to embodied articulation (Experiment 4). In sum, these studies identify a robust time sound symbolism effect, along with tests of underlying mechanisms.

A challenge to identity: Identity processing style and moral injury

Moral injury is a potentially deleterious mental health outcome that can result from exposure to morally challenging events. Treatment of moral injury is currently hindered by incomplete understanding of its underlying mechanisms. Theories of adaptation posit that maintaining a coherent sense of self while realigning one's sense of self with reality aids in adaptation following a disruptive life event. Differences in identity processing style are thought to impact the extent to which an individual engages with the challenges of maintaining a coherent sense of self following identity-related challenges. However, little is known about how identity processing style relates to moral injury event-related distress. This study sought to investigate a hypothesized relationship between identity processing style and event-related distress as well as alternative outcomes including traumatic stress, depression and anxiety. Adults (N = 167) who had been exposed to a potentially morally injurious event were recruited online and completed validated measures of event-related distress, traumatic stress, depression, anxiety and identity processing style. There were significant positive associations between diffuse-avoidant processing and all mental health outcomes, no significant associations between informational processing and any mental health outcomes, and significant negative associations between normative processing and event-related distress and depression.

Individual differences in the evolution of causal illusions

In this research, we investigated individual differences in the formation and persistence of causal illusions. In a re-analysis of existing data, we identified two clusters of participants – persistent and adjusting – based on their trajectories in learning from repeated exposure to null contingencies. The persistent cluster maintained stable causal illusions, while the adjusting cluster demonstrated a reduction over time. This re-analysis provided a nuanced understanding of individual differences in causal learning, emphasizing the differential role of probability estimations in predicting causal judgements. These findings were replicated in a subsequent study, highlighting the robustness of the identified effects. In a pre-registered study, we extended the paradigm to include a second phase (active phase) to assess how individual differences in causal illusion trajectories in the passive phase would manifest when participants had agency in the information gathering process. The results were consistent with those of the two previous studies and confirmed our primary hypothesis that the adjusting cluster would exhibit a lower tendency to introduce the candidate cause on learning trials, and would, therefore, observe a higher frequency of cause–absent trials. Together, these studies provide comprehensive insights into the underpinnings of causal illusion development and persistence, potentially informing de-biasing interventions.

Computers and chess masters: The role of AI in transforming elite human performance

Advances in Artificial Intelligence (AI) have made significant strides in recent years, often supplementing rather than replacing human performance. The extent of their assistance at the highest levels of human performance remains unclear. We analyse over 11.6 million decisions of elite chess players, a domain commonly used as a testbed for AI and psychology due to its complexity and objective assessment. We investigated the impact of two AI chess revolutions: the first in the late 1990s with the rise of powerful PCs and internet access and the second in the late 2010s with deep learning-powered chess engines. The rate of human improvement mirrored AI advancements, but contrary to expectations, the quality of decisions mostly improved steadily over four decades, irrespective of age, with no distinct periods of rapid improvement. Only the youngest top players saw marked gains in the late 1990s, likely due to better access to knowledge and computers. Surprisingly, the recent wave of neural network-powered engines has not significantly impacted the best players – at least, not yet. Our research highlights AI's potential to enhance human capability in complex tasks, given the right conditions, even among the most elite performers.

Automated face recognition assists with low‐prevalence face identity mismatches but can bias users

We present three experiments to study the effects of giving information about the decision of an automated face recognition (AFR) system to participants attempting to decide whether two face images show the same person. We make three contributions designed to make our results applicable to real-word use: participants are given the true response of a highly accurate AFR system; the face set reflects the mixed ethnicity of the city of London from where participants are drawn; and there are only 10% of mismatches. Participants were equally accurate when given the similarity score of the AFR system or just the binary decision but shifted their bias towards match and were over-confident on difficult pairs when given only binary information. No participants achieved the 100% accuracy of the AFR system, and they had only weak insight about their own performance.

The differences in essential facial areas for impressions between humans and deep learning models: An eye‐tracking and explainable AI approach

This study explored the facial impressions of attractiveness, dominance and sexual dimorphism using experimental and computational methods. In Study 1, we generated face images with manipulated morphological features using geometric morphometrics. In Study 2, we conducted eye tracking and impression evaluation experiments using these images to examine how facial features influence impression evaluations and explored differences based on the sex of the face images and participants. In Study 3, we employed deep learning methods, specifically using gradient-weighted class activation mapping (Grad-CAM), an explainable artificial intelligence (AI) technique, to extract important features for each impression using the face images and impression evaluation results from Studies 1 and 2. The findings revealed that eye-tracking and deep learning use different features as cues. In the eye-tracking experiments, attention was focused on features such as the eyes, nose and mouth, whereas the deep learning analysis highlighted broader features, including eyebrows and superciliary arches. The computational approach using explainable AI suggests that the determinants of facial impressions can be extracted independently of visual attention.

Explainability increases trust resilience in intelligent agents

Even though artificial intelligence (AI)-based systems typically outperform human decision-makers, they are not immune to errors, leading users to lose trust in them and be less likely to use them again—a phenomenon known as algorithm aversion. The purpose of the present research was to investigate whether explainable AI (XAI) could function as a viable strategy to counter algorithm aversion. We conducted two experiments to examine how XAI influences users' willingness to continue using AI-based systems when these systems exhibit errors. The results showed that, following the observation of algorithms erring, the inclination of users to delegate decisions to or follow advice from intelligent agents significantly decreased compared to the period before the errors were revealed. However, the explainability effectively mitigated this decline, with users in the XAI condition being more likely to continue utilizing intelligent agents for subsequent tasks after seeing algorithms erring than those in the non-XAI condition. We further found that the explainability could reduce users' decision regret, and the decrease in decision regret mediated the relationship between the explainability and re-use behaviour. These findings underscore the adaptive function of XAI in alleviating negative user experiences and maintaining user trust in the context of imperfect AI.

Generative neural networks for experimental manipulation: Examining dominance‐trustworthiness face impressions with data‐efficient models

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.

Editorial: Introducing the British Psychological Society journals' landmark special issue on the United Nation's Sustainability Goals

People have different expectations for their own versus others' use of AI‐mediated communication tools

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.

Scoping review on natural language processing applications in counselling and psychotherapy

Recent years have witnessed some rapid and tremendous progress in natural language processing (NLP) techniques that are used to analyse text data. This study endeavours to offer an up-to-date review of NLP applications by examining their use in counselling and psychotherapy from 1990 to 2021. The purpose of this scoping review is to identify trends, advancements, challenges and limitations of these applications. Among the 41 papers included in this review, 4 primary study purposes were identified: (1) developing automated coding; (2) predicting outcomes; (3) monitoring counselling sessions; and (4) investigating language patterns. Our findings showed a growing trend in the number of papers utilizing advanced machine learning methods, particularly neural networks. Unfortunately, only a third of the articles addressed the issues of bias and generalizability. Our findings provided a timely systematic update, shedding light on concerns related to bias, generalizability and validity in the context of NLP applications in counselling and psychotherapy.

Assessing novelty, feasibility and value of creative ideas with an unsupervised approach using GPT‐4

Creativity is defined by three key factors: novelty, feasibility and value. While many creativity tests focus primarily on novelty, they often neglect feasibility and value, thereby limiting their reflection of real-world creativity. In this study, we employ GPT-4, a large language model, to assess these three dimensions in a Japanese-language Alternative Uses Test (AUT). Using a crowdsourced evaluation method, we acquire ground truth data for 30 question items and test various GPT prompt designs. Our findings show that asking for multiple responses in a single prompt, using an ‘explain first, rate later’ design, is both cost-effective and accurate (r = .62, .59 and .33 for novelty, feasibility and value, respectively). Moreover, our method offers comparable accuracy to existing methods in assessing novelty, without the need for training data. We also evaluate additional models such as GPT-4 Turbo, GPT-4 Omni and Claude 3.5 Sonnet. Comparable performance across these models demonstrates the universal applicability of our prompt design. Our results contribute a straightforward platform for instant AUT evaluation and provide valuable ground truth data for future methodological research.

Identifying subtypes in persons, situations and person–situation interactions: Categorical latent state–trait modelling approaches

The latent state–trait theory posits that a psychological construct may reflect stable influences specific to a person (i.e., trait), ephemeral influences from situations (i.e., state), and interactions between them (i.e., state–trait interactions). Researchers conventionally apply mixture modelling to explore heterogeneity in variables by identifying homogenous classes with respect to the measured variable, yet rarely distinguishing between person- and situation-specific classes. The current study introduces novel categorical latent state–trait models to identify subgroups in states and traits, quantifying the effects of person-specific classes, situation-specific classes, and person–situation interactions. The proposed models are applied to an empirical dataset. We discuss statistical inference, effect size measures, and model visualization for the proposed models. Based on realistic parameter values from the empirical dataset, preliminary simulation studies were conducted to investigate models’ performances. Bayesian estimation in the proposed models allows flexible testing of a wide range of hypotheses related to state, trait, and interaction effects. We discuss limitations and future directions.

Decoding the language of first impressions: Comparing models of first impressions of faces derived from free‐text descriptions and trait ratings

First impressions formed from facial appearance predict important social outcomes. Existing models of these impressions indicate they are underpinned by dimensions of Valence and Dominance, and are typically derived by applying data reduction methods to explicit ratings of faces for a range of traits. However, this approach is potentially problematic because the trait ratings may not fully capture the dimensions on which people spontaneously assess faces. Here, we used natural language processing to extract ‘topics’ directly from participants' free-text descriptions (i.e., their first impressions) of 2222 face images. Two topics emerged, reflecting first impressions related to positive emotional valence and warmth (Topic 1) and negative emotional valence and potential threat (Topic 2). Next, we investigated how these topics were related to Valence and Dominance components derived from explicit trait ratings. Collectively, these components explained only ~44% of the variance in the topics extracted from free-text descriptions and suggested that first impressions are underpinned by correlated valence dimensions that subsume the content of existing trait-rating-based models. Natural language offers a promising new avenue for understanding social cognition, and future work can examine the predictive utility of natural language and traditional data-driven models for impressions in varying social contexts.

Explanation strategies in humans versus current explainable artificial intelligence: Insights from image classification

Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. Here, we examined human participants' attention strategies when classifying images and when explaining how they classified the images through eye-tracking and compared their attention strategies with saliency-based explanations from current XAI methods. We found that humans adopted more explorative attention strategies for the explanation task than the classification task itself. Two representative explanation strategies were identified through clustering: One involved focused visual scanning on foreground objects with more conceptual explanations, which contained more specific information for inferring class labels, whereas the other involved explorative scanning with more visual explanations, which were rated higher in effectiveness for early category learning. Interestingly, XAI saliency map explanations had the highest similarity to the explorative attention strategy in humans, and explanations highlighting discriminative features from invoking observable causality through perturbation had higher similarity to human strategies than those highlighting internal features associated with higher class score. Thus, humans use both visual and conceptual information during explanation, which serve different purposes, and XAI methods that highlight features informing observable causality match better with human explanations, potentially more accessible to users.

Unveiling the factors of aesthetic preferences with explainable AI

The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences. Our models process these attributes as inputs to predict the aesthetic scores of images. Moreover, to delve deeper and obtain interpretable explanations regarding the factors driving aesthetic preferences, we utilize the popular Explainable AI (XAI) technique known as SHapley Additive exPlanations (SHAP). Our methodology compares the performance of various ML models, including Random Forest, XGBoost, Support Vector Regression, and Multilayer Perceptron, in accurately predicting aesthetic scores, and consistently observing results in conjunction with SHAP. We conduct experiments on three image aesthetic benchmarks, namely Aesthetics with Attributes Database (AADB), Explainable Visual Aesthetics (EVA), and Personalized image Aesthetics database with Rich Attributes (PARA), providing insights into the roles of attributes and their interactions. Finally, our study presents ML models for aesthetics research, alongside the introduction of XAI. Our aim is to shed light on the complex nature of aesthetic preferences in images through ML and to provide a deeper understanding of the attributes that influence aesthetic judgements.

Understanding anxiety through uncertainty quantification

Uncertainty has been a central concept in psychological theories of anxiety. However, this concept has been plagued by divergent connotations and operationalizations. The lack of consensus hinders the current search for cognitive and biological mechanisms of anxiety, jeopardizes theory creation and comparison, and restrains translation of basic research into improved diagnoses and interventions. Drawing upon uncertainty decomposition in Bayesian Decision Theory, we propose a well-defined conceptual structure of uncertainty in cognitive and clinical sciences, with a focus on anxiety. We discuss how this conceptual structure provides clarity and can be naturally applied to existing frameworks of psychopathology research. Furthermore, it allows formal quantification of various types of uncertainty that can benefit both research and clinical practice in the era of computational psychiatry.