Individual Differences Research Articles

Self-evaluations and the language of the beholder: objective performance and language solidarity predict L2 and L1 self-evaluations in bilingual adults

People are often asked to self-evaluate their abilities, and these evaluations may not always reflect objective reality. Here, we investigated this issue for bilingual adults’ self-evaluations of language proficiency and usage. We specifically examined how people’s self-reported language solidarity impacted their first- (L1) and second-language (L2) self-evaluations, while statistically controlling for their objective language performance (i.e. LexTALE). We also investigated whether this impact varied for value-laden evaluations (e.g. how “good” am I at my L2) vs. usage-based evaluations (e.g. how often do I use my L2) for two sociolinguistically distinct groups (i.e. English-L1 speakers vs. French-L1 speakers in Montreal). Starting with value-laden self-evaluations, we found that French-L1 speakers with more favourable L2-English solidarity tended to underestimate their objective L2 ability, whereas French-L1 speakers with less favourable L2-English solidarity more accurately estimated their objective L2 ability. In contrast, English-L1 speakers with more favourable L2-French solidarity more accurately estimated their objective L2 ability than those with less favourable L2-French solidarity who underestimated their L2-French abilities. Turning to usage-based self-evaluations, we found that participants' self-evaluations were generally more accurate reflections of their performance, in a manner that was less affected by individual differences in self-reported language solidarity. This implies that language solidarity (or perhaps language attitudes more generally) can implicitly or explicitly impact bilingual adults’ language self-evaluations when these evaluations are value-laden. These data suggest that people’s language attitudes can bias how they perceive their abilities, although self-evaluations based on language use may be less susceptible to bias than those that are value-laden. These data have implications for the study of language and cognition that depend on self-assessments of individual differences and are relevant to work on how people self-assess their abilities generally.

Investigating heterogeneity in IRTree models for multiple response processes with score-based partitioning.

Item response tree (IRTree) models form a family of psychometric models that allow researchers to control for multiple response processes, such as different sorts of response styles, in the measurement of latent traits. While IRTree models can capture quantitative individual differences in both the latent traits of interest and the use of response categories, they maintain the basic assumption that the nature and weighting of latent response processes are homogeneous across the entire population of respondents. In the present research, we therefore propose a novel approach for detecting heterogeneity in the parameters of IRTree models across subgroups that engage in different response behavior. The approach uses score-based tests to reveal violations of parameter heterogeneity along extraneous person covariates, and it can be employed as a model-based partitioning algorithm to identify sources of differences in the strength of trait-based responding or other response processes. Simulation studies demonstrate generally accurate Type I error rates and sufficient power for metric, ordinal, and categorical person covariates and for different types of test statistics, with the potential to differentiate between different types of parameter heterogeneity. An empirical application illustrates the use of score-based partitioning in the analysis of latent response processes with real data.

Can Corporate Social Responsibility Shift Consumer Behavior? Insights from Scenario-Based Experiment in the Fast Fashion Industry

This study investigates the interplay between Corporate Social Responsibility (CSR) engagement and pricing strategies in shaping consumer purchase intentions in the fast fashion industry. Using a scenario-based experimental design with 267 participants, this research explores how different levels of CSR and two distinct price points influence purchasing behavior. Additionally, the moderating effects of individual differences, such as consumer wealth, motivations for sustainable behavior, and income, are examined. The findings indicate that higher levels of CSR engagement significantly enhance purchase intentions, particularly when combined with higher price points, perhaps due to consumer perceptions of CSR programs associated with more expensive brands as more authentic. However, price remains a critical factor for lower-income consumers, revealing an “ethical consumption gap” where affordability outweighs ethical concerns. Extrinsic motivations, such as social pressure, strongly influence wealthier consumers’ decisions, while intrinsic motivations show a more complex relationship with purchasing behavior. The findings provide practical insights for fast fashion brands, suggesting that aligning CSR with competitive pricing and authentic messaging is crucial for appealing to both price-sensitive and ethically conscious consumers.

Dissecting the Hippocampal Regulation of Approach-Avoidance Conflict: Integrative PerspectivesFrom Optogenetics, Stress Response, andEpigenetics.

Psychiatric disorders are multifactorial conditions without clear biomarkers, influenced by genetic, environmental, and developmental factors. Understanding these disorders requires identifying specific endophenotypes that help break down their complexity. Here, we undertake an in-depth analysis of one such endophenotype, namely imbalanced approach-avoidance conflict (AAC), reviewing its significant dependency on the hippocampus. Imbalanced AAC is a transdiagnostic endophenotype, being a feature of many psychiatric conditions in humans. However, it is predominantly examined in preclinical research through paradigms that subject rodents to conflict-laden scenarios. This review offers an original perspective by discussing the AAC through three distinct lights: optogenetic modulation of the AAC, which updates our understanding of the hippocampal contribution to behavioral inhibition; the impact of environmental stress, which exacerbates conflict and strengthens the stress-psychopathology axis; and inherent epigenetic aspects, which uncover crucial molecular underpinnings of environmental (mal) adaptation. By integrating these perspectives, in this review we aim to underline a cross-species causal nexus between heightened hippocampal activity and avoidance behavior. In addition, we suggest a rationale to explore epigenetic pharmacology as a potential strategy to tackle AAC-related psychopathology. This review assumes greater significance when viewed through the lens of advancing AAC-centric diagnostics in human subjects. Unlike traditional questionnaires, which struggle to accurately measure individual differences in AAC-related dimensions, new approaches using virtual reality and computer games show promise in better focusing the magnitude of AAC contribution to psychopathology.

Conscientiousness, trait self-control, and neuroticism predict individual differences in the variability of goal dimensions

When pursuing personal goals, individuals may experience fluctuations in goal-related dimensions like commitment and enjoyment. We present an approach to describe, analyze, and explain such within-person variability. In Part I, we determined to which extent within-person variability over time contributes to the total variability in goal dimensions, including between-person and between-goal variability. We observed strongest variability between goals, followed by variability over time, and between persons. In Part II, we estimated the within-person variability for each goal dimension using the indices dispersion (individual standard deviation), instability (root of squared successive differences), and inertia (autoregressive parameter). Dispersion was above-average for goal facilitation and progress and below-average for external motivation, value, and demand. Instability was above-average for facilitation and progress and below-average for commitment and demand. Inertia was above-average for facilitation and below-average for progress. Highlighting the relevance of self-regulatory competencies, we found that, when excluding outliers with extremely high variability, people with higher trait self-control, higher conscientiousness, and lower neuroticism showed lower variability. Both higher levels of trait self-control and conscientiousness predicted lower instability and higher inertia of goal dimensions. Conversely, higher neuroticism predicted higher dispersion and instability. We discuss these findings in the context of the Cybernetic Big Five theory.

Patterns and relationships of prolonged grief, post-traumatic stress, and depressive symptoms in Chinese shidu parents: Latent profile and network analyses

Parents who experience the trauma of losing an only child are called “shidu” parents in China. There are individual differences in post-loss outcomes.1,061 Chinese shidu parents were asked to complete questionnaires assessing prolonged grief, post-traumatic stress, and depressive symptoms. The mean age of the sample was 59.68 (SD = 7.52), with the average time since the loss was 9.46 years (SD = 7.05). Most participants were female (62.3%). The main cause of the loss was an unnatural case (52.7%). Latent profile analysis was used to identify similar symptom patterns. Network analysis was used to explore the relationships among symptoms within different subgroups. A two-profile model based on symptom severity identified a “low symptom severity” subgroup (n = 419) and a “high symptom severity” subgroup (n = 642). In the low symptom severity subgroup network, the most central symptoms were loss of interest, feeling numb, and meaninglessness. In the high symptom severity subgroup network, the most central symptoms were physiological cue reactivity, emotional pain, and feeling easily startled. Individual differences in the post-loss outcomes of Chinese shidu parents are reflected not only in symptom patterns but also in the relationships among symptoms.

Heart Rate Variability in Basketball: The Golden Nugget of Holistic Adaptation?

The main aim of this narrative review is to assess the existing body of scientific literature on heart rate variability (HRV) in relation to basketball, focusing on its use as a measure of internal load and vagal nerve responses. Monitoring HRV offers insights into the autonomic function and training-induced adaptations of basketball players. Various HRV measurement protocols, ranging from short-term to longer durations, can be conducted in different positions and conditions, such as rest, training, and sleep, to determine this key metric. Consistency and individualization in measurement protocols, responding to the athlete’s specific characteristics, is crucial for reliable HRV data and their interpretation. Studies on HRV in basketball have explored psychological adaptation, training effects, individual differences, recovery, and sleep quality. Biofeedback techniques show positive effects on HRV and anxiety reduction, potentially enhancing performance and stress management. The scientific literature on HRV in basketball could benefit from studies involving longer monitoring periods to identify significant trends and results related to training and recovery. Longitudinal HRV monitoring in teams with intense travel schedules could reveal the impact on athletes of all levels and ages, and, in this regard, individualized interpretation, considering the subjective recovery and fitness levels of athletes, is recommended to optimize training programs and performance. HRV provides insights into training and competitive loads, aiding in determining exercise intensities and training status. Additionally, HRV is linked to recovery and sleep quality, offering valuable information for optimizing player performance and well-being. Overall, HRV is a reliable tool for adjusting training programs to meet the specific needs of basketball players.

Indulging in Tempting Yet Unhealthy Delights: Exploring the Moderating Influence of Gender and Motivation for Healthy and Sustainable Eating

Individuals frequently encounter alluring food temptations that can disrupt their efforts to follow a healthy diet. These temptations may trigger pleasurable thoughts and sensations, potentially leading to unhealthy eating habits and obesity, which misalign with the goals of sustainable food systems to promote overall well-being. However, there is limited knowledge regarding how individual differences such as gender and motivation for healthy eating might impact individuals’ responses to unhealthy food temptations. In an experimental investigation, 245 participants were exposed to a tasty but low-nutrient food product (potato crisps). The results provide several new insights: (a) when individuals’ motivation for healthy eating is low, pleasurable experiences have a positive impact on perceived dietary quality; (b) pleasurable feelings also directly reduce willingness to consume potato crisps; (c) gender influences the relationship between pleasure-feeling and willingness to eat, with a negative relationship for women and a non-significant relationship for men; and (d) among women, there is a positive relationship between arousal and willingness to eat, while this relationship is non-significant for men. This study adds to the body of knowledge already available on food temptations, nutrition, and sustainable eating.

The Impact of Media Violence, Narcissism and Sex on Reactive and Proactive Aggression in Adolescents: A One-Year Follow-Up Study.

While the impact of violent media on aggression is well established, less is known about how individual differences influence this relationship over time. This longitudinal study addresses that gap by examining whether narcissism and sex moderated the effect of violent media consumption and reactive and proactive aggression one year later. A sample of 2,284 adolescents from Cyprus (Mage = 16, SDage = 0.89, 49.5% female) participated in this study. Hierarchical regressions, controlling for baseline levels of aggression and age, revealed distinct patterns: violent media and sex predicted reactive aggression, but narcissism did not. In contrast, violent media, sex, and narcissism all predicted proactive aggression. Notably, sex moderated the link between violent media and reactive aggression, with females showing a steeper increase than males. Both sex and narcissism moderated the violent media-proactive aggression association, with males being affected regardless of narcissism, while only highly narcissistic females showed an increase in proactive aggression. These findings show the importance of considering individual differences, such as sex and narcissism, to better understand how violent media influences different functions of aggression.

Adapting to Individual Differences: An Experimental Study of Language Evolution in Heterogeneous Populations.

Variations in language abilities, use, and production style are ubiquitous within any given population. While research on language evolution has traditionally overlooked the potential importance of such individual differences, these can have an important impact on the trajectory of language evolution and ongoing change. To address this gap, we use a group communication game for studying this mechanism in the lab, in which micro-societies of interacting participants develop and use artificial languages to successfully communicate with each other. Importantly, one participant in the group is assigned a keyboard with a limited inventory of letters (simulating a speech impairment that individuals may encounter in real life), forcing them to communicate differently than the rest. We test how languages evolve in such heterogeneous groups and whether they adapt to accommodate the unique characteristics of individuals with language idiosyncrasies. Our results suggest that language evolves differently in groups where some individuals have distinct language abilities, eliciting more innovative elements at the cost of reduced communicative success and convergence. Furthermore, we observed strong partner-specific accommodation to the minority individual, which carried over to the group level. Importantly, the degree of group-wide adaptation was not uniform and depended on participants' attachment to established language forms. Our findings provide compelling evidence that individual differences can permeate and accumulate within a linguistic community, ultimately driving changes in languages over time. They also underscore the importance of integrating individual differences into future research on language evolution.

Individual differences in music-induced interpersonal synchronization and self–other integration: the role of creativity and empathy

It has been demonstrated that moving together in synchrony to music makes us feel connected. Yet, little is known about the individual differences that shape the relationship between interpersonal synchronization to music and social bonding. The present research tests the hypothesis that this association is influenced by differences in empathy and creativity–two highly relevant factors in many musical activities. We implemented a synchronization task featuring a virtual drummer and measured self–other integration (SOI), a core component of social bonding. We employed a dual-measurement paradigm, incorporating both an explicit assessment ( Inclusion of Other in the Self scale) and an implicit assessment ( joint-Simon effect ) of SOI. Surprisingly, our analysis did not reveal explicit and implicit measurements correlating, nor were they similarly affected by interpersonal synchronization. This raises questions about the assessment of SOI in interpersonal synchronization experiments. Furthermore, we observed no moderating role of empathy or creativity in the association between interpersonal synchronization and SOI. Nevertheless, we found creativity to correlate with SOI. In light of this finding, we recommend placing greater emphasis on creativity as a decisive factor in the study of musical interaction.

To repeat or not repeat? A matter of economic reward and individual differences

This study explores the tendency to prefer more repetitive (but highly economic rewarding) tasks over less repetitive (and less economic rewarding) tasks in a sample of junior professionals, as well as their relationship to individual differences. Behavioral performance at a novel decisionmaking task, decision-making and personality profiles were collected. Findings showed that most junior professionals seem to prefer highly repetitive tasks (with greater economic reward) than less boring and less rewarding tasks. However, a cluster approach allows distinguishing between four distinct clusters of decision-makers: the “reward seekers”, the “temporizers”, the “balancers” and the “outsiders”. Each cluster of professionals exhibits unique individual differences in terms of decision-making styles and personality profiles (except for reward responsiveness). Evaluating junior professionals decision-making profiles in choosing which tasks to carry out is extremely relevant in company selection processes, as it allows you to assign the new resource to the best job position.

Three principles for the utility of simple tasks that assess elemental processes in parsing heterogeneity.

As clinical psychological science and biological psychiatry push to assess, model, and integrate heterogeneity and individual differences, approaches leveraging computational modeling, translational methods, and dimensional approaches to psychopathology are increasingly useful in establishing brain-behavior relationships. The field is ultimately interested in complex human behavior, and disruptions in such behaviors can arise through many different pathways, leading to heterogeneity in etiology for seemingly similar presentations. Parsing this complexity may be enhanced using "simple" tasks-which we define as those assaying elemental processes that are the building blocks to complexity. Using eyeblink conditioning as one illustrative example, we propose that simple tasks assessing elemental processes can be leveraged by and enhance computational psychiatry and dimensional approaches in service of understanding heterogeneity in psychiatry, especially when these tasks meet three principles: (a) an extensively mapped circuit, (b) clear brain-behavior relationships, and (c) relevance to understanding etiological processes and/or treatment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Domain‐General Individual Differences in Visual Comparison: Generalisability and Stability of Visual Comparison Ability Re‐Visited

ABSTRACTVisual comparison is the ability to ‘match’ visual stimuli like fingerprints or faces and decide whether they are from the same source or different sources (e.g., fingerprint‐matching). Limited research has investigated individual differences in this ability. In this paper, we present the results of three studies that explore the generalisability and stability of five visual comparison tasks (fingerprints, faces, artificial‐prints, footwear and toolmarks). We report data from three new studies examining the generalisability and stability of footwear comparison (Exp. 1) and toolmark comparison (Exp. 2), as well as the generalisability of all five comparison tasks (Exp. 3). Our results reveal that visual comparison ability generalises across all five comparison tasks and has stable test–retest reliability over time.

Revisiting the Alcohol-Aggression Link: The Impact of Alcohol Consumption Patterns

Laboratory studies have repeatedly reported a link between alcohol and aggression, yet many rely on single-dose administration methods and overlook variations in alcohol consumption patterns. The present study investigates the effects of alcohol on aggressive behavior using a double-blind, placebo-controlled cumulative drinking administration approach that mirrors the natural drinking behaviors often observed in pubs within a laboratory setting. This study also pioneers the examination of how alcohol consumption patterns (light or heavy) moderate the relationship between precise Breath Alcohol Concentration (BrAC) levels and extreme aggressive behavior. Seventy-five light (N=38) and heavy (N=37) alcohol drinkers were randomly assigned to alcohol (N=33) or placebo (N=42) conditions. Participants drank four drinks successively. Taylor's aggression paradigm was completed twenty minutes after each drink. Multilevel modeling was applied to analyze the effects of precise BrAC and account for within-person variability. Alcohol showed a dose-dependent effect on aggression; as alcohol levels rose, so did aggression (p<.001). Alcohol consumption pattern moderated the effect of cumulative BrAC on aggression, such that the effect was more substantial for light as compared with individuals who drink heavily (p=.03). The current study highlights the moderating role of alcohol consumption pattern in the association between precise BrAC levels and extreme aggression, offering insights into individual differences in susceptibility to alcohol-induced aggression, and supporting the I3 meta-theory (Finkel, 2014). The Findings underscore the importance of investigating the interplay between acute and chronic alcohol use on behavior, challenging conventional thresholds for hazardous drinking classification. Implications for future studies, legislators, and policymakers are discussed.

Beyond breathalyzers: AI-powered speech analysis for alcohol intoxication detection

Detecting potential alcohol inebriation or intoxication status holds paramount significance for social prevention and security. Beyond its association with long-term health effects, alcohol consumption can lead to immediate consequences, including reduced control over one’s actions, with traffic fatalities representing one of the most tragic outcomes.This study leveraged the Alcohol Language corpus, involving 162 subjects recorded both in sober and inebriated states. Participants provided 60 speech samples while sober and 30 when intoxicated, all within a realistic car setting using head-mounted microphones. Our research endeavors encompassed comprehensive stratified statistical tests to examine the impact of alcohol consumption on speech production while uncovering the influence of covariates such as age, gender, and drinking habits.Additionally, we introduced a speaker-neutral machine learning algorithm, based on the Domain-Adversarial Neural Network architecture. This approach aimed to overcome challenges posed by individual differences that often complicate intoxicated speech analysis. Notably, our findings highlighted the effectiveness of features like the RASTA-filtered auditory spectrum. Nevertheless, the results from statistical tests emphasized the need for techniques that minimize inter-subject variability.As for the automatic classification, the proposed architecture exhibited promising results, yielding a classification accuracy slightly exceeding 70% on an independent test set. Although preliminary, our research demonstrates the potential for detecting alcohol-induced speech changes, benefiting societal well-being and security. It also underscores the importance of developing strategies that account for individual differences while harnessing the power of automatic models to effectively distinguish between sober and intoxicated individuals.

Individual differences in acceptance of direct load control

Consumer acceptance of direct load control is becoming increasingly important as energy systems transition towards greater reliance on intermittent renewable energy sources. The objective of this paper is to better understand the attitudinal and socio-economic determinants of direct load control acceptance. To do so, we collect survey data from participants in 31 European countries (N = 5,970). Regression analyses testing a comprehensive model of attitudinal and socio-economic determinants of direct load control acceptance reveal that attitudes and beliefs specific to direct load control acceptance (social and personal norms, anticipated emotions, and outcome efficacy beliefs) predict acceptance, whereas more general attitudinal variables and socio-economic characteristics play no or only a secondary role. These findings substantially improve our understanding of direct load control acceptance. While European policy documents recognize the importance of individual attitudes for the success of demand response programs, reference to specific factors or processes is often missing due to lack of evidence. The present research helps fill this gap, and can inform the design of novel soft policy measures – highlighting the usefulness of facilitating positive peer influence, of reinforcing perceptions that engaging in demand response is effective, is the responsible thing to do, and also something to be proud of

Evolution of cooperation in heterogeneous populations with asymmetric payoff distribution.

The emergence and maintenance of cooperation is a complex and intriguing issue, especially in the context of widespread asymmetries in interactions that arise from individual differences in real-world scenarios. This study investigates how asymmetric payoff distribution affects cooperation in public goods games by considering a population composed of two types of individuals: strong and weak. The asymmetry is reflected in the fact that strong players receive a larger share of the public pool compared to weak players. Our results demonstrate that asymmetric payoff distribution can promote cooperation in well-mixed populations and trigger the co-evolution of cooperation between sub-populations of strong and weak players. In structured populations, however, the effect of asymmetric payoff distribution on cooperation is contingent on the proportion of strong players and the extent of their payoff share, which can either foster or inhibit cooperation. By adjusting the interaction probability between strong and weak players based on their spatial arrangement on lattice networks, we find that moderate interaction probabilities most effectively maintain cooperation. This study provides valuable insights into the dynamics of cooperation under asymmetric conditions, highlighting the complex role of asymmetrical interactions in the evolution of cooperation.

Mining soil heavy metal inversion based on Levy Flight Cauchy Gaussian perturbation Sparrow Search algorithm Support Vector Regression (LSSA-SVR)

Soil heavy metal pollution in mining areas poses severe challenges to the ecological environment. In recent years, machine learning has been widely used in heavy metal inversion by hyperspectral data. However, deterministic algorithms and probabilistic algorithms may confront local optimal solutions in practical applications. The local optimal solution is not the optimal value obtained within the entire defined interval, and as a result will affect the reliability of these approaches. This paper proposes a Levy Flight Cauchy Gaussian perturbation Sparrow Search algorithm Support Vector Regression (LSSA-SVR) soil heavy metal content prediction model. It introduces Levy Flight (LF) measurement and Cauchy Gaussian perturbation based on the Sparrow search algorithm. The LSSA-SVR model was shown to increase the breadth of solutions searched, avoiding the local optimal solution problem. When applied to mining soil heavy metal experiments, we found that the LSSA-SVR model gave a good fit for the elements Cu, Zn, As, and Pb. The correlation coefficients between the predicted results and the actual results of the four elements were all above 0.94. The heavy metal predicted results of LSSA-SVR have a small error margin in both the overall distribution and in individual differences. This study provides an efficient and accurate monitoring method for mining soil heavy metal inversion. It also provides strong support for environmental management and soil remediation.

Trajectories of depressive symptoms in Korean adults with diabetes: Individual differences and associations with life satisfaction and mortality.

We examined trajectories of depressive symptoms and their predictors in adults with diabetes. We assessed whether these trajectories were related to life satisfaction and mortality. Longitudinal, prospective observational study. We analysed data from 1217 adults with diabetes (aged ≥45 years) in the Korean Longitudinal Study of Aging (2006-2018). Three trajectories of depressive symptomology were identified in growth mixture models: low/stable (i.e., low and stable levels of symptoms; 85.56%), high/decreasing (i.e., high levels of symptoms with a decreasing trajectory; 7.47%), and moderate/increasing (i.e., moderate levels of symptoms with an increasing trajectory; 6.98%). Participants with poor perceived health status at baseline were more likely to be in the moderate/increasing or high/decreasing classes than in the low/stable class. The moderate/increasing class had the lowest satisfaction with quality of life, followed by the high/decreasing and low/stable classes. The moderate/increasing and the high/decreasing classes had lower satisfaction with relationships with spouse and children than the low/stable class. The high/decreasing class had a higher mortality risk than the low/stable class. Long-term monitoring of depressive symptoms in adults with diabetes is warranted given their potential adverse impact on life satisfaction and mortality.