I checked 15 psychology journals on Friday, May 15, 2026 using the Crossref API. For the period May 08 to May 14, I found 35 new paper(s) in 12 journal(s).

Advances in Methods and Practices in Psychological Science

The Language-Based Assessment Model Library: Open Model Sharing for Independent Validation and Broader Applications
August H. Nilsson, Veerle C. Eijsbroek, Zhuojun Gu, Katarina Kjell, Salvatore Giorgi, Roman Kotov, Adithya V. Ganesan, H. Andrew Schwartz, Oscar N. E. Kjell
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Language-based assessments (LBAs), quantitative estimates of scientific constructs based on language, have advanced methods in the psychological and social sciences for more than a decade. LBAs based on individuals’ prompted descriptions analyzed with large language models to produce scores of their psychological states and traits have shown strong convergence with the corresponding rating scales ( r > .80) and have often surpassed rating scales in predicting theoretically relevant behaviors (external criteria). Despite their high validity across numerous psychological outcomes and contexts, the broader adoption of LBA models (LBAMs) has been limited. Even when made available alongside research publications, these models often remain inaccessible because of technical complexities, inconsistent documentation, and the absence of a standardized repository. In this tutorial, we introduce a framework targeted to social and psychological scientists for accessible sharing models with others—the Language-Based Assessment Models (L-BAM) Library—and a toolkit for easily using LBAMs via the text package in R. L-BAM covers a wide range of models for assessing mental-health disorders (e.g., depression, anxiety), well-being (e.g., satisfaction with life, harmony in life), implicit motives (need for power, affiliation, and achievement), and more. The L-BAM Library aims to increase the availability and resource efficiency of LBAs of psychological constructs while encouraging replication, independent validation, and the broad application of preexisting LBAMs.

Behavior Research Methods

Adapting tree-based multiple imputation methods for multilevel data? A simulation study
Nico Föge, Jakob Schwerter, Ketevan Gurtskaia, Markus Pauly, Philipp Doebler
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When data have a hierarchical structure, such as students nested within classrooms, ignoring dependencies between observations can compromise the validity of imputation procedures. Standard (tree-based) imputation methods implicitly assume independence between observations, limiting their applicability in multilevel data settings. Although multivariate imputation by chained equations (MICE) is widely used for hierarchical data, it has limitations, including sensitivity to model specification and computational complexity. Alternative tree-based approaches have shown promise for individual-level data, but remain largely unexplored for hierarchical contexts. In this simulation study, we systematically evaluate the performance of novel tree-based methods—chained random forests (missRanger) and extreme gradient boosting (mixgb)—explicitly adapted for multilevel data by incorporating dummy variables indicating cluster membership. We compare these tree-based methods and their adapted versions with traditional MICE imputation in terms of coefficient estimation bias, type I error rates, and statistical power under different cluster sizes (25 and 50), missingness mechanisms (missing completely at random [MCAR], missing at random [MAR]), and missingness rates (10%, 30%, 50%), using both random intercept and random slope data generation models. The results show that MICE provides robust and accurate inference for level 2 variables, especially at low missingness rates (10%). However, the adapted boosting approach (mixgb with cluster dummies) consistently outperforms other methods for level 1 variables at higher missingness rates (30%, 50%). For level 2 variables, while MICE retains better power at moderate missingness (30%), adapted boosting becomes superior at high missingness (50%), regardless of the missingness mechanism or cluster size. These findings highlight the potential of appropriately adapted tree-based imputation methods as effective alternatives to conventional MICE in multilevel data analyses.
Analyzing interpersonal coordination through motion capture and cross-correlation: An integrated approach to magnitude, temporality, and morphology
Esteban Hurtado, Marisol Correa, Zamara Cuadros, Javiera Paredes, David Carré, Carlos Cornejo
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dynConfiR: An R package for sequential sampling models of decision confidence
Sebastian Hellmann, Michael Zehetleitner, Manuel Rausch
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The modeling of response times using sequential sampling models has a long history. Because choices, confidence judgments, and reaction times are closely linked in perceptual decisions, it seems only natural to simultaneously model these three outcome variables of a decision. In the package dynConfiR, we implemented various sequential sampling models of choice, response time, and decision confidence in R. This paper gives an overview of the package, which provides probability density functions as well as high-level functions for fitting parameters to empirical data, prediction of reaction time and response distributions, and simulation of artificial data sets. We describe the mathematical specifications of the implemented models and provide detailed descriptions of the implemented likelihood functions. In addition, we outline the workflow for applying the model to empirical data step-by-step: data preprocessing, model fitting, model prediction, quantitative model comparison, and visual assessment of model predictions. Finally, we present results from parameter and model recovery analyses and assess the precision of probability density calculations, illustrating the robustness of the implemented computations. Offering intuitive usability and high flexibility, the package is targeted at researchers in the fields of decision-making and confidence and does not require expert-level programming skills.
Comparing automated gaze classifiers in infant looking studies: Accuracy and vulnerability to environmental factors
Hiromichi Hagihara, Nanako Kimura, Lorijn Zaadnoordijk, Rei Yasuda, Rhodri Cusack, Sho Tsuji
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We evaluated the performance and environmental robustness of three state-of-the-art gaze classification algorithms designed for infant looking-time research: iCatcher+, OWLET, and an Amazon Rekognition-based model. Gaze classifications for each algorithm were compared to human-coded data using a novel dataset ( N = 47), and iCatcher+ demonstrated the highest agreement (78.4–85.4%). We then investigated the effect of environmental factors commonly encountered in webcam-based home experiments with infants. We quantified six factors: distance to the camera; infants’ left–right offset; facial rotation; facial movement; facial brightness; and spatial variability in facial brightness. Suboptimal recording conditions led to performance degradation for all algorithms. Even iCatcher+, while the most accurate overall, was susceptible, particularly when facial illumination was uneven (i.e., strong brightness variability) or when the head position moved substantially. These findings provide practical insights into the selection and deployment of gaze classification tools for infant research, and can be used to optimize instructions for participants in home webcam experiments. This study contributes to improving methodological transparency and reliability in remote infant eye-tracking research.
Robust Bayesian multilevel meta-analysis: Adjusting for publication bias in the presence of dependent effect sizes
FrantiĆĄek BartoĆĄ, Maximilian Maier, Eric-Jan Wagenmakers
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Meta-analyses often include multiple dependent effect sizes, yet current methods typically neglect the resulting within-study dependencies or fail to address model uncertainty and publication bias adequately. We extend robust Bayesian meta-analysis (RoBMA) to a multilevel framework, simultaneously handling within-study dependencies, model uncertainty, heterogeneity, moderators, and publication bias. Specifically, the three-level RoBMA integrates approximate Bayesian selection models with PET-PEESE adjustments within a hierarchical Bayesian setting. We illustrate the methodology through empirical examples and demonstrate its performance via simulations. The approach is implemented in the package and JASP.
An omnibus test for several dependent correlations
Zvi Drezner, George A. Marcoulides, Dawit Zerom
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Towards the ecological automated measurement of joint attention: Development of an interactive eye-tracking battery for joint attention in children with and without autism
Christy D. Yoon, Hedda Meadan, Frederick Shic
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Eye tracking has emerged as a powerful tool for advancing autism research, including diagnostics and interventions. However, studies on joint attention (JA) in autistic children have predominantly concentrated on the responding to joint attention (RJA) construct, with limited focus on the initiating joint attention (IJA) construct. Moreover, despite the interactive nature of JA, researchers have often relied on passive paradigms to study JA in this population. To address these gaps, we developed a gaze-contingent eye-tracking battery targeting three developmentally appropriate JA skills for young children: RJA, IJA to request, and IJA to comment or reference. The development process was multifaceted and iterative, involving a series of collaborative steps and the allocation of various resources. These steps included determining the motion format and stimulus type, designing and prototyping the stimuli, recruiting an actor to serve as a communication partner in the stimuli, recording and editing videos for the stimuli, and building and test-running the battery. We developed the Interactive Eye Tracking for Joint Attention (IET-JA) battery, which consists of 32 JA stimuli: 16 RJA, 8 IJA-Request, and 8 IJA-Comment/Reference. The stimuli are dynamic (i.e., videos) and feature a preprogrammed interactive human communication partner who is responsive to the participant’s gaze. The IET-JA takes approximately 8 minutes to complete, and its duration is expected to vary based on the participant’s level of engagement. Implications for advancing methodologies, fostering team science, and enhancing iterative processes are discussed.
Advantages and artifacts of high-speed OLED monitors for vision, eye-tracking, and EEG research
Olaf Dimigen, Arne Stein
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A bstract The recent introduction of organic light-emitting diode (OLED) monitors with refresh rates of 240 Hz or more opens new possibilities for their use as precise stimulation devices in vision research, experimental psychology, and electrophysiology. These affordable high-speed monitors, targeted at video gamers, promise several advantages over cathode ray tube (CRT) and liquid crystal display (LCD) monitors. Unlike LCDs, OLEDs have self-emitting pixels that can show true black, resulting in superior contrast, a broad color spectrum, and wide viewing angles. More importantly, the latest OLEDs offer excellent timing properties with minimal input lag and rapid transition times. However, OLED technology also has potential drawbacks, such as auto-brightness limiting (ABL), where luminance changes with the number of illuminated pixels. This study characterized a 240 Hz OLED monitor (ASUS PG27AQDM) in terms of its timing, temporal independence, spatial uniformity, viewing angles, warm-up time, and ABL behavior, and compared it with CRTs and LCDs. Results confirm excellent temporal performance, with CRT-like transition times, wide viewing angles, and good spatial uniformity. We show that ABL can be prevented with appropriate settings. However, we also report a novel type of luminance artifact on OLEDs, where high-contrast stimuli, shown for long durations, can create image persistence via localized warming or cooling of the panel. Finally, we demonstrate the monitor’s benefits in two time-critical paradigms: rapid invisible flicker tagging (RIFT) and saccade-contingent display changes. The latest consumer OLEDs provide precise and cost-effective stimulation devices for time-critical experiments, although some caution is warranted in experiments involving long exposures to high-contrast stimuli.
A stroke-level large-scale database of Chinese character handwriting and the OpenHandWrite_Toolbox for handwriting research
Zebo Xu, Shaoyun Yu, Mark Torrance, Guido Nottbusch, Nan Zhao, Zhenguang Cai
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Understanding what linguistic components (e.g., phonological, semantic, and orthographic systems) modulate Chinese handwriting at the character, radical, and stroke levels remains an important yet understudied topic. Additionally, there is a lack of comprehensive tools for capturing and batch-processing fine-grained handwriting data. To address these issues, we constructed a large-scale handwriting database in which 42 Chinese speakers each handwrote 1200 characters in a handwriting-to-dictation task. Additionally, we enhanced the existing handwriting package and provided comprehensive documentation for the upgraded OpenHandWrite_Toolbox. This toolbox allows users to easily modify the experimental design, capture the stroke-level handwriting trajectory, and batch-process handwriting measurements (e.g., latency and duration). Analysis of our large-scale database indicates that orthographic predictors affect handwriting preparation and execution at the character, radical, and stroke levels. Phonological factors influence handwriting at character and radical levels. Importantly, these lexical effects demonstrate hierarchical attenuation: they were most pronounced at the character level, followed by the radical, and weakest at the stroke level. These findings demonstrate that handwriting preparation and execution at the radical and stroke levels are closely intertwined with linguistic components. This database and toolbox offer valuable resources for future psycholinguistic and neurolinguistic research on the handwriting of characters and sub-characters across different languages.

Computers in Human Behavior

Generic title: Not a research article
Corrigendum to ‘Addressing FoMO and telepressure among university students: Could a technology intervention help with social media use and sleep disruption?’ [Computers in Human Behavior 93 (2019) Pages 192-199]
Arielle P. Rogers, Larissa K. Barber
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Decoding and controlling emotion in LLMs through human-aligned representational geometry with enhanced interpretability
Xiuwen Wu, Hao Wang, Zhiang Yan, Xiaohan Tang, Pengfei Xu, Wai-Ting Siok, Ping Li, Jia-Hong Gao, Bingjiang Lyu, Lang Qin
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Rethinking smartphone use and attention regulation among adolescents: A focus on habit and online basic psychological needs satisfaction
Haoyu Zhao, Jennifer Shapka
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Between the bars: Virtual reality and physical prison simulations link to reduced prejudice against incarcerated people
Marco Marinucci, Paolo Riva, Teresa Traversa, Maria Elena Magrin
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Group Processes & Intergroup Relations

People High in Social Dominance Orientation Prefer Bridge-Building to Dismantling Diversity Approaches
AnalĂ­a F. Albuja, Leigh S. Wilton
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Individuals vary in how they approach diversity; some emphasize relationship-building across groups ( bridging ), while others favor driving systemic change ( dismantling ). White participants ( N = 1224) evaluated an employee who embraced or forewent these approaches. Participants low in social dominance orientation (SDO)—those less supportive of hierarchy—evaluated targets who endorsed bridging (Study 1a) and dismantling (Study 1b) approaches more positively (i.e., warmer, more competent, preferred for leadership) than targets who opposed either of these approaches. However, when directly comparing targets who strongly endorsed both approaches, participants high in SDO distinguished between targets, preferring the target who endorsed bridging over the target who endorsed dismantling approaches (Study 2). This effect was mediated by anticipated discomfort. While both bridging and dismantling can promote equality, these studies uncover a subtle way structural change may be curtailed, even when not outright dismissed, thus limiting the full potential of diversity approaches.
Scarcity of Suffering: How Historical Victimhood Beliefs Shape Conspiracy Thinking via Cognitive Biases of Attribution, Intentionality and Memory
Theofilos Gkinopoulos, Maciej Siemiątkowski, MichaƂ Bilewicz
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Even decades after historical traumas, their scarcity shapes victimhood perceptions and beliefs about outgroups. In one correlational ( N = 369) and one experimental ( N = 510) study, we examined how exclusive versus inclusive victim beliefs predict outgroup, World War II-related, and generic conspiracy beliefs. We also tested the mediating role of three victimogenic cognitive biases: hostile intentions attribution, negative interpretation, and memory bias. Unlike prior work focusing mainly on exclusive victimhood, our studies provide the first direct comparison of both victimhood forms, revealing their distinct and sometimes opposing effects on conspiracy thinking. Correlational results showed that exclusive victim beliefs heightened conspiracy beliefs, with different biases mediating different conspiracy types. Experimental results showed that exclusive victim beliefs increased outgroup and generic conspiracy beliefs through negative interpretation bias, whereas inclusive victim beliefs reduced WWII and generic conspiracies by weakening hostile attribution bias. We discuss the implications of the findings for intergroup relations and post-conflict beliefs.

Journal of Experimental Social Psychology

Strategically prosocial: Using acts of kindness to secure more valuable interaction partners
Luuk L. Snijder, Mirre Stallen, Jörg Gross, Carsten K.W. De Dreu
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Why do people dislike gender role violators? A test of three models
Alan J. Lambert, Fade R. Eadeh, Svyatoslav Prokhorets, Giselle Gisser, Keralyn Siebrass
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Common = ineffective? A replication attempt of the normative dilution effect in the context of political apologies
Vlada Trofimchuk, Rebecca Littman
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Multiculturalism shapes moral judgments of sexist men across religious groups
Alexandra VĂĄzquez, Beatriz Alba
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Interpersonal synchrony modulates explicit and implicit self-other blurring: Evidence from an IAT
Manisha Biswas, Marcel Brass
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Journal of Personality and Social Psychology

Genetic and environmental factors underlying the associations between attachment styles and mental and physical health.
Keely A. Dugan, Jacob J. Kunkel, Stefania V. Vacaru, R. Chris Fraley, Theodore E. A. Waters, Matthew McGue, Robert F. Krueger, Glenn I. Roisman
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Speaking of gender: Language genderedness and its association with gender differences in personality across 48 languages.
Roxana Hofmann, René MÔttus
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From charm to conflict: Simulating narcissistic interpersonal dynamics with agent-based modeling.
Lena Herchenhahn, Emanuel Jauk, Martin Schoemann, Stefan Scherbaum, Veronika Lerche
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Multivariate Behavioral Research

An IRtree Model for Aberrant Response and Missing Data
Fangbin Chen, Daxun Wang, Yan Cai, Dongbo Tu
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How to Use Residual Dynamic Structural Equation Modeling to Study Individual Differences and Intraindividual Variability in Experimental Factorial Designs: A Tutorial
Benedikt Langenberg, Jonathan L. Helm, Connor J. McCabe, Thomas GĂŒnther, Axel Mayer
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Organizational Research Methods

The Case for Reporting Control Variable Coefficients
Arturs Kalnins, J. Myles Shaver
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We argue that reporting control variable results strengthens the transparency and credibility required for programmatic knowledge building in regression-based empirical research. Control variables are not just technical adjustments; their results provide diagnostic information that can reveal otherwise hidden biases and model misspecification. We present a practical multistep approach that employs control variable coefficients to uncover harmful combinations of multicollinearity, omitted variable biases and correlated measurement error. These harmful combinations, in turn, may generate type 1 errors (false positives) among variables of theoretical interest. We also show how to distinguish true suppressor effects from artifacts of poor model specification. Full reporting supports programmatic research by enabling scholars to compare results across studies, build on prior findings, and refine theory over time. Based on these benefits, we challenge a recent call to omit control variable results from manuscripts. Instead, we recommend that journals and reviewers require their inclusion in all published results tables.

Personality and Social Psychology Bulletin

Receiving Applause “From the Right”: Punishing Freeriding Is Socially Rewarded by Those High in Right-Wing Authoritarianism
Richard Rau, Luise Hönig, Mitja D. Back, Michael P. Grosz
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Most social groups punish freeriders (i.e., individuals who receive the same benefits from the group as others, despite contributing less to its success). In small groups, individual group members (rather than established authorities) typically implement this punishment spontaneously, and punishers may consequently be awarded social status by their peers. Here, we tested the preregistered hypothesis that this way of acquiring status works best when fellow group members are high, rather than low, in right-wing authoritarianism (RWA). The hypothesis was supported in a laboratory-based behavioral study ( N = 667) in which small groups interacted in a financially incentivized repeated public goods game involving punishment (i.e., a social dilemma that puts immediate individual benefits at odds with long-term collective interests). Linking the process of status acquisition to peer RWA significantly advances the understanding of social dynamics in small groups.
Comparing Trait-Wise and Profile-Wise Approaches to Assess the Links Between Metaperceptions and Romantic Interest During Speed-Dating
Hasagani Tissera, Nickola C. Overall, Emily J. Cross, Lauren J. Human, John E. Lydon
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Our perceptions of how we come across to others—metaperceptions—potentially shape whether romantic connections flourish or fade. The current study advanced the investigation of metaperceptions in relationship initiation in two ways: (a) by comparing two leading approaches to assessing meta-accuracy and meta-bias (the profile-wise social accuracy model and the trait-wise truth and bias model) and (b) by examining how metaperceptions of evaluative mate attributes (attractiveness, trustworthiness, status) relate to romantic interest. Using data from a naturalistic speed-dating study ( N = 214, 1,730 dyads), we found that perceivers who believed they were seen by others in line with what is normative (meta-normativity) expressed more romantic interest in others, whereas perceivers who underestimated how positively they were seen expressed lower romantic interest. In contrast, more accurate metaperceptions predicted greater romantic interest from others. These findings demonstrate that different analytic approaches offer unique insights into the role of metaperceptions in relationship initiation.
What Childhood Leaves Behind: Cognitive Ability and Trust in Adulthood
Chris Dawson
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This article challenges the idea that cognitive ability uniformly predicts prosocial traits. Using data from a large, nationally representative U.K. sample ( N = 24,140), we test a moderated mediation model in which childhood disadvantage is associated with generalized trust both directly and indirectly via cognitive ability, while also moderating the association between cognitive ability and trust. We find that childhood disadvantage is associated with lower cognitive ability—measured across memory, verbal fluency, fluid reasoning, and numerical reasoning—and with lower generalized trust in adulthood. We also find that cognitive ability is positively associated with generalized trust; however, this relationship is significantly attenuated among those who experienced childhood disadvantage. These results persist after adjusting for current socioeconomic factors. The pattern whereby early-life disadvantaged environments are associated with differences in cognitive development and with constrained social returns to cognitive ability is likely to reinforce social immobility.
Invisibility Is Dynamic
Elia Q. Y. Lam, Rebecca Neel
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Interpersonal invisibility is a consequential form of stigmatization but is not well-understood. Existing work has largely focused on who feels invisible (between-person effects) rather than when people feel invisible (within-person effects). Five studies ( N = 3,575) examine when people feel invisible. In Studies 1 and 2, Black, East Asian, and White American men and women report how invisible they feel to men and women motivated to protect themselves or to seek a romantic partner. Studies 3, 4, and 5 additionally explore invisibility to same- and other-race people. Results show that invisibility is dynamic: Participants report that they are invisible to some people and not to others, depending on the combination of their own race and gender with the race, gender, and goals of the other person. These findings speak to theories of invisibility and constitute a critical development in our understanding of when and why people feel invisible to others.

Psychological Methods

Assessing qualitative individual differences with Bayesian hierarchical latent-mixture models.
Martin Schnuerch, Jeffrey N. Rouder
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Modeling psychological time series with multilevel hidden Markov models: A tutorial.
Emmeke Aarts, Jonas Haslbeck
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Psychological Science

Motive Alignment Promotes Adolescents’ Proenvironmental Behavior: A Field Experiment in Two Cultures
Jenna Spitzer, Stathis Grapsas, Astrid M. G. Poorthuis, Fan Li, Yue Song, Sander Thomaes
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Realizing a sustainable future requires the active participation of today’s young generations. How can we foster adolescents’ proenvironmental engagement? In a preregistered, cross-national, longitudinal field experiment, we tested a novel approach to promoting adolescent behavior change: motive alignment. We hypothesized that presenting proenvironmental behavior as aligned with adolescents’ developmentally salient motives (in this case, autonomy and peer status) would enhance their engagement. In Study 1 (the Netherlands), a motive-alignment (versus control) intervention implemented in secondary schools increased adolescents’ proenvironmental food choices on the day of the intervention. Although this effect faded after 4 weeks, participants in the intervention condition continued to donate more to an environmental organization at follow-up. In Study 2 (China), we replicated these findings. Motive alignment thus offers a promising approach to strengthen interventions promoting adolescents’ proenvironmental behavior; it presents scalable and affordable opportunities to foster youth behavior change.
Retributive Sentiments Track Both Deterrent and Compensatory Concerns in a Small-Scale Society and a WEIRD Sample
LĂ©o Fitouchi, Manvir Singh
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Evolutionary theories suggest that retributive sentiments evolved to deter antisocial behavior, yet psychological evidence shows punitive sentiments imperfectly optimize deterrence. Recent theories resolve this paradox, suggesting that retributive sentiments serve to restore mutual benefit between partners by both compensating the victim and imposing an additional deterrent cost on the transgressor. In four experiments, we tested predictions of this hypothesis with adults from a small-scale, politically decentralized society (Mentawai horticulturalists, Indonesia; N = 74) and a large-scale society (the United States; N = 600). Consistent with compensatory concerns, participants demanded that victims be rewarded in the currency of their loss and that more severe punishment be imposed when victims suffered more, holding aggressor benefit constant. Consistent with compensation being entangled with deterrence, participants endorsed additional penalties beyond restitution that were higher for recidivism and intentional offenses. This proximate entanglement of compensation and deterrence helps resolve apparent contradictions about the function of punishment in humans.

Psychology of Popular Media

The associations between media multitasking, sleep outcomes, and trait mindfulness.
El-Lim Kim, Alena Rogojina, Kyle Samson
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