I checked 15 psychology journals on Friday, October 09, 2026 using the Crossref API. For the period October 02 to October 08, I found 28 new paper(s) in 11 journal(s).

Behavior Research Methods

HelexKids 2.0: A linguistically annotated lexical database building on HelexKids
Anthi Revithiadou, Aris Terzopoulos, Georgia Niolaki, Giorgos Markopoulos, Konstantinos Avdelidis, Ilias Mittas, Kosmas Kosmidis
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HelexKids 2.0 represents an annotated expansion of the original HelexKids, a word frequency database compiled from Greek and Cypriot elementary school textbooks. This article presents the extended annotation methodology employed to enrich the database with part-of-speech tags, phonological properties (syllable count, phonetic transcription, orthographic and phonological syllabification, and stress), and morphological features (case, number, gender, and inflection class for nouns). All original frequency and lexical measures are retained, and new ones (e.g., PLD20, bigram and biphone frequencies) are added. The annotation process combined automated tools with extensive manual annotation and expert verification. We redesigned the database to assemble dynamically from the full set of textbooks, delivering results on the fly. The annotated database comprises 67,802 types and over 1.3 million tokens. We report on stress pattern distributions across major parts of speech and grade levels, show how stress is distributed by word class, and provide hierarchies of word-level syllabic templates. HelexKids 2.0 is freely available through the GRADIENCE project webpage and serves as a valuable resource for psycholinguistic and morphophonological research, as well as for educational applications.
A beta way: A tutorial on Bayesian beta regression for psychological research
Jason Geller, Robert Kubinec, Chelsea M. Parlett Pelleriti, Matti Vuorre
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Bayesian distributional models of executive functioning
Robert Kasumba, Zeyu Lu, Dom C. P. Marticorena, Mingyang Zhong, Paul Beggs, Anja Pahor, Geetha Ramani, Imani Goffney, Susanne M. Jaeggi, Aaron R. Seitz, Jacob R. Gardner, Dennis L. Barbour
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This study uses controlled simulations with known ground-truth parameters to evaluate how distributional latent variable models (DLVM) and Bayesian distributional active learning (DALE) perform compared with conventional independent maximum likelihood estimation (IMLE). DLVM integrates observations across multiple executive function tasks and individuals, allowing parameter estimation even under sparse or incomplete data conditions. To establish known ground truth, we uniformly sample individual sessions from a neural network-learned latent space and map them to distributional cognitive performance across different tasks. We then sample individual test items from these distributions using DALE, a random procedure, or a standard fixed-battery approach. Given the same observations, DLVM consistently outperformed IMLE, especially with smaller amounts of data, and converged faster to highly accurate estimates of the true distributions. In a second set of analyses, DALE adaptively guided sampling to maximize information gain, outperforming random sampling and fixed test batteries, particularly within the first 80 trials. These findings establish the advantages of combining DLVM’s cross-task inference with DALE’s optimal adaptive sampling, providing a principled basis for more efficient cognitive assessments.

Computers in Human Behavior

Online collective aggression in algorithmic environments: The roles of algorithm awareness, moral outrage, and negative descriptive norms
Zilin Wang, Jingyuan Yang, Xiaofei Qiao, Li Lei
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Sociotechnical imaginaries and acceptance of artificial intelligence in education: A longitudinal social media analysis
Özgehan UƟtuk, Ali Fuad Selvi, Zihan Xia
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From the Couch to the Arena: Prefrontal Cortex Network Dynamics of Reward and Loss Processing during Gameplay across Internet Gaming Disorder Symptom Severity
Xinyu Zhang, Dongyu Liu, Christian Montag, Jon D. Elhai, Haibo Yang
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The dynamics of climate change skepticism sharing on social media: Social identity, partisanship, and the impact of negative public opinion cues
Seo Yoon Lee
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Not naive, just gullible: psycho-cognitive vulnerability and fraud victimization in Italy
Chiara Barbara DadĂ , Laura Colautti, Matteo Robba, Alessia Rosi, Elena Cavallini, Paola Iannello
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Group Processes & Intergroup Relations

The Roots of Solidarity: Social Class Identity is Associated with Support for Reducing Inequality
Danny Hang, Ellen C. Reinhart, Hannah J. Birnbaum, Andrea G. Dittmann, Rebecca M. Carey
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The collective efforts of individuals with the least amount of resources, status, and power in a society can be a powerful tool for reducing inequality. In the current research, we examine the links between identity and support for reducing inequality . Recruiting two online surveys of individuals with objectively low social class standing (i.e., low education, low income) and applying regression analysis, we find that those who subjectively identify as lower (versus higher) social class were more likely to support reducing economic inequality (e.g., support policies that reduce economic inequality; Studies 1 and 2). Additionally, the more central their lower social class was to their identity, the more likely people were to support reducing economic inequality (Study 2). Taken together, these results provide novel support for the importance of social class identity in efforts to reduce economic inequality.

Journal of Experimental Social Psychology

Reevaluating the empirical support for a lens-based account: dissecting comparative fit and reconstructive category guessing
Roland Imhoff, Verena Heidrich
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Is honesty the best policy? Why people prefer false empathy over truthful unempathy
Zi Ye, Feiteng Long, Roujia Feng, Yi Zhang, Wilco W. van Dijk
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When less is more: Unifinal framing promotes intention to use social media for social connection
David S. Lee, Daniel Kulesza
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Everyday conceptualizations of patience
Samuel Murray, Devon Guzy, Áine Flynn
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Multivariate Behavioral Research

When Nesting is Nuisance in Cluster Sampled Longitudinal Research
James Peugh, Francis Huang, Sonja D. Winter
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Personality and Social Psychology Bulletin

Should I Stay or Should I Go? Preference for Consistency Predicts Choice Perseveration in the Monty Hall Problem
Agata Gasiorowska, Dariusz Dolinski, Michal Folwarczny, Tobias Otterbring
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Five incentivized studies ( N = 5,354) tested whether preference for consistency (PfC) predicts staying with one’s initial choice in the Monty Hall problem, despite the fact that switching maximizes the probability of winning. Studies 1 and 2 found that higher PfC predicts staying, even after controlling for need for closure, preference for structure, intolerance of uncertainty, conspiracy beliefs, and numerical competence. Studies 3 and 4 provided experimental evidence that incentives moderated the link between PfC and staying, but higher (vs. lower) PfC only attenuated rather than eliminated incentive sensitivity. Study 5 identified anticipated regret over switching and losing as a mechanism underlying the effect, showing that the link between PfC and staying held across cultural contexts, although its magnitude was culturally calibrated. Together, this research shows that consistency motivation governs choice perseverance in a task that is intentionally impersonal and assumed to be driven by probabilistic reasoning rather than motivational forces.

Psychological Bulletin

Contributions of the general factor of intelligence to cognitive performance across ability levels and age: An individual participant data meta-analysis of child and adolescent norming data.
Moritz Breit, Martin Brunner, Julian Preuß, Monika Daseking, GĂŒnter Esser, Alexander Grob, Jan-Philipp Freudenstein, Ulf Kieschke, Ludwig Kreuzpointner, Franz Pauls, Christoph Perleth, Gabriele Ricken, Stefan Schipolowski, Ulrich Schroeders, Franziska Walter, Oliver Wilhelm, Anne Wyschkon, Franzis Preckel
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A meta-analytic review of the associations between patterning and academic achievement.
Giulia A. Borriello, Tongyao Zhang, Victor Wei Wang, Peng Peng, Emily R. Fyfe
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Childhood emotional abuse and adult psychopathology: A multilevel meta-analytic review.
Noga Miron, Wendy M. D'Andrea, Eran Barzilai, Shoshana Krohner, Ellen H. Yates, Samuel G. Conner Self, E. Samuel Winer, Ashley M. Doukas, Joseph Spinazzola
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A systematic review and meta-analysis of partial correlations between caregiver cognitive stimulation in early childhood and child development.
Sarah F. Hatch, Noelle M. Suntheimer, Abigail W. Otwell, Laura Tang, Dana C. McCoy, Sharon Wolf
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Toward a unified process model of situational frustration, need deprivation, and behavioral compensation: A meta-analytic review.
Maximilian Agostini, N. Pontus Leander, Jannis Kreienkamp, Justin König, Catharina Gerigk, Russell Spears
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Psychological Methods

Regularized multigroup exploratory approximate factor analysis with orthogonal factors.
Katrijn Van Deun, TrĂ  LĂȘ, Jakub Malinowski, Floortje Mols, Dounya Schoormans
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Psychological Science

Face-Matching Lineups: A Method to Control Mistaken Identifications in Video Evidence
Camryn N. Yuen, Daniel M. Bernstein, Andrew M. Smith, Rebecca C. Ying, Ryan J. Fitzgerald
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When crime is caught on video, suspects can be identified by matching their faces to the perpetrator in the footage. However, errors in face-matching decisions have led to wrongful arrests. We tested face-matching in a nonprofessional student sample from a Canadian university ( N = 905) with one-to-one comparisons and lineups. On the basis of findings in the eyewitness identification literature, we hypothesized that if face-matching lineups were fair and included known-innocent fillers (i.e., nonsuspects), they would control the error rate on trials with innocent suspects and increase the accuracy of suspect “match” responses. This hypothesis was supported. However, the accuracy of suspect-nonmatch responses was greater for one-to-one comparisons than for lineups. Additionally, we found that applying wisdom-of-crowd approaches to multiple independent decisions could eliminate errors in both match and nonmatch responses. Whether to control face-matching errors with lineups, with the wisdom-of-crowds, or with both depends on practical considerations.
Do Children Who Develop Faster Go on to Age Faster in Midlife?
J. Kathy Xie, Avshalom Caspi, Kathleen Mullan Harris, Allison E. Aiello, HonaLee Harrington, Renate Houts, Christopher Kositzke, Daniel W. Belsky, Laurel Raffington, Jay Belsky, Sandhya Ramrakha, Reremoana F. Theodore, Terrie E. Moffitt
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We quantified the association between rate of child development and pace of midlife aging in the Dunedin Study and the Add Health Study. Physical development was quantified in Dunedin participants ( N = 1,037; age 45) using a composite comprised of (1) birth weight for gestational age, (2) toddler weight gain, (3) timing of behavioral milestones, (4) adiposity-rebound age, (5) timing of adolescent growth spurt, and (6) tempo of adolescent growth spurt. Social development was quantified using the Vineland Social Maturity Scale. Multi-organ-system (cardiovascular, metabolic, renal, immune, dental, pulmonary) longitudinal biological aging was used as the adult outcome. Fast physical development in childhood was associated with faster midlife aging. This was replicated in Add Health ( N = 1,537; age range = 33–44 years), where girls who menstruated earlier had faster midlife aging. By contrast, faster social development in childhood was associated with slower midlife aging. Findings contribute initial empirical evidence characterizing the link between child-development rate and adult aging in humans.
Commentary on Alister et al. (2025): Individual Differences or Unsystematic Noise?
Peter Shepherdson
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Alister et al. (2025) reported individual differences in the extent to which people find source-dependent and source-independent claims persuasive, but an exploratory analysis showed no discernible relationship between these individual differences and demographic variables such as age, education, politics, and social-media use. Here I show through simulations that the individual-difference patterns Alister et al. identified are largely consistent with random across-trial variation in the absence of underlying differences between individuals. This casts doubt on the strength of their evidence for individual differences and provides one plausible account of why their exploratory analyses did not yield systematic relationships.

Psychology of Popular Media

“The constant jokes make me feel crap about myself”: A reflexive thematic analysis of boys’ experiences of appearance-related banter on Instagram.
Danielle L. Hope, Beth T. Bell
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Technology, Mind, and Behavior

When artificial intelligence apologizes: Dynamic trust updating and the role of personality.
Jit Wei A. Ang, Chenye Zhong, Syaheed B. Jabar, Georgios Christopoulos
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Conversational artificial intelligence can foster a sense of meaningful work through eliciting authentic pride.
Joshua J. Prasad, Isabella A. Boyd, Bryan J. Dik
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Exploring the limits of large language models as a reflection of human cognition: An illustration in the context of moral judgment.
Sarah Schröder, Thekla Morgenroth, Ulrike Kuhl, Valerie Vaquet, Benjamin Paaßen
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