I checked 15 psychology journals on Saturday, July 25, 2026 using the Crossref API. For the period July 18 to July 24, I found 35 new paper(s) in 11 journal(s).

Behavior Research Methods

StreetArt4Sustainability dataset: Mapping aesthetic emotions to street art
PatrĂ­cia Arriaga, Erin M. Buchanan
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A novel dataset of 556 street art images is presented, accompanied by affective evaluations from 1,239 Portuguese and Brazilian participants. Artworks were selected to reflect themes associated with the United Nations Sustainable Development Goals. Using a stimulus-sampling design, each participant completed an online survey in which 10 randomly selected artworks were presented and reported their responses in terms of valence, arousal, and specific emotion labels (being moved, awe, inspiration, hope, sadness, fear, anger, emotional connection, reflection, awareness, and interest), as well as their interest in street art and sustainability consciousness. Multilevel analyses showed that higher interest in street art and greater sustainability consciousness were consistent predictors of more positive emotional responses to the artworks. In contrast, the effects of gender and age were negligible, and national differences emerged only for feeling moved and awe. Network analyses revealed a highly interconnected emotional structure, with three clusters: self-transcendent, epistemic, and negative emotions. Feeling moved and emotional connection occupied central bridging positions, showing both direct and indirect links across positive and negative emotion clusters. Overall, these findings indicate that street art evokes a broad range of interconnected self-transcendent, cognitive-epistemic, and negative emotions, highlighting the complexity of viewers’ responses to the artworks. The dataset provides a valuable resource for research on emotional responses to street art and can support broader investigations into visual perception, aesthetic processing, and the communication of sustainability-related themes.
Measurement error is lower for visual analogue scales than for slider scales
Tim Angelike, Ulf-Dietrich Reips
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Errors in measurement can arise in study and survey responses when there is a discrepancy between the intended and selected response. A significant portion of the scientific discourse has centered on the comparison of discrete and continuous response scales. In this study, we examined various continuous rating scales to ascertain which scale would yield the lowest measurement error. To this end, we compared visual analogue scales (VAS) with different slider scales in an online study ( N = 222) that built upon the original work by Reips and Funke (2008). In this study, participants were asked to estimate where a percentage value would lie on a line ranging from 0 to 100%. The slider scale conditions differed in the initialization of the slider thumb (left, middle, right), with an additional slider condition that employed the default HTML slider with a large thumb without any modifications. The findings of this study suggest that the measurement error in estimating the true value was lower in VAS than in slider scales. Additionally, our findings suggest that VAS lead to reduced variability in errors within and between individuals. Contrary to our initial hypothesis, we did not find a higher measurement error in the default slider than in the other slider conditions. The findings of this study suggest that VAS may offer a more precise means to the assessment of ratings. Practitioners who intend to employ continuous rating scales should consider employing VAS or at least carefully consider the pitfalls of slider scales.
Unveiling local dependencies in accuracy and speed: A mixture hierarchical modeling approach
Hung-Yu Huang
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Hierarchical models (HMs) are commonly used to jointly model response accuracies and response times (RTs). However, their relationship cannot be fully captured by the population-level correlation between ability and speed, as local dependencies may arise and threaten valid inferences about individuals and items. In this study, a mixture-based hierarchical model (Mix-HM) that allows respondents to switch between different pacing speeds and identifies positive and negative item-level dependencies is proposed. Two simulation studies were conducted: Simulation 1 examined parameter recovery effects, and Simulation 2 evaluated the effectiveness of Bayesian information-based criteria in model selection processes. The results showed that the Mix-HM achieved satisfactory parameter recovery effects, whereas the conventional HM yielded biased estimates when local dependencies were present. In addition, the model fit criteria were generally able to correctly identify the true model across most conditions. An empirical analysis conducted using large-scale assessment data further showed that the new model provided an improved degree of fit and more stable parameter estimates, while the conventional HM distorted the relationship between ability and speed. These findings highlight the importance of accounting for the heterogeneity of latent speed and local dependencies when incorporating RTs as collateral information.
Customizable Bayesian adaptive testing with Python – The adaptivetesting package
Jonas Engicht, R. Maximilian Bee, Tobias Koch
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This paper introduces an open-source Python package for simplified, customizable computerized adaptive testing (CAT) using Bayesian methods for ability estimation. It addresses the lack of sophisticated packages for CAT in the Python programming language. Moreover, it bridges the gap between the construction and simulation of adaptive tests and their practical application by providing a dedicated API for integration with experiment software. Thereby, it eliminates the need for major code rewrites when transitioning from simulated to real-world adaptive testing. By leveraging Python’s object-oriented programming approach, such as abstract classes, protocols, and inheritance, the package allows for easy extension and customization of its functionality. For example, Bayesian estimators can be modified to incorporate custom priors. This paper outlines the relevance and practical use of the package through a walkthrough example. The package is fully documented, and its source code is published on GitHub. It is also available on the Python Package Index (PyPi) and conda-forge thus it can easily be installed using Python’s package manager or . Leveraging R’s package, can also be accessed from within RStudio.
AI-generated familiarity estimates are a useful new source of information about word knowledge in Simplified Chinese
Ziyi Ding, Kangning Qin, Marc Brysbaert, Qing Cai
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Developing a psychological test battery to measure cognition in daily life
Andrew J. Aschenbrenner, Muchen Xi, Jeremy Cohn, Derek A. Simon, Joshua J. Jackson
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Cognition is not a static process but is subject to substantial and meaningful variation within individuals over time. This has led to an increase in studies that aim to describe cognition in daily life by sampling participants repeatedly and remotely. Such studies, which we call high-frequency cognitive assessment or “HFCA”, tend to use a limited number of brief cognitive tests. This focus on a small number of tests leaves open questions concerning the psychometric characteristics of a wide array of cognitive tasks useful for HFCA that can guide researchers on appropriate task selection. We developed the Cognitive Variability Battery (CVB), a series of nine cognitive tests clustered into three distinct cognitive domains: attentional control, processing speed, and episodic memory. CVB was administered to participants three times per day for 3 weeks. Cognitive tests were rotated to reduce the length of any single testing session. Each test was administered up to 60 times. We provide detailed descriptions of the performance of each task, including variability, skew, and reliability statistics, using intraclass correlations. We examine the sensitivity of each test to several contextual factors including stress, affect, and social interactions. Finally, we provide power analyses on each cognitive test to determine how many assessments and participants are needed to detect effects of interest. These analyses will be essential to anyone seeking to implement HFCA testing in their own research programs, by providing guidance on which cognitive tests to select and how many participants and observations may be needed.
Modeling intraindividual variability in affect (MIVA): Formalized theoretical approach, computational model, and parameter recovery study
Maria Wirth, Andreas Voss, Stefan T. Radev, Klaus Rothermund
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No matter how angry, sad, or happy we are, eventually, we will feel different. Studying this ebb and flow of affective experience in daily life provides important insights into psychological functioning and well-being. We have developed a parsimonious formalized model of intraindividual variability in affect (MIVA), resting on the assumption that such affective changes reflect transactions between an individual and their proximal environment. We provide an outline of its theoretical background, scope, and mathematical formulation. We situate MIVA within the research field of affect dynamics and illustrate the models’ behavior under realistic conditions using a simulation study. We use simulation-based inference to train a custom neural network on MIVA simulations, which we employ to rapidly estimate the model’s parameters on a multitude of synthetic experiments with different configurations. Our simulation study demonstrates that the synthesis between a computational model and probabilistic neural networks results in an efficient and flexible tool for model-based inference of affect dynamics. Our simulation study also offers insights into the data requirements for a precise recovery of the model’s parameters and recommendations for future data collection. The potential of MIVA for providing insights into affect dynamics is discussed.
Measuring complex constructs in large-scale text with computational social mixed methods
Alina Herderich, Jana Lasser, Mirta Galesic, Segun Aroyehun, David Garcia, Joshua Garland
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A growing convergence between social science and machine learning enables, in principle, large-scale analyses of complex social phenomena through text. Yet, approaches leveraging supervised text classification based on human-annotated data for statistical analysis often treat conceptual validity and technical performance as separate challenges, impairing measurement quality. We provide guidelines to bridge this gap in what we call computational social mixed methods pipelines across three stages: data annotation, model training, and statistical analysis. Building on best practices and our own methodological innovations, such as “Iterative Annotation” and “Training on Confident Examples”, we address recurring pitfalls like unbalanced training data or stagnant model performance. We also discuss when large language models constitute a viable alternative to transformer-based classifiers. Using a case study on countering online hate, we illustrate how consequently integrating social science and machine learning expertise improves the validity and comparability of computational social science.
Segmented profile analysis (SEPA): Plane-wise decomposition of within-person variation via ipsatized singular value decomposition
Se-Kang Kim, Joe Grochowalski
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Traditional profile analyses summarize multivariate person data with overall mean levels and relative patterns, but existing methods often blur these sources of variation or reduce each individual to a single best-fitting profile. Segmented Profile Analysis (SEPA) offers a unified, ipsatized singular-value decomposition (SVD) framework that decomposes individual profiles into orthogonal level (LE) and pattern (PE) effects and, crucially, introduces plane-wise segment profiles (summaries of each person's response pattern within each variable-contrast dimension) as primary person-oriented objects. Within each low-dimensional plane, SEPA defines a projected response pattern (segment profile), domain–person cosines that index variable-by-variable alignment, and plane-fit correlations that summarize how closely an individual’s pattern follows the plane’s domain structure. Across planes, SEPA aggregates information via singular-value weighting to yield an overall segment profile while preserving contrast-specific signal. A practical workflow combines ipsatized SVD, parallel analysis for PE dimensionality, marker-domain rules, bootstrap confidence intervals, and subspace-stability diagnostics. Using multivariate cognitive data from the Woodcock–Johnson IV, SEPA identifies interpretable marker domains, reveals distinct pattern facets across planes, and provides person-oriented indices that can be carried into standard regression models. Simulation studies examine the stability of segment profiles and cosines under varying sample sizes and variance structures. SEPA thus supplies a reproducible, geometry-based foundation for person-centered measurement that connects Q-type factor analysis, biplot methods, and contemporary within-person profiling in multidomain assessments.
The Social Learning-Generosity (SL-Gen) Task: Redesigning the multi-round trust game paradigm to examine social learning and generosity sensitivity in young people
Brennan Delattre, Alister R. Dale-Evans, Amy L. Gillespie, Juliet D. Griffin, Erdem Pulcu, Susannah E. Murphy, Catherine J. Harmer
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Social learning is important for societal functioning, and adolescence is a critical period for the development and maintenance of social behaviors. Specifically, the ability to establish and maintain beneficial social interactions while avoiding or withdrawing from detrimental or harmful ones is crucial for healthy interpersonal functioning. Beyond self-report measures, the multi-round trust game, a commonly used behavioral economics paradigm, can help elucidate differences in social decision-making between healthy and clinical populations. To more specifically probe the role of social learning and generosity sensitivity during social exchange in young people, we have designed a new task: the Social Learning-Generosity (SL-Gen) Task. Using versions of the multi-round trust game as a basis for the design, we have incorporated more environmentally realistic task components, including controlled gain, loss, and variable gain-loss generosity conditions. In a single-session online study, the present research investigated task behavior and task acceptability in individuals aged 18–24 from a United Kingdom census-based sample, as well as exploring task differences by self-reported trust and gender. While this task is sensitive to differences in self-reported trust and gender and behaves similarly to existing versions of the trust game with respect to these effects, it has added utility within mental health research and treatment contexts for characterizing social decision-making behavior in more detail using set generosity conditions.

Computers in Human Behavior

Employee Knowledge and Smart Technology Adoption: Evidence from the E-waste Sector
Amila Kasun Sampath Udage Kankanamge, Michael Odei Erdiaw-Kwasie, Matthew Abunyewah, Kerstin Zander
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Delegating (or Not) to Machines: How Role Expectations Shape Leaders’ Willingness to Use AI for Communication
Roshni Raveendhran, Arthur S. Jago, Jonathan Gratch, Nathanael J. Fast
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Pretty Privilege? Effects of Perpetrators’ Attractiveness and Hate Type on User Responses Against Misogynist Digital Hate
Rinat Meerson, Kevin Koban, Jörg Matthes
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Journal of Experimental Social Psychology

We're near, they're far: On the association between one's gender in-group and psychological distance
Alys Ferragamo, Cheryl Jan Wakslak
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Feeling with family, grateful to strangers: Moral reactions to compassion and gratitude align with their social functions
Alexa Weiss, Pascal Burgmer
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Prosocial by default: Defaults boost giving even under distraction and widespread non-responsiveness
Linh Vu, Margarita Leib, Jan Hausfeld, Shaul Shalvi
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The subjectivity of objectivity: The effects of positionality statements on objectivity perceptions of psychological research
Sakaria Laisene Auelua-Toomey, Ellen C. Reinhart, Kengthsagn Louis
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Revisiting Gino, Ayal, et al.’s (2009) contagion and differentiation in unethical behavior: A registered conceptual replication and extension
Jareef Martuza, Esra Aslan
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Journal of Personality and Social Psychology

How institutional distrust breeds one-sided leadership: A consistency-based account.
Claire Linares, Anne-Sophie Chaxel
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When having less elevates more: Benefactor income, moral elevation, and prosocial contagion among observers.
Bingqing Miranda Yin, Jenny G. Olson, Yexin Jessica Li
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Organizational Research Methods

Interaction Effects May Indeed Be Artifacts of Common Method Variance
Arturs Kalnins
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A common belief in the organizational sciences is that estimated interaction effects in ordinary least squares regression cannot be artifacts of common method variance (CMV). This belief rests on the claim that CMV universally attenuates estimated interaction effects. As a result, researchers frequently dismiss CMV concerns when testing moderated relationships. We present an analytic closed-form regression model demonstrating that this universal attenuation claim is false in commonplace scenarios. In particular, when a quadratic term legitimately affects the dependent variable (DV) in the presence of CMV, an estimated interaction effect may be purely artifactual. The common belief holds only in two special cases: (1) when quadratic terms have zero effect on the DV, or (2) when one primary term that enters the interaction is unambiguously unaffected by CMV. We conclude that researchers should apply all standard CMV precautions when testing moderated hypotheses; the fact that one is assessing interactions should not be viewed as a “get out of CMV jail free” card. In addition, we recommend estimating and reporting model specifications both with and without quadratic terms to assess robustness.

Personality and Social Psychology Bulletin

Me, My Self (Concept), and I – Disentangling the Link Between Narcissism and the Impostor Self-Concept
Kristina Klug, Mona Leonhardt, Sophie Oprée, Sinem Rhein, Sonja Rohrmann
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The impostor self-concept involves self-doubt and fear of being exposed as a fraud. While vulnerable narcissism shares substantial psychological similarities with the impostor self-concept, grandiose narcissism is associated with an overestimation of one's own capabilities. The present study explores the relationship between the personality constructs impostor self-concept and narcissism, considering parenting styles and adult attachment. In a sample of 339 participants, path analyses revealed that overprotective and controlling parenting fostered both impostor self-concept and vulnerable narcissism, while grandiose narcissism was linked to parental warmth. Impostor self-concept and vulnerable narcissism predicted higher attachment anxiety and lower trust, whereas grandiose narcissism had no significant effects on adult attachment. Despite substantial overlap in developmental predictors and relational consequences, factor analyses confirmed the impostor self-concept as distinct from vulnerable narcissism. Findings point to shared developmental pathways and distinct relational implications, and highlight the need for longitudinal research and interventions targeting self-esteem and attachment security.
Does Self-Projection Have a Dominant Temporal Direction? In Nine Countries, People Feel More Similar to Their Future Than Past Selves
Jareef Martuza, Simen Bø, Helge Thorbjørnsen, Hallgeir Sjåstad
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Do you project your current self—the person you are today—equally across time? Compared to the present, 12 studies (total N = 11,416) reveal that people feel more similar to their future selves than their equidistant past selves. This future-oriented asymmetry in self-projection is directionally consistent across nine countries, with variation in effect size, and holds across different time horizons. Time-asymmetric self-projection covaries with higher levels of emotional connection between present and future selves and lower levels of perceived future self-change. We also provide preliminary causal-chain evidence for perceived self-change as a process by experimentally manipulating self-change beliefs. The future-oriented asymmetry appears to be self-focused, as it does not extend to others. Finally, future-oriented self-projection can lead to miscalibrated expectations: People expect their future selves to be more satisfied with hypothetical decisions made in the present than they currently would be with the same decisions in the past.

Psychological Methods

A comparison of the predictive performance of continuous and class-based latent trait models.
Wanjing Anya Ma, Yiqing Liu, Klint Kanopka, Wenchao Ma, Benjamin W. Domingue
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An application of procedural knowledge space theory to the study of strategic planning in board games.
Andrea Brancaccio, Luca Stefanutti
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Adjustment set selection for estimating optimal treatment rules under confounding.
Nina Galanter, Susan M. Shortreed, Erica E. M. Moodie
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Psychological Science

Reduced Mental Health and Well-Being in Parents of Transgender Youth Following the 2025 U.S. Presidential Inauguration
Rachel A. Leshin, Aditi Kodipady, Grey F. Raber, Natalie M. Gallagher, Kristina R. Olson
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The numerous executive orders directed at transgender youth in the weeks following the 2025 U.S. presidential inauguration were likely a signal to these youth—and their parents—that the federal government no longer supported them. Using a longitudinal design spanning 3 years prior to the inauguration (2022–2024) and 2 months surrounding the inauguration, we tested whether the mental health and well-being of U.S.-based transgender youth and their parents declined relative to that of cisgender youth and their parents in a sample that, on the whole, did not support the new administration ( N = 160 youth, aged 12–17 years; N = 167 parents). Across preregistered analyses, we observed significant declines in the mental health and well-being of parents of transgender youth compared to parents of cisgender youth; we observed fewer differences over time between transgender versus cisgender youth themselves. Our findings identify an immediate potential cost of the current political environment for supportive parents of transgender youth.

Psychology of Music

The Role of Past Experience With Listening to Classical Music in Liking Sophisticated Music
Valnea Žauhar, Igor Bajšanski, Sabina Vidulin
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The aim of the study was to examine the validity of the Past Experience with Listening to Classical Music Scale (PastELCMS) developed for adolescents and children, and to explore its role in preference for sophisticated music. In Study 1, participants were 151 students from a general education school who rated their liking for six excerpts of sophisticated music and completed questionnaires about previous experience with listening to classical music and other music-related tendencies and behaviours. Study 2 involved 286 pupils attending a primary music school. They reported their liking for an excerpt of classical music and completed questionnaires on the emotions evoked by the music while listening to the excerpt and on previous experience with listening to classical music. PastELCMS correlated positively with preference for sophisticated music, cognitive and emotional music listening, and music consumption in Study 1, as well as with liking for a classical music excerpt and music-evoked activation while listening to the excerpt in Study 2. Past experience with listening to classical music also positively predicted liking sophisticated music. Previous experience should be investigated to understand preferences for sophisticated music. PastELCMS is a valid and reliable measure that can be used with adolescents and children.
Flow State in Live Music Performance: A Qualitative Study on Musicians’ Stage Experiences
UÄźur Ă–zalp, Sergen Kaya
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This exploratory qualitative study examines how 32 professional musicians in Turkey described flow during live performance, and the conditions they perceived as facilitating or constraining it. Using a qualitative descriptive design with a phenomenological orientation and maximum-variation sampling, we conducted semi-structured interviews immediately after live sets to obtain performance-proximal accounts rather than implementing real-time experience sampling method (ESM) prompts. Reflexive thematic analysis of the interviews generated five themes: (1) definitions of flow (intense focus, altered time perception, unity with the music, present-centredness, well-being), (2) moments when flow tended to arise (improvisation, emotional or high-energy passages, stage entry), (3) external conditions (audience interaction, group energy, sound/technical reliability, unexpected events), (4) internal conditions (genre affinity, challenge–skill fit, music-theoretical orientation), and (5) perceived effects on performance (technical fluency, automaticity, effortlessness, expressiveness, creativity). Participants’ accounts highlight how flow in Turkish live-music venues is shaped by situated interactions with audiences, ensembles, and stage infrastructures, including genre-specific technical demands (e.g., bağlama performance). Overall, the study provides context-bound, experience-near insight into on-stage flow in contemporary Turkish popular music settings.

Psychology of Popular Media

The puzzle of engagement: An interview study on the subjective experience of engagement with mainstream narrational complexity.
Gaia Yonah, Cynthia Cabañas, Steven Willemsen, Miklós Kiss, Frank Hakemulder, Mariken van der Velden, Elly Konijn, Katalin Bálint
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Older and wiser, but not immune: A brief report examining movie exposure and male body image across development.
Kate Stewart, James Alex Bonus
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LGBTQ+ engagement with harmful online health content: Effects on self-perception and body image, health behaviors, and mental health.
Alex Penfold, Melissa Oxlad, Anna Chur-Hansen
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“It made life worth living at times”: A qualitative study of sexually explicit fanfiction as a narrative well-being resource.
Daniel R. du Plooy, Domenica A. Clowes, Gabriella Karakas
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Technology, Mind, and Behavior

Pushed to the edge: When radical political messages persuade more on social media.
Brahim Zarouali
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The bystander effect in human–robot interaction: How the presence of bystanders inhibits helping intentions for a social robot.
Guiying Liu, Tatjana Korbanka, Jasmin Timm, Naomi Oetelshofen, Laura Maier, Markus Huff, Frank Papenmeier
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