I checked 15 psychology journals on Tuesday, August 11, 2026 using the Crossref API. For the period August 04 to August 10, I found 37 new paper(s) in 11 journal(s).

Advances in Methods and Practices in Psychological Science

Event-History Analysis for Psychological Time-to-Event Data: A Tutorial in R With Examples in Bayesian and Frequentist Workflows
Sven Panis, Richard Ramsey
Full text
Time-to-event data, such as response times and saccade latencies, form a cornerstone of experimental psychology and have had a widespread impact on the understanding of human cognition. However, the orthodox method for analyzing such data—comparing means between conditions—is known to conceal valuable information about the timeline of psychological effects, such as their onset time and how they evolve over time. The ability to reveal finer-grained “temporal states” of cognitive processes can have important consequences for theory development by qualitatively changing the key inferences that are drawn from psychological data. Well-established analytical approaches, such as event-history analysis (EHA), can evaluate the detailed shape of time-to-event distributions and thus characterize the time course of psychological states. One barrier to wider use of EHA, however, is that the analytical workflow is typically more time-consuming and complex than orthodox approaches. To help achieve broader uptake of EHA, in this article, we outline a set of tutorials that detail one distributional method, known as discrete-time EHA. We touch on several key aspects of the workflow, such as how to process raw data and specify regression models, and we also consider the implications for experimental design. We finish the article by considering the benefits of the approach for understanding psychological states and its limitations. Finally, the project is written in R and freely available, which means the approach can easily be adapted to other data sets.
Bayesian Sample-Size Determination for Longitudinal Trials With Attrition: The BayesSSD Package
Ulrich Lösener, Mirjam Moerbeek
Full text
Sample-size determination (SSD) is the procedure of determining the number of subjects necessary to achieve a desired level of statistical power and is essential in planning an experiment. Although open-access software for SSD via closed-form equations is readily available in the null-hypothesis-significance-testing framework, this approach has been subject to severe criticism in the past. As an alternative, Bayesian evaluation of informative hypotheses via the Bayes’s factor or posterior model probabilities has been proposed. However, available software packages for Bayesian SSD are either (a) limited to simpler models, such as analysis of variance and t test, and cannot handle longitudinal data or (b) unable to handle more than two treatment conditions. Current software also neglects participant attrition—a common occurrence that may substantially reduce the power of a longitudinal experiment. In the present work, we address this gap by introducing the open-access R package BayesSSD , which performs simulation-based Bayesian SSD for longitudinal trials with two or more treatment conditions. Through a simulation study, we show that not only the proportion of individuals dropping out but also the timing of dropout need to be considered when performing SSD. In the presented method, various patterns of expected attrition can be specified via parametric and nonparametric survival functions and accounted for in the SSD procedure. To facilitate adoption, we provide a tutorial with empirical data, illustrating each step of the Bayesian SSD process.
Musicians, Memory, and General Cognitive Ability: A Commentary on Grassi et al. (2025)
Enrico Toffalini, Tommaso Feraco
Full text
When cognitive variables show a positive manifold, mainstream psychometric theory suggests that their common variance should be modeled first. Treating correlated cognitive scores as if they were separately interpretable outcomes instead requires explicit theoretical justification. We comment on Grassi et al., an important multilab study on musicians and nonmusicians, and reexamine their cognitive results at the latent level. Using multigroup and multilevel structural equation models on the same data set, we ask whether the reported pattern can be parsimoniously understood as a difference in shared cognitive variance rather than as a set of task-specific advantages. The results suggest that under this latent-variable representation, the musician advantage is mostly captured by a latent common factor, whereas melody span retained a clear residual advantage and vocabulary showed, at most, a smaller task-specific deviation. The focus, therefore, is not just whether musicians differ from nonmusicians on a set of observed tasks, possibly controlled for each other, but also how such differences should be interpreted once those tasks are allowed to share variance. Grassi et al. provided an excellent example of open, collaborative work that the field should actively encourage. We suggest that this kind of enterprise should also be paired with equally strong and theoretically grounded measurement modeling.

Behavior Research Methods

Hierarchical Bayesian modeling of interoceptive psychophysics
Arthur S. Courtin, Jesper Fischer Ehmsen, Leah Banellis, Francesca Fardo, Micah G. Allen
Full text
Interoception, the capacity to sense, perceive, and metacognitively appraise viscerosensory and homeostatic signals, is a growing focus in psychology and psychiatry. Adaptive psychophysical tasks now allow quantification of perceptual sensitivity, bias, and precision in cardiac and respiratory domains. However, accurately estimating these parameters often requires large numbers of trials or participants, posing practical challenges, especially in clinical research where participant availability and tolerance are limited. One approach to reduce participant burden while maintaining statistical rigor is to optimize data analysis. Here, we present hierarchical Bayesian models tailored for cardiac and respiratory interoceptive psychophysics that efficiently estimate sensitivity, bias, and precision at both individual and group levels. Using simulations and empirical data, we validate these models and demonstrate that they allow enhanced inference relative to conventional approaches. To support adoption, we provide openly accessible resources, including a tutorial on implementing and fitting these models in R (written with researchers without modeling expertise in mind) and an app for sample-size justification. These tools facilitate robust, efficient, and generalizable modeling of interoceptive performance, enabling rigorous studies even with limited trials or participant availability.
Disentangling within- and between-subject correlations in cognitive models: The essential role of hierarchical estimation
Michelle C. Donzallaz, Niek Stevenson, Andrew Heathcote, Dora Matzke
Full text
Cognitive models, such as evidence-accumulation models, are increasingly used in individual differences research in psychology and neuroscience. By computing correlations between cognitive model parameters across participants, researchers aim to understand how the psychological processes the parameters represent relate to one another and jointly determine performance. It is generally acknowledged that cognitive models can be challenging to estimate due to strong within-subject correlations among the parameters, which are embedded in the model’s likelihood function. What is less often recognized, however, is that within-subject correlations can also distort correlations computed between parameters estimated with non-hierarchical methods, so they no longer reflect true individual differences, potentially leading to misleading conclusions. Here we illustrate this pitfall of non-hierarchical estimation and show how appropriately parameterized, descriptively adequate hierarchical models can mitigate the problem by effectively separating within- and between-subject sources of variation. We then offer recommendations for identifying and guarding against the inferential biases resulting from the strong within-subject correlations inherent in many cognitive models.
GridSamp: An open-source Python toolbox for grid sampling
Maarten Leemans, Christophe Bossens, Johan Wagemans
Full text
PinPointer: An offline error measurement system for motor behavior research
Milton E. T. Marin, Michael B. F. Cabrera, Joshua R. Samson, Juliana O. Parma, Alyssa Kubota
Full text
Eye-tracking-while-reading: A living survey of datasets with open library support
Deborah N. Jakobi, David R. Reich, Paul Prasse, Jana M. Hofmann, Lena S. Bolliger, Lena A. Jäger
Full text
Eye-tracking-while-reading corpora are a valuable resource for many different disciplines and use cases. Use cases range from studying the cognitive processes underlying reading to machine-learning-based applications, such as gaze-based assessments of reading comprehension. The past decades have seen an increase in the number and size of eye-tracking-while-reading datasets as well as increasing diversity with regard to the stimulus languages covered, the linguistic background of the participants, or accompanying psychometric or demographic data. The spread of data across different disciplines and the lack of data sharing standards across the communities lead to many existing datasets that cannot be easily reused due to a lack of interoperability. In this work, we aim at creating more transparency and clarity with regards to existing datasets and their features across different disciplines by i) presenting an extensive overview of existing datasets, ii) simplifying the sharing of newly created datasets by publishing a living overview online, https://t.uzh.ch/1Yh , presenting over 55 features for each dataset, and iii) integrating all publicly available datasets into the Python package which offers an eye-tracking datasets library. By doing so, we aim to strengthen the FAIR principles in eye-tracking-while-reading research and promote good scientific practices, such as reproducing and replicating studies.
Simulating insufficient effort responding with large language models: A persona-based prompt engineering approach
Donghun Kim, Giryong Park, Jin Suk Park, Taehun Lee
Full text

Computers in Human Behavior

Approval Mechanisms Fueling Digital Hate: Online Incivility and Intolerance Perpetration in Four Countries
Melanie Hirsch, Stephanie Bührer, Kevin Koban, Jörg Matthes
Full text
How users interpret AI-assisted reviews: Disclosure design and authenticity perceptions
Hayeon Kim, Sang Woo Lee
Full text
Motivation, cognition, and emotion: Unpacking the pathways from fitness app gratifications to workout intention
Lanxin Jiang, Chen Luo, Tongxuan Tian, Xinchan Xiang
Full text
The brick-to-jade effect of AI hallucination: Evidence from chatbots in online communities
Hongchao Zhang, Kunlu Zhou, Jifei Wu, Xirong Gao, Yinggao Qin
Full text
Engaged but careless? The roles of online civic engagement, well-being, and information literacy in careless information sharing
Michal Mužík, Marie Jaron Bedrosova, Giovanna Mascheroni, Hana Machackova
Full text
Walking in Her Shoes: Virtual Embodiment of a Famous Female Scientist Reduces Implicit Gender–Science Associations
Marta Beneda, Julia Spielmann, Amna Ramadhan Alahmadi, Domna Banakou, Andrea C. Vial
Full text

Group Processes & Intergroup Relations

Dehumanization and Socioeconomic Status: Replicating and Extending the Animalization of Low-SES Targets and the Mechanization of High-SES Targets
Coralie Botalla-Raynal, Frédérique Autin
Full text
In three preregistered, high-powered studies, we replicated and extended findings on dehumanization based on socioeconomic status (SES), where low-SES groups are denied Human Uniqueness (animalization), and high-SES groups are denied Human Nature (mechanization). Study 1 ( N = 296, representative sample, 3.25 times the original sample) replicated Sainz et al.’s first study, confirming the animalization of low-SES groups but not consistently supporting the mechanization of high-SES groups. Study 2 ( N = 536, representative sample) used adapted materials and successfully replicated both phenomena. Study 3 ( N = 103 students) extended the findings by shifting from judgments of social groups to judgments of individual targets. We subtly induced SES via facial characteristics and assessed dehumanization through perceived animal- or robot-likeness. Results were consistent with both forms of dehumanization. This research provides evidence of the robustness and generalizability of SES-based dehumanization, contributing to the understanding of social inequalities and the perceptions that justify them.
Disentangling Religiosity: Specific Religious Perspectives Reduce Intergroup Bias
Patty Van Cappellen, Amanda M. Bernal, Caimiao Liu
Full text
A large body of research has documented links between religiosity and prejudice toward groups perceived as threatening to traditional religious values. In the present research, we aimed to identify and experimentally manipulate facets of religiosity that reduce such intergroup bias. Across Studies 1 ( N = 293) and 2 ( N = 795), we used a theory- and data-driven approach and identified representations of God and liberal–conservative religious ideology that are associated with lower discrimination between groups that align with, are neutral to, or threaten religious values. In Studies 3 ( N = 693) and 4 ( N = 564), we developed novel perspective-taking prompts and found that encouraging American Christians to reflect on either a benevolent God or a liberal religious perspective significantly reduced bias in donation recommendations between value-neutral and value-threatening groups, relative to a control condition. These findings extend prior correlational work by identifying specific religious perspectives that can be experimentally manipulated to reduce discrimination and promote more equitable intergroup behavior toward groups that are perceived to threaten traditional religious values.
Multiracial Identity Contestation and Race Concept Reflection
Zoey Eddy, Diana T. Sanchez
Full text
This paper explores how Multiracial identity contestation may foster greater social conceptions of race through race concept reflection (i.e., thinking frequently about racial categories). Across two correlational studies, Multiracial participants (total N = 1,159) completed a cross-sectional survey measuring identity contestation, race concept reflection, social race conceptions, and flexible group categorization. Identity contestation was related to greater race concept reflection, which was associated with greater social race conceptions. Further, social race conceptions were related to higher flexible group categorization. In Study 3, participants ( n = 252) who recalled identity contestation engaged in greater race concept reflection than those in the control condition, which was associated with endorsing greater social race conceptions. In Study 4, participants ( n = 235) who reflected on race concepts after recalling identity contestation reported greater social race conceptions than those in the control condition. Identity contestation and race concept reflection may, in part, account for Multiracial people’s social race conceptions. These relationships held while controlling for related concepts such as racism reflection (Studies 1–3), general discrimination experiences (Studies 1–2), and negative affect (Studies 3–4).
The Future of Latines’ Racial Categorization and Sociopolitical Attitudes Amid Rising US Diversity
Melissa Vega, Eric Knowles, Jaime Napier
Full text
Latines have become one of the largest ethnic groups in the United States. Given the historical fluidity of whiteness in the US and the Latine group’s uniquely ambiguous racial status, it is unclear how this group will be hierarchically and politically positioned in the future. Across three studies (total N = 1,754 Latines), we investigated how exposure to information about the possible inclusion of Latine Americans in the White racial category changes Latines’ beliefs about their group’s future racial status and their subsequent sociopolitical attitudes. Participants who read about the Latine group’s likely inclusion in (vs. continued exclusion from) the White category more strongly believed Latines would soon be considered White (Studies 1–3) and reported increased symbolic racism and political conservatism (Studies 2 and 3). Our results demonstrate the malleability of Latines’ racial categorization beliefs and suggest that White racialization might lead Latines to adopt sociopolitical views typically associated with dominant groups.

Journal of Experimental Social Psychology

Sustaining your stance by speaking your mind: Expressing moral judgments increases certainty and prevents moral desensitization
Simone Mattavelli, Daniel A. Effron
Full text

Journal of Personality and Social Psychology

The cost of an expanding moral circle: After living abroad, outcasts matter more but loved ones matter less.
Daniela Rodriguez-Mincey, Salvatore J. Affinito, Giselle E. Antoine, Kurt Gray, William W. Maddux
Full text
Self-efficacy predicts differential neuroticism change in a smartphone-based intervention.
Michael D. Krämer, Amanda J. Wright, Peter Haehner, Johannes Zimmermann, Christoph Flückiger, Christopher J. Hopwood, Wiebke Bleidorn
Full text

Multivariate Behavioral Research

Romeb: An R Package for Robust Median-Based Bayesian Linear Growth Curve Modeling with Missing Data
Dandan Tang, Xin Tong
Full text
Comparing inference methods for causal mediation analysis with nominal mediators: A simulation and empirical study
Sooyong Lee, Cory L. Cobb, Soyoung Kim
Full text
Investigating Measurement Invariance Across Situations in Intensive Longitudinal Data
Lisa Peuckmann, Andreas B. Neubauer, Dorota Reis
Full text
A Comparison of Latent and Deterministic Blockmodeling with Application to Binary Substance Use Disorder Data
Michael Brusco, Douglas Steinley, Ashley L. Watts
Full text
To g or Not to g ? A Cross-Domain, Subtest-Level Investigation of the Flynn Effect Across Ages 7-15 Years
Evan J. Giangrande, Sean R. Womack, Deborah Finkel, Deborah W. Davis, Christopher R. Beam, Eric Turkheimer
Full text
A Mechanistic Model of Symptom Dynamics: Implications for Statistical Network Analyses
Kyuri Park, Lourens Waldorp, VĂ­tor V. Vasconcelos
Full text
Flexible Multiple Imputation of Missing Data in Time-Structured Longitudinal Designs
Mark Lustig, Oliver LĂĽdtke, Alexander Robitzsch, Simon Grund
Full text

Personality and Social Psychology Bulletin

Riding Solo: The Associations Between Singlehood Self-Expansion Potential, Self-Expansion Experiences, and Singlehood Outcomes
Elina Moreno, Yuthika U. Girme, Anastasiia Burik, Sarah C. E. Stanton
Full text
Being single (i.e., not in a romantic relationship) offers people an important opportunity to self-expand and experience the associated well-being benefits. Drawing on self-expansion theory, we investigated the role of singlehood self-expansion potential (SSEP) across three pre-registered studies. In two diary studies (Studies 1 and 2), greater SSEP was associated with concurrent and (to a lesser extent in Study 2) lagged associations with greater self-expanding experiences, singlehood satisfaction, psychological need fulfillment, and life satisfaction, and lower fear of being single. We also examined the self-expanding activities that single people engage in and found that singlehood self-expansion predominately occurs with non-romantic close others (Study 2). Finally, in an experimental study (Study 3), individuals who imagined how singlehood could facilitate future novel (vs. routine) activities did not report greater SSEP but reported greater self-expansion experiences and positive mood. This research highlights the importance of viewing singlehood as having potential for self-expansion.
Beyond Content: Psychological Structure of Ideological Beliefs
Gabriela Czarnek, Katarzyna Jasko, Iwona Dudek, Mark J. Brandt, Maja Piotrowska
Full text
Research on ideological beliefs structure primarily focused on mapping the underlying dimensions of belief content . Beyond what beliefs people hold, it is also crucial to understand how they hold these beliefs. Drawing from diverse literature, we identified nearly 20 constructs and hypothesized three overarching factors of the psychological structure of ideology: importance, certainty, and metacognitive difficulty. Using 49 political issues across the United States, Poland, and India ( N total = 2,838), we found evidence for two primary dimensions: importance and metacognitive difficulty. Certainty did not emerge as a separate factor: in the United States, certainty items split between these two dimensions, whereas in Poland and India, importance and certainty converged. We also investigated the predictive power of these dimensions. Higher importance and certainty and lower metacognitive difficulty were linked to more extreme beliefs, and importance was a key predictor of advocacy intentions. These findings offer a comprehensive framework for understanding how ideological beliefs are held.

Psychological Methods

Dynamic latent class structural equation modeling: A hands-on tutorial for modeling intensive longitudinal data.
Roberto Faleh, Sofia Morelli, Vivato Andriamiarana, Zachary J. Roman, Christoph FlĂĽckiger, Holger Brandt
Full text

Psychology of Music

What Music Do People Use for Mood Regulation?
Catherine Tan, Peter M. C. Harrison
Full text
This study seeks to understand what music is used for music mood regulation (MMR). We question how audio features can characterise the music used for different MMR strategies and explore how participant background variables (musical sophistication, sensitivity to musical reward, empathy, and well-being) might predict the use of these strategies, and hence the kinds of music adopted for MMR. Participants ( N = 229) completed an online survey that produced a dataset composed of 5,334 tracks for MMR, their Spotify audio feature measures, and scores for the participant background variables. Principal component analyses revealed that energetic and positive music was preferred for strategies that regulated positive moods or modulated arousal, whereas instrumental music was preferred for the Strong Sensation strategy and those requiring cognitive responses. Regarding individual differences, we identify various correlations between participant background variables and amount of MMR strategy usage; exploratory analyses additionally suggest that musical sophistication, empathy, and well-being also predict the kind of music that is used for particular strategies. We discuss the potential implications of our research for advancing theories on musical emotions and the development of well-being tools.
Using Generative Artificial Intelligence to Identify Themes of Basic Psychological Needs in Popular Song Lyrics
Hermione H. Liu, Suzy E. Miller, Mark A. Lee, Nicholas Matherne, Damien J. Miller, Emma D’Aprano
Full text
Music listening is a universal human behaviour, increasingly recognised for its association with well-being. The mechanisms underlying how music listening influences well-being remain unclear, especially in terms of broader motivational processes. Utilising a self-determination theory (SDT) framework, we examined the extent to which popular song lyrics represented themes of basic psychological needs (BPN). Our corpus comprised the top 10 songs of the Australian Recording Industry Association’s top 100 singles chart for the period 1988–2023, resulting in 360 unique songs. Lyrics were analysed through deductive content analysis using a researcher-created application, MuseAI , which employs large language model platforms using custom media input. Our findings indicated the representation of all three BPNs across the pop song lyric corpus. Relatedness themes occurred at the highest frequency, followed by autonomy and competence, respectively. Need satisfaction occurred more frequently than need frustration. As these songs were those most listened to by audiences across more than three decades, our findings suggest that song lyrics frequently represent themes of BPN, which may help explain the motivational appeal of music listening. This exploratory research provides initial theoretical support for further investigation of music listening engagement utilising an SDT framework.
Performer Identity, Agency, and Programming Lesser-Known Piano Repertoire
Ning Hui See
Full text
The diversification of concert repertoire has garnered increased attention recently, yet research on modern concert programming remains limited, focusing mainly on quotas and the perspectives of organisers and audiences. Discourses on the contextualisation and evaluation of women composers’ music have not transcended questions raised since the 1990s, and historical patterns demonstrate that change is not linear. Given the role of performers as co-creators of musical meaning and value, we need a better understanding of their practices to achieve sustainable change. This study examines the interrelation between the performer’s sense of identity and agency and their selection and programming of music by composers who are lesser-known due to stylistic unfamiliarity or their gender, race, or other demographic characteristics. Using interpretative phenomenological analysis (IPA), I examined interview accounts of four professional pianists experienced in performing such repertoire. Six group experiential themes emerged: career and professional identity; aesthetic, emotions, or sociopolitical connections; interpretative strategies and commitment; contextualising lesser-known repertoire as accessible or valuable; programming agency in relation to organisers, venues, and audiences; and belonging and outsiderness. These findings bear implications for effective programming practices and conservatoire pedagogical transformations.
Experiencing motherhood as a professional musician: Issues of musical identity
Maria Papazachariou-Christoforou, Maria Tympa
Full text
Recognizing that musical identities mediate how individuals and groups engage with and through music, this case study explored a professional mother-musician’s experience of musical parenting with her infant and the perception of her musical identity in this context. Data collection spanned 4 months and included semistructured interviews with the mother, informal discussions via a mother–researcher networking platform, digital diaries, and videos provided by the mother. Previous studies have identified the significance of infant–mother musical interaction for the care and development of the infant as well as for enhancing attachment and bonding between them. However, very few studies have focused on how this interaction impacts the musical identity of the mother. The findings of this study suggest that the mother incorporated a variety of musical activities into her infant’s care, and she perceived musical parenting as a fruitful context for negotiating and strengthening her own musical identity. The study’s findings suggest the need for further research into the issue of musical identity among professional musician parents within the context of musical parenting.

Psychology of Popular Media

Magic mirror on my screen: An experimental test of assimilation effects of beauty filters on Chinese college women’s self-esteem and affect.
Yanzhuo Niu
Full text