I checked 15 psychology journals on Saturday, April 04, 2026 using the Crossref API. For the period March 28 to April 03, I found 71 new paper(s) in 11 journal(s).

Behavior Research Methods

An AI-powered research assistant in the lab: A practical guide for text analysis through iterative collaboration with LLMs
Gino Carmona-DĂ­az, William JimĂ©nez-Leal, MarĂ­a Alejandra Grisales, Chandra Sripada, Santiago Amaya, Michael Inzlicht, Juan Pablo BermĂșdez
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Analyzing texts such as open-ended responses, headlines, or social media posts is a time- and labor-intensive process highly susceptible to bias. However, large language models (LLMs) are promising tools for text analysis, using either a predefined (top-down) or a data-driven (bottom-up) taxonomy, without sacrificing quality. Here, we present a step-by-step tutorial to efficiently develop, test, and apply taxonomies for analyzing unstructured data through an iterative and collaborative process between researchers and an LLM. Using personal goals provided by participants as an example, we demonstrate how we used this method to write prompts to review datasets and generate a taxonomy of life domains, evaluate and refine the taxonomy through prompt and direct modifications, and apply the taxonomy to categorize an entire dataset with high intercoder reliability, while achieving high levels of human–LLM intercoder agreement, reducing analysis time by approximately 87.5%. This test offers a proof of concept, suggesting that with the right procedures LLMs can be used to generate reliable bottom-up categorizations. We discuss the possibilities and limitations of using LLMs for text analysis.
Support for the coverage EMA: Participants can perceive and report discrete auditory event characteristics over 2 h in a simulated EMA scenario
Meynard John L. Toledo, Arthur A. Stone, Olivia L. Pomeroy, Sarah Goldstein
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Ecological momentary assessment (EMA) minimizes recall bias common in self-report, but variations like the “coverage model” reintroduce short-term recall, raising concerns about accuracy. This study evaluated the fidelity of ratings of characteristics of a discrete auditory event over a 2-h period, simulating coverage EMA, and examined the influence of objective event characteristics (intensity, duration, temporal location) on these ratings. In a remote experiment, participants ( N = 741) watched a 2-h film containing one embedded thunder sound stimulus. A 2 × 2 × 3 between-subjects design manipulated stimulus intensity (high/low), duration (short/long), and temporal location (start/middle/end). Immediately after, participants completed coverage EMA-style ratings of perceived intensity, duration, and location. Participants' ratings generally reflected the manipulated objective characteristics; the main effects of intensity, duration, and location on their corresponding ratings were significant. Evidence supporting cross-characteristic influences were weak/anecdotal, and effect sizes were small. Approximately 25% of participants failed to accurately report the single event's occurrence; accurate detection was predicted by higher intensity, longer duration, and temporal location ( p < .01). The results show that coverage EMA reports over a 2-h period can capture basic features of discrete events and demonstrate sensitivity to objective characteristics. They also exhibit certain reporting patterns that suggest potential influences between characteristics, although relatively weak effect sizes. Event detection sensitivity may also vary, particularly for less salient stimuli. These findings highlight the utility of coverage EMA while also emphasizing the need for researchers to consider how these patterns might operate within the context of their specific study goals.
Estimating correlations across tasks in experimental psychology
Shanglin Yang, Jeffrey N. Rouder
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Understanding how people covary in performance across experimental tasks is central to individual-difference psychology. The classic Pearson correlation has two strengths: (1) it is invariant to the scale of measurement, and (2) it is invariant to including additional variables in the analysis. However, it is susceptible to attenuation from measurement noise. Bayesian hierarchical models address this issue by modeling measurement error directly. Resulting estimates, however, depend on prior specifications and are not invariant to scale or variable inclusion. We compare three common priors—inverse Wishart (IW), scaled inverse Wishart (SIW), and LKJ—to assess robustness to prior assumptions in hierarchical settings. Our main tools are visualizing the priors and evaluating their effects on posterior estimates through simulation. When prior settings match ground truth, all priors recover true correlations accurately in low-dimensional settings. When prior variance is misspecified, the IW shows strong bias: low-variance priors inflate correlations, and high-variance priors deflate them. The SIW shows the same pattern but less severely, while the LKJ remains largely unaffected by scale misspecification. When more variables are added, the IW is most stable, whereas the SIW and LKJ show slight shrinkage toward lower correlations. The main drawback of the LKJ is computational speed—models with it can take orders of magnitude longer than those using IW or SIW. Overall, the LKJ provides the most accurate estimates, while the SIW offers a practical compromise for large-scale models where computational speed is crucial.
Can we include dichotomous variables in meta-analytic structural equation modeling? Mind the prevalence
Hannelies de Jonge, Belén Fernåndez-Castilla, Suzanne Jak, Kees-Jan Kan
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Meta-analytic structural equation modeling (MASEM) is a method to systematically synthesize results from primary studies, allowing the researchers to simultaneously examine multiple relations among variables by fitting a structural equation model to the pooled correlations. Incorporating dichotomous variables (e.g., having a specific disease or not) into MASEM poses challenges. While primary studies that investigate the relation between a dichotomous and continuous variable typically report standardized mean differences (e.g., Cohen’s  d ), in the specialized MASEM software it is not possible to directly include standardized mean differences. Instead, MASEM typically uses correlation matrices as input. A proposed solution is to convert the standardized mean differences to point-biserial correlations. Here lies a complication because, in contrast to a standardized mean difference, the point-biserial correlation depends on the distribution of group membership. Through three Monte Carlo simulation studies, we investigated which conversion formula is suitable when one wants to include a dichotomous variable in MASEM. We varied the prevalence, sampling plan, within-study sample sizes, and the distribution of participants over two groups. Our results show that which conversion is suitable, and which is not depends on the aim of the meta-analyst. Moreover, if the group distribution in the sample does not reflect the prevalence in the population, it is necessary to adjust the correlation between the continuous variables in the model. We have extended our freely available web application (Effect Size Calculator and Converter; https://hdejonge.shinyapps.io/ESCACO/ ) to fill the existing gap and to assist the meta-analyst with both the conversions and the adjustment. 
An illustrative guide to expressing cognitive theories using evidence accumulation modelling
Luke Strickland, Russell J. Boag, Niek Stevenson, Andrew Heathcote
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Evidence accumulation models (EAMs) explain and predict human choices and response times in a way that maps more directly to cognitive processes than traditional analyses. For example, EAMs can separate the speed–accuracy trade-off from processing capacity. However, little guidance is available regarding how to use EAMs to instantiate cognitive process theories, which often involve complex mappings of parameters to experimental designs. This tutorial illustrates how to embed such theories using the R package EMC2. We show how the effects of cognitive processes can be estimated by mapping EAM parameters to experimental designs using an augmented linear model language. We demonstrate with two examples. The first instantiates a theory of prospective memory. The second instantiates a theory of how humans integrate advice from automated decision aids into their choices. We then show how to combine these two different theories in a unified framework. We conclude by discussing further directions for theory embedding, including non-linear mappings from stimulus values to EAM parameters and the incorporation of trial-by-trial dynamics.
From zero to lab: Guidelines and practical implementation for building a multimodal experimental psychology and cognitive neuroscience laboratory
David del Rosario-Gilabert, A. García-Miquel, I. Vigué-Guix
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As multimodal approaches become increasingly common in cognitive neuroscience, there is a growing need for clear guidelines for designing and building laboratories. Here, we present a structured framework for the development of a multimodal neuroscience laboratory, covering key aspects such as space selection, acoustic treatment, electromagnetic shielding, environmental control, data synchronization, and data management. We also describe its practical implementation at the Instituto de Neurociencia Avanzada de Barcelona (INAB), where the facility was configured to support both individual and multi-participant studies using electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), eye-tracking, and peripheral biosensors. The laboratory was designed to preserve signal quality, minimize artifacts, and promote experimental reproducibility through controlled environmental conditions and rigorous synchronization procedures. Validation tests confirmed that the recording space achieved reverberation times below 0.6 s and reduced electromagnetic interference (EMI) by more than 30 × . Taken together, these technical and practical considerations provide a replicable model that other research groups can adopt to improve standardization and data reliability in multimodal neuroscience settings.
When the meaningless make sense: Wordlikeness and affective norms for 4,800 pseudowords and 1,200 Spanish words
Celia Martínez-Tomås, Marc Guasch, Pilar Ferré, Miguel Låzaro, José Antonio Hinojosa
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Most research using pseudowords has focused on the contribution of sublexical properties to the study of word processing. However, recent evidence suggests that pseudowords can also provide insights into the semantic and emotional aspects of language processing. Research in this field would greatly benefit from datasets providing estimations for pseudoword stimuli in the various lexicosemantic variables that have been shown to affect word recognition. Such datasets are currently lacking. In the present study, we introduce normative data for 4,800 pseudowords and 1,200 Spanish words, which were rated by 1,210 participants on three dimensions: wordlikeness, valence, and arousal. The stimuli were derived from emotional and neutral base words, and the morphological structure of the pseudowords was manipulated to create four versions combining real roots and suffixes with non-roots and non-suffixes. Additionally, we computed the normalized Levenshtein distance, the number of orthographic neighbors, and the mean Levenshtein distance to the 20 closest orthographic neighbors (OLD20) to examine the influence of objective measures on perceived wordlikeness. The results showed that the morphological structure of the pseudowords had a gradual effect on wordlikeness, valence, and arousal scores, with those combining real roots and suffixes being rated the highest. Furthermore, affective variables were found to consistently predict perceived wordlikeness ratings, whereas objective measures only accounted for a small proportion of the variance. This empirically validated set of well-controlled pseudowords is a valuable resource for researchers interested in the effects of morphology and affect on word processing. The complete database can be downloaded from: https://osf.io/baues/ .
Snip  & Stitch: a simple and accessible correction for the pupil foreshortening error
Koert H. Stribos, Damian Koevoet, Yuqing Cai, Marnix Naber, Christoph Strauch
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Modern eye trackers allow easy measurement of pupil size, a powerful physiological marker of cognitive processing. A major hindrance to using pupillometry is the so-called pupil foreshortening error (PFE). The PFE is the apparent change in pupil size that results from a change in the angle of the eye relative to the camera, despite the pupil remaining constant in reality. To prevent this, experimenters often rely on fixed gaze, limiting design flexibility. Existing correction methods necessitate specific geometric properties of the setup, often unavailable for existing datasets, and do not work for all tracker types. We here introduce ‘Snip  & Stitch’, a straightforward, accessible, and easy-to-implement correction for the PFE. Specifically, Snip  & Stitch corrects the PFE by ‘snipping’ pupil size changes during a saccade, and ‘stitching’ pupil size back by subtracting the difference between pre- and post-saccadic pupil size. Our results demonstrate that this simple method reduced the PFE by an estimated 71–81%. Snip  & Stitch is openly available online. We recommend Snip  & Stitch, especially for experiments in which participants make one saccade before pupil size is compared, and argue that the method can be easily applied to experiments in which participants make up to five saccades in sequence. Limitations and possible further improvements are discussed. Together, Snip  & Stitch allows researchers to employ pupil size as an outcome measure in a wide range of tasks and setups.
Slider versus Likert scales: Psychometric properties in ambulatory assessment
Dominik Vollbracht, Charlotte Ottenstein, Sabrina Ecker, Tanja Lischetzke
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Slider scales, a type of visual analogue scale, are commonly used as a response format in smartphone-based ambulatory assessment studies. This may be due to several advantages of slider scales, including the use of a metric scale compared to an ordinal Likert scale and the intuitive use of slider scales on touchscreens. However, research on the comparability of Likert and slider scales remains scarce, especially in the context of ambulatory assessment (i.e., intensive longitudinal data). To address this gap, we conducted a 3-week ambulatory assessment study with four measurement occasions per day, in which we experimentally manipulated the response format (Likert vs. slider scales) between groups. Our final sample consisted of 21,730 measurement occasions nested in 406 participants. We tested for measurement invariance across response-format groups and compared their psychometric properties, including reliability, within-person variability, and validity. Results indicated measurement invariance across groups, with equal factor loadings at the within-person level and equal factor loadings, intercepts, and indicator-specific residual variances at the between-person level. In addition, we found no significant differences in reliability or validity and only minor differences in within-person variability. We discuss the implications of these findings for the design of ambulatory assessment studies and offer recommendations for future research.
Author Correction: Attention in hindsight: Using stimulated recall to capture dynamic fluctuations in attentional engagement
Effie J. Pereira, Samantha Ayers-Glassey, Jeffrey D. Wammes, Daniel Smilek
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Computers in Human Behavior

Deepfaking the past: Memory and perceived truth of resurrected historical figures
MarĂ­a T. Soto-Sanfiel, Gina Junhan Fu
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Knowledge sharing in networked communities of practice: Computational network analysis of organizing dynamics in online crowdsourcing communities
Yiqi Li
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Mapping the symptom structure of internet gaming disorder among adolescents: Insights from network and Bayesian graph analyses
Firoj Al-Mamun, Moneerah Mohammad ALmerab, Mohammed A. Mamun
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For whom does online social support matter most? Exploring the joint moderating roles of depressive symptoms and physical functioning in the relationship between online social support and quality of life
Juwon Hwang
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Risk profiles for the perpetration of non-consensual sharing of sexual content among Spanish adolescents: a cross-sectional and longitudinal study
Estrella Durån-Guerrero, Virginia Sånchez-Jiménez, Noelia Muñoz-Fernåndez
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Does transparency matter when an AI system meets performance expectations? An experiment with an online dating site
Yuan Sun, Mengqi (Maggie) Liao, S. Shyam Sundar, Joseph B. Walther
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Exploring protective and risk factors for a positive sexting experience among young adults – insights from the SEX-THINK! Project
Barbara Agueli, Immacolata Di Napoli, Marcella Autiero, Nicole Bellanca, Alice Lucarini
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Altered uncertainty processing during adaptive learning in internet gaming disorder
Yi-Xu Pang, Lei Zhang, Yuan-Wei Yao, Marc N. Potenza, Lu Liu
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Game on or gone too far? Executive functioning and implicit sequence learning in problematic vs. recreational gamers
Krisztina Berta, Zsuzsanna ViktĂłria Pesthy, TeodĂłra VĂ©kony, Bence Csaba Farkas, Orsolya KirĂĄly, Zsolt Demetrovics, DezsƑ NĂ©meth, Bernadette Kun
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Think twice, scroll once: Encouraging critical reflection as a shield against health misinformation and overgeneralized messaging by social media influencers
Jaroslava Kaƈkovå, Jörg Matthes
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Personalizing explanations in AI-based decisions: The effects of personalization and (mis)aligning with individual preferences
Richard Uth, Nelli Niemitz, Isabel Valera, Markus Langer
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Negative perceptions of outsourcing to artificial intelligence
Scott Claessens, Pierce Veitch, Jim A.C. Everett
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To share or not to share, that is the (moral) question: How moral frames and bystander cues shape health misinformation correction sharing on social media
Yujie Dong, Wu Li
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Perceptions of sexualized deepfake abuse across three nations: An exploration of how victim gender and race shape attitudes towards deepfake abuse in the United States, the United Kingdom, and Australia
Asia A. Eaton, Adrian J. Scott, Asher Flynn, Anastasia Powell
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Association between school phone restriction policies and adolescents’ cyberbullying, gambling, and substance use behaviors
Szu-Chia Chen, Tzu-Fu Huang, Kevin Chang, Fong-Ching Chang, Shawn C. Chiang, Chiung-Hui Chiu, Ping-Hung Chen, Nae-Fang Miao, Hung-Yi Chuang
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Science communication in social Media: Analysis of success on TikTok, Instagram, and YouTube across scientific disciplines
Montserrat Aiger, Carmen Elboj, Raquel Lozano-Blasco, Marian Acero-Ferrero
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Gamified feedback in adaptive retrieval practice: Points and progress-bars enhance motivation but not learning
Gesa S. E. van den Broek, Stefanie Scholten, Bente van Thuil, Hedderik van Rijn, Tamara van Gog, Maarten van der Velde
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Know thyself through data: Improving WhatsApp interaction awareness with data-driven visualizations
Olya Hakobyan, Hanna Drimalla
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Bridging or broadening Gaps? AI-Assisted professional writing among native and non-native English Writers
Inyoung Shin, Hyesun Choung, Mina Choi
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From facial expressions to academic performance: Affective computing reveals the serial mediating roles of emotional valence and self-regulated learning
Ruchang Miao, Peijia Yang, Shuna Li, Kaizhen Kong, Xiangting Wang
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Adolescent social media use profiles: A longitudinal study of friendship quality and socio-motivational factors
Federica Angelini, Ina M. Koning, Gianluca Gini, Claudia Marino, Regina J.J.M. van den Eijnden
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Content camouflage: How diversified posting patterns influence human detection of AI-enabled social bots
C.J. Saucier, M. Wack, D. Linvill, A. Okoronkwo, G. Tatineni, A. Sezgin
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Dating app use, psychological health, and psychological well-being: A systematic review and quantitative meta-analysis
Liesel L. Sharabi, Lihong Ou, Paige A. Von Feldt, Thomas D. Parsons
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The Trusted Partner for financial decision making: Romantic partner or AI?
Erik Hermann, Max Alberhasky
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Choose to think: Nudging towards privacy informed decisions at the app download stage
Jennifer KlĂŒtsch, Verena Zimmermann, Sabine J. Schlittmeier
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Neural correlates of how different emotional reactions elicited by emojis influence facial expression processing
Mingkui Yang, Chunying Qiu, Weihan Wang, Xinchao Yang, Qiang Xu
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Group Processes & Intergroup Relations

A consistent but highly varied androcentric bias in the visual representation of “typical” faces
Daniel N. Albohn, Alexander Todorov
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Decades of research have shown that androcentric bias (i.e., assuming that men represent the default) is prevalent across text, images, and social interactions. Despite this evidence, recent research on the mental imagery of faces shows an opposite of the expected androcentric bias: Mental representations of “typical” faces appear more like women than men. In the present research, we first aim to reconcile this apparent discrepancy by examining the mental imagery associated with typical persons using generative reverse correlation—a data-driven method that leverages artificial intelligence to construct photo-realistic imagery of visual stereotypes for both groups and individuals. Second, we explore potential reasons for the observed reversal in mental imagery by examining individual differences in typicality judgments. Across two studies, our results show (1) individuals tend to equate “typical persons” with “men” in their mental representations at the group-level; but (2) there is large individual-level variability in both “typical person” mental imagery and explicit “typicality” judgments that complicates conclusions drawn from aggregate-level data.

Journal of Experimental Social Psychology

When rightness is wrong: Chronic prevention orientation predicts cardiovascular threat responses under regulatory fit
Deborah E. Ward, Mark D. Seery, Thomas L. Saltsman, Cheryl L. Kondrak
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Unequal participation: How low socioeconomic status hinders political engagement
Rodrigo Furst, Yan Vieites, Bernardo Andretti
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Does ignorance love company? The social dynamics of information avoidance
Katharina Reher, Martin Götz, Filippo Toscano, Jörg Gross
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Beyond confronting: Cultivating inclusion through proactive Allyship
Lucy De Souza, Toni Schmader
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When society feels broken: How perceptions of anomie shape donation tendencies across cultures
Fei Gao, Lan Xia
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Journal of Personality and Social Psychology

Finding agreement: Functional magnetic resonance imaging hyperscanning reveals that mental state space exploration facilitates opinion alignment.
Sebastian P. H. Speer, Haran Sened, Laetitia Mwilambwe-Tshilobo, Lily Tsoi, Shannon M. Burns, Emily B. Falk, Diana I. Tamir
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Overestimating the social costs of political belief change.
Trevor Spelman, Abdo Elnakouri, Nour Kteily, Eli J. Finkel
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The interpersonal consequences of community gatekeeping.
Evan Weingarten, Rachel Gershon, Amit Bhattacharjee
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Self-essentialism underlies social projection to unfamiliar similar others.
Charles Chu, Lydia Needy, Rebecca Schlegel
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Goal harmony.
Jiabi Wang, Ayelet Fishbach
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“Me in a nutshell”: Exploring the content and properties of central traits.
Elizabeth U. Long, Norhan Elsaadawy, Erika N. Carlson, Marc A. Fournier
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Personality and mortality risk: A systematic review and meta-analysis of longitudinal data.
MĂĄire McGeehan, Angelina R. Sutin, Stephen Gallagher, Antonio Terracciano, Nicholas A. Turiano, Elayne Ahern, Emma M. Kirwan, Martina Luchetti, Eileen K. Graham, PĂĄraic S. O'SĂșilleabhĂĄin
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Talking about what we support versus oppose affects others’ openness to our views.
Rhia Catapano, Zakary L. Tormala
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Personality trait change in three sub-Saharan countries: Normative development and life events.
Peter Haehner, Luzelle Naudé, Christopher J. Hopwood, Catherine M. Shirima, Sumaya Laher, Elizabeth N. Shino, Stephen Asatsa, Maria Florence, Tracey-Ann Adonis, Wiebke Bleidorn, Amber G. Thalmayer
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Observers (and transgressors) prefer creative punishments.
Timothy G. Kundro, Salvatore J. Affinito, Daniela Rodriguez-Mincey
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Truth over falsehood: Experimental evidence on what persuades and spreads.
Nicolas Fay, Keith J. Ransom, Bradley Walker, Piers D. L. Howe, Andrew Perfors, Yoshihisa Kashima
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Multivariate Behavioral Research

Improving the Evaluation of Construct Change Over Time: Advantages of Longitudinal Moderated Nonlinear Factor Analysis Over Conventional First-Order Growth Models
Siyuan Marco Chen, Daniel J. Bauer
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Evaluating Model Predictive Performance in Confirmatory Factor Analysis with Binary Outcomes Using the InterModel Vigorish
Lijin Zhang, Charles Rahal, Klint Kanopka, Esther Ulitzsch, Zhiyong Zhang, Benjamin W. Domingue
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Personality and Social Psychology Bulletin

Subjective Well-Being Enhances Experiential Perceptions
Hyewon Oh, Joseph K. Goodman, Dan R. Schley, Incheol Choi, Kathleen D. Vohs
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The experiential advantage refers to the well-being people derive from experiences over material goods. This research took a psychological needs approach and tested whether well-being predicts seeing purchases and products as being able to offer experiences. Five studies, using trait and state measures of well-being and sampling people in Asia and North America, supported this hypothesis. Controlled studies found that people higher in trait well-being viewed purchases as more experiential (Studies 1 and 5). Momentary well-being, whether measured or manipulated, showed a similarly positive impact of higher well-being on experiential perceptions (Studies 2–4). The effect was specific to perceptions of the experiential nature of products, not their materiality, and was most consistent for the positive affect component of well-being. Combined with prior findings, results suggest a self-reinforcing, benevolent cycle: experiences improve well-being, and well-being orients people to the experiential, need-satisfying aspects of products, which may then further support well-being.
Trust, But Verify: How (In)consistent Allyship Shapes Disadvantaged Group Members’ Perceptions
Patricia Ciordas, Charlotte E. Moser, Shaun Wiley, Anna Kende, Yasin Koc
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Advantaged group members can play a significant role in advocating for social change on behalf of disadvantaged groups. Drawing on Kelley’s covariation model and the attribution-identity model of ally sincerity, we argue that allyship that is inconsistent over time raises doubt about advantaged group members’ motives. In four studies conducted in theUnited States, we found that Black Americans (Study 1, N = 330) perceived White Americans who participated consistently in protests for racial equality as more internally motivated and as better allies than those protesting for the first time, and that LGBTQIA+ individuals viewed inconsistent (i.e., decreasing or alternating) participation over time by straight allies as less internally motivated and less trustworthy than consistent participation (Study 2, 3, and 4, N s = 287, 601, 434) or a control condition (Study 3). Our results highlight the importance of sustained allyship for positive perceptions of advantaged group allies.
Unintentional Outcomes as a Catalyst for Brainstorming
Taly Reich, Alexander G. Fulmer, Kelly B. Herd
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Companies increasingly engage in ideation exercises both with their employees and the public. One field experiment with Marketing and Sales employees at a candy company and four laboratory studies demonstrate a novel strategy to promote ideation quantity and quality. They reveal that prompting people to reflect on a history of their own unintentional outcomes in different domains can promote subsequent ideation in brainstorming tasks. This occurs because reflection on one’s unintentional outcomes can incite motivation to regain threatened control. We demonstrate this effect in various domains and in several different contexts that have practical implications for both organizational managers and individuals. Further, we identify a theoretically driven moderator of this effect, showing that the promotion of ideation occurs subsequent to control threats in domains perceived as relatively malleable, in which there is an expectation that control can be regained, but does not in domains perceived as relatively non-malleable.

Psychological Methods

Handling missing values when using neighborhood selection for network analysis.
Kai Jannik Nehler, Martin Schultze
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Heteroskedasticity-robust inference in Bayesian linear regression via the generalized method of moments.
Weicong Lyu
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Factored structural equation modeling in blimp.
Craig K. Enders, Brian T. Keller
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Modeling intraindividual variability as a predictor with intensive longitudinal data.
Lijuan Wang, Xiao Liu
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You must parcel carefully if you have to! Comparing eight item parceling strategies with the item-level model for bifactor predictive models.
Jinsoo Choi, Bo Zhang, Dexin Shi, Sunbeom Kwon, Leo Alexander
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Variable selection for explaining interindividual heterogeneity in longitudinal growth trajectories.
Qian Zhang, Haochen Lei, Palmer Swanson, Hongyuan Cao, Elizabeth H. Slate
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Psychological Science

Does Income Inequality Predict Adolescent Depressive Symptoms?
Sondre Aasen Nilsen, Kyrre Breivik, Kjell Morten Stormark, Tormod BĂže
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Income inequality is frequently cited as a forceful determinant of mental health and as a possible contributor to the rising trend in adolescent depressive symptoms. However, research findings often rely on low-powered cross-sectional designs. We conducted a preregistered study of the within-municipality effect of income inequality on adolescent depressive symptoms in Norway, covering ≈550,000 respondents nested within 863 municipality years and 340 municipalities. Using multilevel modeling and equivalence testing, the overall within-municipality effect of income inequality was neither statistically significant nor practically meaningful and did not significantly interact with family financial situation. A significant gender interaction showed that rising inequality predicted slightly higher depressive symptoms among females and slightly lower among males; however, the main gender effects were also probably too small to be meaningful. We conclude that changes in income inequality likely do not meaningfully predict nor help explain changes in adolescent depressive symptoms in Norway from 2010 to 2019.
The Rise, Impact, and Imbalances of Big-Team Psychology
Nicholas A. Coles, JoĂŁo Francisco Goes Braga Takayanagi, Gabrielle L. Grant, Dana M. Basnight-Brown
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The present work evaluates the rise, impact, and imbalances of big-team psychology via an analysis of 3,023,895 articles published in the 21st century. Results indicate that big teams—ranging from 10 to more than 100 authors—are relatively unusual ( n = 49,695) but increasing in popularity. More notably, such collaborations generate unusually high impact in terms of yearly mentions in scholarly articles ( n = 39,788,158), the news ( n = 1,018,639), social media ( n = 5,971,965), and policy documents ( n = 69,959). An examination of country-level sociocultural indicators revealed that first authors, in general, tend to be in regions that are relatively WEIRD: Western, Educated, Industrialized, Rich, and Democratic. However, this imbalance is slightly more pronounced among larger teams. In summary, results suggest that big-team science is an emerging trend in psychology—one that is unevenly deployed across world regions to generate high-impact scientific insights.
Neural-Context Reinstatement of Recurring Events
Adam W. Broitman, Michael J. Kahana
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Episodic recollection involves retrieving context information bound to specific events. However, autobiographical memory largely comprises recurrent, similar experiences that become integrated into joint representations. In the current study, we used scalp electroencephalography (EEG) to extract a neural signature of temporal context and investigate whether recalling a recurring event accompanies the reinstatement of one or multiple occurrences. We asked 52 young adults (aged 18–30) from the Philadelphia area to study and recall lists of words that included both once-presented and repeated items. Participants recalled repeated items in association with neighboring list items from each occurrence, but with stronger clustering around the repetition’s initial occurrence. Furthermore, multivariate spectral analyses of EEG data recorded just prior to the recall of these words revealed stronger patterns of context reinstatement of the first occurrence than the second. Together, these results suggest that the initial occurrence of an event carries stronger temporal-context associations than later repetitions, as predicted by retrieved-context frameworks of episodic memory.
Conscious Detection of Spoken Words Depends on Their Valence
Gal R. Chen, Zaheera Maswadeh, Leon Deouell, Ran R. Hassin
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Conscious experiences appear to play a central role in human behavior, yet most neural processing occurs outside of consciousness. Understanding how the mind prioritizes information for consciousness is, therefore, crucial for theories of cognition. Prior research has largely focused on vision, but generalization is tenuous given the vastly different characteristics of the senses—particularly for audition, which lacks foveation and cannot be intentionally stopped. We examine the affective domain, for which prioritization is not well understood. In three experiments (two preregistered), 101 Hebrew-speaking adults completed a visual task with a stream of auditory pseudowords in the background. Occasionally a meaningful word appeared, and participants were asked about its presence. Using objective and subjective awareness measures, we found that neutral words were prioritized over negative words, regardless of task difficulty, intelligibility, and low-level features. These findings challenge theorizing and modal intuitions, and we discuss ways in which those can be reconciled.

Psychology of Music

‘It made me feel helpless because I couldn’t control anything’: Occupational stress and well-being experiences of conservatoire music students
Simone Willis, Mikel Mellick, Rich Neil, David Wasley
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Conservatoire music students experience a range of demands including performance, academic, and interpersonal demands. If not effectively managed, demands may lead to stress and negative well-being outcomes. This qualitative study explored conservatoire music students’ experiences of occupational stress and well-being, informed by a transactional stress theory. Six conservatoire music students were purposively selected to participate in semi-structured interviews. Participants discussed two stressful events: one perceived positively and a second perceived negatively. Interpretative Phenomenological Analysis was adopted and five themes developed: (a) Performance Demands; (b) Organisational Demands; (c) Relationship Demands; (d) Academic Demands; and (e) Multiple Demands. Participants commonly appraised demands as a threat. A smaller number of challenge or benefit appraisals were reported, with few harm or loss appraisals. Key underlying properties of stress appraisal were self and other comparison, preparation, and novelty. Participants highlighted the personal resources, psychological skills and problem-solving, and the organisational resource of social support to manage stressful experiences. Well-being outcomes related to stress appraisals. This study provides insight into the intra-individual processes related to occupational stress and well-being of conservatoire music students. Findings suggest interventions targeting the conservatoire culture and curriculum need exploring to create a positive learning culture and support students to cope with demands.
“I Can See Clearly Now”: On the time-varying associations between self-concept clarity and music preferences across adolescence into young adulthood
Andrik Becht, Tom ter Bogt
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This longitudinal study explored the connections between self-concept clarity (SCC) and music preferences across early adolescence into young adulthood. Six times, N = 900 Dutch adolescents and young adults ( M age T1 = 12.48 years, 51% females) completed a survey assessing their SCC and music preferences, categorized into mainstream music (including pop, hip-hop, popular rock, and dance/trance) and non-mainstream music (heavy metal, goth, and hardstyle dance). Latent growth curve analyses with SCC as time-varying covariates confirmed that there was no systematic association between SCC and mainstream preferences for pop, hip-hop, and dance/trance in mid- to late adolescence, and that this relationship became mostly positive in young adulthood. However, SCC was negatively associated with a preference for another type of mainstream music: popular rock. As predicted, adolescents with low SCC also preferred thematically complex, non-mainstream genres such as heavy metal and goth, or music that is linked to a non-mainstream subculture: hardstyle dance. Lower SCC levels remained linked to higher preferences for goth and heavy metal music even into young adulthood. This suggests that goth and heavy metal continue to hold significant importance for young people who struggle with clarifying their identity.

Psychology of Popular Media

Self-administered media prescriptions: Training algorithms to deliver inspirational content to reduce stress and increase goal motivation.
Robin L. Nabi, Amber van der Wal
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