I checked 15 psychology journals on Tuesday, March 31, 2026 using the Crossref API. For the period March 24 to March 30, I found 35 new paper(s) in 12 journal(s).

Advances in Methods and Practices in Psychological Science

Chatbots Are Undermining Crowdsourced Research in the Behavioral Sciences: Detecting Artificial Intelligence–Assisted Cheating With a Keystroke-Based Tool
Michael W. Asher, Gillian Gold, Eason Chen, Paulo F. Carvalho
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Generative artificial intelligence (AI) poses a significant threat to data integrity on crowdsourcing platforms, such as Prolific, which behavioral scientists widely rely on for data collection. Large language models (LLMs) allow users to generate fluent and relevant responses to open-ended questions, which can mask inattention and compromise experimental validity. To empirically estimate the prevalence of this behavior, we analyzed keystroke data from three studies ( N = 928) on Prolific between May and July 2025. Using an embedded JavaScript tool, we flagged participants who pasted text or whose keystroke count was anomalously low compared with their response length. For each flagged participant, we manually compared detected keystrokes with their final response to determine if the text could have been typed. This confirmed that despite deterrence measures, approximately 9% of participants submitted responses consistent with AI assistance or other forms of outsourced responding. These participants outperformed noncheaters (by up to 1.5 SD ), were more than twice as likely to share geolocations with other participants (suggesting possible proxy use), and exhibited lower internal consistency on questionnaire scales. Simulated power analyses indicate that this level of undetected cheating can diminish observed effect sizes by 10% and inflate required sample sizes by up to 30%. These findings highlight the urgent need for new detection methods, such as keystroke logging, which offers verifiable evidence of cheating that is difficult to obtain from manual review of LLM-generated text alone. As AI continues to evolve, maintaining data quality in crowdsourced research will require active monitoring, methodological adaptation, and communication between researchers and platforms.

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. 
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.
Measuring naturalistic speech comprehension in real time
Irmak Ergin, Jill Kries, Shiven Gupta, Maria Papworth Burrel, Laura Gwilliams
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Speech comprehension has been described as an effortless and robust process; yet, in real-world contexts, it is common for a listener to misunderstand what was said or fail to derive meaning entirely. Typically, methods of measuring speech comprehension are applied ‘post hoc’ - that is, after the comprehension has happened. This approach fails to capture comprehension as it occurs, limiting the field’s understanding of the cognitive processes involved in real-time comprehension. To overcome these challenges, we designed and tested a novel method of measuring real-time speech comprehension during naturalistic listening. We built a slider device that synchronizes with experimental software and provides millisecond read-out. In three experiments, participants listened to audiobook segments while providing continuous comprehension ratings using the slider. To vary comprehension success, we presented speech segments at speed factors of 1–5 times faster than normal. We validated the time-resolved slider data against established speech comprehension assessment methods. Overall, our findings validate our novel time-resolved comprehension measure and demonstrate that it is possible to derive an online behavioral measure of real-time speech comprehension. We also confirmed numerous limitations of static post hoc assessments, including challenges with multiple-choice question design and the confounding of potential effects due to recency bias and comprehension for summarization. The measure proposed here overcomes the constraints of static post hoc assessments and can be effectively integrated with neuroimaging techniques, offering a valuable tool for future research on dynamic processes during naturalistic listening.
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.
Network psychometrics in practice: A practical framework for designing empirical studies that utilize a psychological network approach
Monique Chambon, Jonas Dalege, Janneke E. Elberse, Frenk van Harreveld
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A psychological network approach enables the study of psychological phenomena as networks of interacting elements by utilizing network psychometrics. This approach is gaining increasing popularity in different domains of empirical psychological research such as clinical and social psychology. Simultaneously, a scientific debate has emerged on the added value and application of employing such an approach. The current paper contributes to this debate by providing an applied perspective on designing empirical studies that employ a psychological network approach and does so based on best practices in previous empirical psychological research. With a practical framework, we aim to support researchers who want to employ a psychological network approach to mitigate potential criticism in the design phase of their study. The framework can be summarized in three iterative steps. This paper describes each step in detail, including illustrative examples and practical considerations. First, researchers are advised to evaluate their argumentation for adopting a psychological network approach and whether this is the best approach for their research aim. This approach is suitable for aims ranging from descriptive accounts of complex survey data to testing hypotheses about the network’s structure. Second, researchers should carefully evaluate which variables the psychological network should contain. Such decisions should be informed by previous research (e.g., theoretical frameworks). Third, researchers should consider which research design and type of data are optimal to answer their research questions, as different designs provide different insights. Adopting a psychological network approach in accordance with the framework presented in this paper can further advance empirical psychological research.

Computers in Human Behavior

Generic title: Not a research article
Corrigendum to “The influence of cyber descriptive norms on immoral online behavior: The moderating role of moral conviction” [Computers in Human Behavior, 181 (2026) 108991]
Jin Wang, Chang Liu, Tumaresi Paerhati, Zhuo Wang, Xilei Zhang, Yu Ku
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Time to (Re)visualise Victims? Introducing Shadow Victims of Digital Misinformation
Souvik Mukherjee, Lennon Yao-Chung Chang
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Development of digital empathy: Non-linear relationships between daily digital communication time and digital empathic tendencies
Andrew M. Collins, Wayne A. Warburton, Naomi Sweller, Kay Bussey
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From AI Psychosis to Brain Rot: How pseudo-diagnoses endanger genuine psychological and medical discovery in challenging times
Christian Montag, Daniel L. King, Benjamin Becker, Joël Billieux
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Physiological synchrony in elite esports matches driven by competitive motivation
Ken Watanabe, Sorato Minami, Naoki Saijo, Makio Kashino
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Journal of Experimental Social Psychology

Gossip or confrontation? Sanctioning environmental norm violations and the reputation of punishers
Xiyan Song, Catherine Molho, Paul A.M. Van Lange
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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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Does ignorance love company? The social dynamics of information avoidance
Katharina Reher, Martin Götz, Filippo Toscano, Jörg Gross
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Using intersectional implicit association measures does not consistently improve the predictive validity of the implicit association test
Jeffrey To, Jordan Axt
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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

Cultural differences in the Personality Triad: The interplay of personality traits, situation characteristics, and behavioral states around the world.
Niclas Kuper, character(0), Gwendolyn Gardiner, Erica Baranski, David C. Funder, John F. Rauthmann
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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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Multi-Group Multidimensional Classification Accuracy Analysis (MMCAA): A General Framework for Evaluating the Practical Impact of Partial Invariance
Meltem Ozcan, Mark H. C. Lai
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Multivariate Location-Scale Models for Meta-Analysis
Katrin Jansen, Steffen Nestler
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Organizational Research Methods

Applying Machine Learning and Natural Language Processing Methods to Support Taxonomy Development and Maintenance
Nathaniel M. Voss, Jiayi Liu, Saron Demeke, Martin C. Yu, Harrison J. Kell, Brian Prost, Dan J. Putka
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Taxonomies provide a systematic way to organize phenomena and have various practical and theoretical benefits for organizational researchers and practitioners. While taxonomy development and maintenance is often a burdensome process (e.g., time-consuming, costly, and prone to judgmental error), advances in natural language processing (NLP) have the potential to streamline this process. In this study, we employed various evaluation metrics (e.g., cosine similarity) to investigate how machine learning (ML) methods and large language models (LLMs) can automate taxonomy development and maintenance. We examined two embedding models, six clustering algorithms, and three generative LLMs (for creating cluster labels) to construct taxonomies and compared their alignment with four established taxonomies (CABIN, IPIP-NEO-120, ATAF, and O*NET). The confirmatory taxonomic method we examined resulted in effective clustering (i.e., similar text statements were consistently grouped), frequently yielded structures similar to the original taxonomies for ATAF, IPIP-NEO-120, and CABIN (with O*NET being more variable), and resulted in extremely efficient taxonomy title generation. These findings can provide researchers with a foundation for how to approach NLP-based taxonomy development and maintenance activities for their own contexts.

Personality and Social Psychology Bulletin

Around But Not Close? Mapping Normative Trends in Cross-Race Contact During Adulthood
Stephen Antonoplis, Claude S. Fischer
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How do people form cross-race relationships in everyday life, and do people vary from each other in this process? Answering these questions can yield useful insights for scholars interested in encouraging cross-race contact. We investigated how people ( N = 1,156 Bay Area adults) met their different-race (vs. same-race) contacts, the roles that different-race contacts occupied in their personal networks, and the content and quality of their relationships with their different-race contacts. We found that different-race contacts were, on average, “around but not close.” They were met in less intimate settings; they occupied less intimate roles; and they were felt less close to. Importantly, processes varied across people. People who formed cross-race kin relationships were the most likely to have stable cross-race contact, and people who engaged in “high effort” activities with their different-race contacts (e.g., confiding in) had closer relationships with them. We highlight insights of these results for encouraging cross-race contact.
Broken Promises: Betrayal and Support for Violence in Intergroup Relations
Josephine Gellersen, Eran Halperin, Tamar Saguy
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In diverse societies, minority groups may face challenges when events signal exclusion from a superordinate identity (SOI) shared with the relevant majority groups. We examine how such SOI threats relate to hardline political attitudes, focusing on betrayal as a potential mechanism. A cross-sectional study of Ethiopian Jews in Israel ( N = 276) showed that priming an SOI threat was associated with support for violent resistance via betrayal. A two-wave study of Arab-Muslims in Israel ( N = 165) showed that a real-time SOI-threatening event predicted betrayal and, in turn, increased support for violence, particularly among those with stronger baseline SOI. An additional two-wave study of Israeli Jewish women ( N = 584) during the recent Gaza war extended this framework to a broader SOI shared with women worldwide: stronger baseline SOI predicted higher expectations of solidarity, which, when undermined by SOI threat, was associated with greater betrayal and hawkish wartime policy support.
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

Factored structural equation modeling in blimp.
Craig K. Enders, Brian T. Keller
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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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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.

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.

Psychology of Popular Media

Which platforms count? The diverse meanings of “social media” in the United States.
Stephanie Torres-Pantoja, Lisa Rhee, Julian Unkel, Muniba Saleem, Joseph B. Bayer
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Reliving 10 years old: Descriptive insights into retro gaming.
Nick Ballou, Nicholas David Bowman, Thomas Hakman, Andrew K. Przybylski
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Exploring the evolving portrayal of #Ozempic content on TikTok.
Megan Sutton, Zachary Staffell, Karen Leung, Eva Pila
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