Psychological Reports最新文献

Despite substantial gender equality in highly gender-egalitarian countries like Germany, perceptions of persistent inequality remain widespread. We examine systematic perception gaps that may explain this disconnect. In a survey of 735 German adults, participants reported their perceived societal and personal gender inequality, estimated others' perceptions, and indicated their attitudes toward gender equality measures. Both women and men perceived women as less fairly treated than men. Women reported a classic person-group discrepancy, perceiving more inequality in society than in their own lives, and projected this discrepancy onto 'average women.' This projection, combined with systematic misperceptions of others' beliefs forms what we term a pluralistic illusion: the logically incoherent belief that most others perceive more inequality in society than people personally experience. We also find a better-than-average effect such that participants see themselves as more supportive of gender equality than the average person. Finally, both men and women substantially underestimated men's support. In combination, these perception gaps may help explain persistent, polarized debates about gender equality in egalitarian societies.

This paper will review the evolution of Social Identity Mapping as a potential theoretical and analytical framework for interpreting complex online behaviours. It will commence with an exploration of the evolution and utility of social identity mapping, before critically examining the application of social identity mapping in empirical research, both online and in person. It will conclude by presenting an argument for the ability to, and need for, objective markers of the self to be developed as a mechanism for understanding multiple salient social identities, across multiple online platforms, in a manner that is generalisable to a range of Contexts.

Psychological research increasingly relies on high-dimensional data, yet it remains challenging to determine whether patterns of representation are independent across experimental contexts. Traditional multivariate approaches, such as decoding, are sensitive to pattern differences but do not directly test factorial hypotheses. In contrast, analysis of variance (ANOVA) provides inferential clarity but is limited to univariate measures. To address this gap, we introduce Multivariate Interaction Classification (MIC), a framework that combines the logic of factorial interaction tests with the sensitivity of multivariate pattern analysis. MIC evaluates representational independence by comparing within-context and cross-context decoding performance. Through simulation studies, we show that MIC reliably distinguishes modality-specific, modality-general, and hybrid representational structures. We then validate the method with affective ratings of gustatory and auditory stimuli, demonstrating how MIC can reveal the coexistence of specific and general codes. By providing a statistically grounded and easily implemented tool, MIC enables researchers to move beyond descriptive decoding toward confirmatory tests of representational hypotheses. All code and materials are openly available to ensure transparency and reproducibility.

The current progressive adoption of online platforms and web-based interventions, within the context of Cognitive Behavioral Therapy (CBT) services, offers a novel opportunity to scale evidence-based psychotherapy. In the present work, we depict the development of a web and native application within the Italian landscape, GRETA (Graphic Robotic Engine for Therapy Automation). GRETA provides the following functions: (a) Management of therapy appointments and payments; (b) Clinical data, therapy progress, and sessions summary between professionals; (c) Production of the medical report and notes for external institutions; (d) Homework, materials, psychometric measures, progress reports, and therapy notes; (e) Systematic monitoring of the therapeutic process and outcomes; (f) Ensuring confidentiality, security, and integrity of patient information; (g) Collection, aggregation, and analysis of anonymized patient data through statistical reports and graphical dashboards. Beyond the technological implementation, this study also assesses the effectiveness of therapy delivered through GRETA. Pre-post treatment comparisons were conducted on a sample of 442 patients discharged for any reason by the CBT service, categorized into three diagnostic groups: anxiety disorder, depressive disorder, and comorbid anxiety and depressive disorder. Results revealed significant improvements in symptom severity and functional adjustment across all groups. Future developments of GRETA will involve integrating Artificial Intelligence-based features, such as predictions of clinical outcomes.

Interventions in which people are exposed to counter-stereotypical role models are often used for breaking gender stereotypes. Most gender role-model interventions focus on adolescents and emerging adults. Yet, middle childhood might be a highly effective period for changing gender stereotypes because children are still learning about gender and gender roles. Therefore, this study examined the effects of a newly developed educational program with counter-stereotypical female heroines, on children's gender schemas and self-esteem. Differences between boys and girls in the effects of the intervention were also investigated. A sample of 125 Dutch children (53% girls, 7-11 years old) completed a quantitative survey (assessing gender schemas, self-esteem) in class before and after completing the Heroines program with their teachers. Results showed that the program reduced children's gender stereotypes about activities, but did not lead to change in five other gender schemas or self-esteem. Thus, the Heroines program had modest effects on some gender schemas, whereas most gender schemas did not change. This limited change might be due to the relatively short duration of the program, its broad nature, and the possible resistance of gender schemas to change as they have been formed over years in environments that are filled with gender-stereotypical information.

The present study investigated whether work-related subjective well-being (SWB) can be assessed using employee responses to interview questions. Our objective was to provide proof-of-principle evidence that unstructured language can be used to simultaneously predict multiple SWB components. To achieve this goal, we asked 386 employees (52% women) from various industries to complete self-reported measures of SWB, and then we conducted individual interviews. The responses collected during structured interviews were analyzed using transformer-based models to extract semantic characteristics. Next, the semantic characteristics were used to predict multiple SWB indicators. Results showed that descriptions of typical work activities offered fair predictive accuracy of SWB scales, performing better than narratives focused on positive or on negative experiences. Furthermore, simpler machine learning algorithms such as Naïve Bayes achieved higher accuracy than more complex models, demonstrating the effectiveness of transformers-based approaches. Although the study has limitations, the results provide a foundation for using NLP in assessments of SWB, opening the way for tools that are customizable and text-sensitive.

Researchers reject the idea that social media use causes anxiety and depression, instead reporting that cognitive and behavioral variables of social media self-control failure, fear of missing out, and social media social comparison contribute to anxiety and depression. While prohibiting, delaying, or fasting from social media are suggested by popular writers as answers to these problems, prohibiting social media is known to be ineffective at preventing these cognitive social media problems once a person begins using social media. Moving forward, counselors should prepare themselves to use the therapeutic tools they currently have or develop new tools for treating clients whose problems are related to social media. We sought to determine if social media self-control failure, fear of missing out, and social media social comparison were associated with deficiencies in self-compassion. Our pilot study (n = 61) confirmed that the problematic social media outcomes share considerable variance with deficiencies in self-compassion with moderation models found. Thus, self-compassion interventions may be useful for treating social media self-control failure, fear of missing out, and social media social comparison, but future research will need to explore the efficacy of these interventions.

Internalizing symptoms emerge early and can negatively affect engagement and achievement during the primary-school years. At the same time, children's socio-emotional competencies may shape how they appraise and regulate school-related stress. This cross-sectional study tested whether Trait Emotional Intelligence (trait EI) and Social Intelligence (SI) are associated with anxiety and depressive symptoms and academic/behavioral outcomes, and whether these competencies distinguish clinical vs. non-clinical internalizing levels. Participants were 228 Italian primary-school children (8-11 years). Measures included the TEIQue-CSF (trait EI), a child-adapted TSIS (SI: Social Awareness, Social Information Processing, Social Skills), the Anxiety Scale Questionnaire for Children (scholastic anxiety), the Children's Depression Inventory (depression; clinical cut-off = 19), teacher-reported grades (Italian, English, Mathematics), and behavior ratings. Analyses comprised correlations, binomial logistic regressions predicting clinical status, and hierarchical multiple regressions for grades and behavior. Higher trait EI was inversely related to scholastic anxiety and depression and reduced the odds of meeting clinical criteria for both outcomes. SI showed weaker, facet-specific links: Social Information Processing was the most informative SI dimension for Mathematics grades. Trait EI predicted higher language grades (Italian and English), whereas associations with behavior ratings were small or non-significant. Findings highlight trait EI as a school-relevant protective correlate of internalizing symptoms in late childhood, while suggesting that Social Intelligence relates more to academic performance. Implications for brief, classroom-based socio-emotional learning are discussed.

This study builds upon Riester and Keller (2025) and extends prior findings by (a) employing an experimental approach involving the recollection of neutral, positive (meaningful) or negative (bullshit) work episodes (b) examining the effect of the experimental manipulation, and specifically the recollection of bullshit episodes, on the reported likelihood to engage in deviant work behavior, turnover intentions and negative affect, (c) investigating the mediating role of negative affect, and (d) analyzing the moderating role of work ethic. In a sample of German employees (N = 253), we manipulated the recollection of experienced work episodes, including a neutral, a meaningful, or a bullshit episode. Results show that recalling bullshit work episodes was associated with increased negative affect and, in turn, with enhanced likelihood to engage in problematic workplace behavior and turnover intentions compared to the other experimental conditions. Furthermore, these relationships were amplified among individuals with stronger work ethic convictions. In contrast, the effects of recollecting meaningful (vs. neutral) experiences at work were not significant for all dependent variables. The study extends prior research (Riester & Keller, 2025) through an experimental investigation and underscores the effects of bullshit job experiences on negative affect, the tendency to engage in unethical work behavior and the critical role of work ethic.

Attitudes toward suicide are complex and multifaceted. Their predictive roles and how they interact with mental health in suicidal ideation and suicide attempts are not well understood. Elaborating on attitudes toward suicide can help contribute to suicide prevention. The current study examined whether and how attitudes toward suicide and depression levels are involved in suicidal ideation and suicide attempts among college students. A cross-sectional survey was administered to 1,427 Chinese college students (61.32% females; mean age, 22.42 years), of whom 570 reported suicidal ideation. Participants completed questionnaires to assess their endorsed attitude toward suicide, stigmatized attitude toward suicide, self-stigma toward suicide, depression, suicidal ideation, and suicide attempts. Structural equation modeling revealed that the associations between the three types of attitudes, i.e., endorsed attitude, stigmatized attitude, and self-stigma, and suicidal ideation and suicide attempts were fully or partially mediated by depression. The results suggested that attitudes toward suicide significantly influence suicidal behaviors through depression levels and future suicide prevention efforts should consider these influences.