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Investigating the role of multiple disadvantaged groups and intersectional awareness in promoting intraminority solidarity
No full textLimited research has examined the dynamics of collective action among disadvantaged groups, especially the impact belonging to multiple disadvantaged groups has on intraminority solidarity. While previous research has found that perceived similarity fosters collective action among disadvantaged group members, in this paper we introduce intersectional awareness as a novel mechanism through which intraminority solidarity among multiple disadvantaged groups can be facilitated. Participants were categorized by their number of disadvantaged group memberships: 0, 1, 2, and 3, based on their race, gender, and sexual identities. Across two studies, participants (N = 550) with a greater number of disadvantaged identities were more likely to engage in collective action for two disadvantaged outgroups (i.e., Muslims, people with a disability). Mediation analysis revealed that increased intersectional awareness but not perceived similarity explained this relationship. This research introduces intersectional awareness as a novel mechanism through which intraminority solidarity can be fostered.peerReviewedpublishedVersio
A transdiagnostic approach to Psychiatric and Psychological Brief Psychotherapy PKP
No full textBased on an integrative behavioural and psychodynamic understanding of the case, PKP Brief Psychotherapy applies evidence-based, disorder-specific behavioural therapy interventions for anxiety, depression, alcohol dependence and chronic pain. In addition, a transdiagnostic intervention and baseline inventory is now available so that patients with less common diagnoses can also be treated across disorders. These will be discussed in this paper. Firstly, the development of the PKP project and its theoretical and conceptual background are described. The current state of research is briefly outlined.https://eupehs.org/haupt/european-psychotherapy/peerReviewedpublishedVersio
When we were young: Memories of early mathematics experiences
No full textEarly math experiences predict children’s later math abilities and beliefs. However, less is known about longer-term associations between early childhood math experiences and adult math outcomes. The present study examined emerging adults’ earliest memories of mathematics and reading experiences, asking whether characteristics of their early learning memories differ across domains of learning and relate to their adulthood math achievement and beliefs. Undergraduate students (n = 161, MAge = 19.6 years) described their earliest memories of math and reading, then completed measures of their math anxiety, math task value, and math achievement. Our results reveal significant domain differences in participants’ age during their earliest memories, the level of social interaction, and their overall rating of the experience. Emerging adults with more positive memories of their earliest math experiences had lower math anxiety, higher math task value, and higher math achievement. Our results provide additional evidence of the long-term associations between early math experiences and later math outcomes and underscore the need to promote early math experiences that are positive and engaging for young children.peerReviewedpublishedVersio
The healthy = sustainable heuristic: Reaction Times and heuristic scope
No full textAim one of this study is to investigate whether the ‘healthy = sustainable’-heuristic occurs on an automatic, more implicit level. Aim two of the study is to determine the scope of the heuristic, i.e., if it is applied only to foods which are 'ambiguous', i.e., not clearly healthy or unhealthy or also is applied to 'unambiguous' foods such as vegetables or sweets. The sample of N = 534 living in Austria will be collected via a panel provider. In part one, participants see images of foods with custom-made high/low sustainability labels and are asked to decide if the foods are healthy or unhealthy while their reaction times are recorded. In part two participants see images of foods with manipulated food labels depicting either the Nutri-Score or the Eco-Score and are asked to rate foods on several dimensions (among which healthiness and sustainability). Data will be analysed using Bayesian multi-level-modelling.unknownothe
A meta-analysis of the cross-sectional and longitudinal relations between executive functioning and math in early childhood
No full textMath and executive functioning (EF) skills are thought to be tightly linked in early childhood. To facilitate our understanding of this link in early childhood, here we present a meta-analysis of over 1,000 different correlation values between EF and math measures in early childhood (4-6yrs). The overall average EF-Math relation was r = .350, 95% CI [.338, .361]. We then examined whether the strength of the EF-Math relation in this age-range depends on measurement factors, socio-economic status (SES), and the nature and direction of longitudinal relations. [1] Overall achievement measures of EF and math generally led to higher estimates of the EF-Math relation relative to measures of isolated EF subprocesses or specific math skills, though this may be due more to measurement than developmental factors. [2] EF measures using numerical stimuli inflate estimates of the EF-Math association by roughly 40%. [3] Low SES samples showed the strongest average EF-Math associations. [4] Longitudinal associations that do not adjust for Time-1 measurement of the outcome variable lead to inflated (as much as 120%) estimates of directional associations. After making this adjustment, we found [5a] significant, albeit reduced bidirectional relations between EF and math, and [5b] that math is a stronger predictor of future change in EF than the reverse. In sum, the results of this work contribute to theoretical models of the interaction between EF and math in early childhood, as well as to practical attempts to foster growth in children’s EF and math skills, whether in the lab, classroom or living room.peerReviewedpublishedVersio
Measuring belief in climate change with a single item
No full textBrief, but psychometrically valid assessments of psychological constructs are increasingly needed to be included in larger psychological and other social scientific studies, such as Many Labs projects or representative surveys. Here, we provide a novel one-item measure of individual differences in belief in climate change. Based on two studies (N = 913, N = 288) recruited from various global regions, we establish convergent, predictive, and discriminant validity. More specifically, we find that the single-item measure correlates with other constructs measuring belief in climate change and with relevant downstream constructs, among them intentions to engage in pro-environmental behavior, actual consequential behavior, and self-reported everyday behaviors. We therefore conclude that the single item is a suitable instrument to measure belief in climate change when multiple-item assessments are either too costly or otherwise unfeasible.peerReviewedpublishedVersio
The “favorite person” in borderline personality disorder: A content analysis of social media posts
No full textIn the borderline personality disorder (BPD) online community, shared experience has led to the emergence of the term “favorite person” (FP) to describe a unique interpersonal relationship. Despite its widespread use, this term has not been defined in the scholarly literature. The purpose of this exploratory study was to develop a working definition of FP through quantitative content analysis of relevant Instagram posts. Results suggest that FP may be defined as an insecure attachment figure who consumes the thoughts and evokes the abandonment fears of individuals with BPD. The FP is viewed as a rescuer and depended on for a sense of identity and emotional validation. Reactivity of mood and a tendency to hypermentalize around the FP may contribute to the instability evident in these relationships. These findings offer a novel understanding of the lived experience of BPD relationships, having important implications for treatment and stigma reduction.peerReviewedpublishedVersio
An Evaluation of a Story Exchange Teacher Training Intervention to Promote Empathy
No full textEmpathy, a key social emotional competency, plays an integral role in our daily
functioning and social interactions, and the role of empathy in educational
settings cannot be understated. Schools are widely engaged in promoting social
emotional learning (SEL) and, thus, empathy development in students. However,
it has become evident that student SEL and empathy promotion also require the
development of such skills in teachers. Storytelling interventions can be used in
school settings to promote the development of social emotional competencies.
However, little is known as to how engaging in such intervention training affects
teachers’ SEL and empathy development. This study explores the perspectives of
teachers (N=10) who engaged in a story exchange facilitator training
intervention.
Through semi-structured interviews this study explored the perceived effects of
the training on a) teachers’ social emotional competencies, particularly empathy,
b) attitudes towards the SEL training, and c) experiences of SEL intervention
implementation. Four themes were identified: the perceived importance of SEL
for teachers, training outcomes, training perceptions, and experiences of
intervention implementation. Findings indicate that the story exchange facilitator
training may enhance teachers own social emotional learning with strengths of
the training and issue in implementing the training outlined. Limitations and
directions for future research are explored.notReviewedothe
“we grind each other as stones and get rid of sharp edges”: Young people’s reported positive change, learnings, and growth through romantic relationships
No full textRomantic and intimate experiences serve as a crucial learning ground for individual and relational development, yet many aspects of this learning process remain underexplored. The present qualitative study explores romantic relationship-induced learning among 104 participants between 18 and 35, which may foster better navigation of their future relational interactions. Data, i.e., 37 in-depth and 67 written interviews, were analysed using reflexive thematic analysis, applying an inductive, semantic, and experiential approach. The report of themes created in the analysis describes how romantic experience positively affected the participants in: (i) identity (self-knowledge, personal growth, and self-evaluation), (ii) relational competence (communication, socio-emotional skills, and problem-solving), and (iii) partner decisions (relationship expectations, relationship boundaries).peerReviewedpublishedVersio
The Hybrid Modern Network Model: A multi-technique framework for comprehensive network analysis
No full textThis research addresses the limitations of traditional network models in capturing the complexity and dynamics of real-world social networks. Motivated by the need for a more comprehensive and flexible framework, the study introduces the Hybrid Modern Network Model (HMNM). The HMNM integrates foundational models like the Stochastic Block Model (SBM) and Preferential Attachment with advanced machine learning techniques, including Graph Neural Networks (GNNs), Reinforcement Learning (RL), Hierarchical Random Graphs (HRGs), Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs). The methods employed involve constructing initial network structures using SBM, simulating network growth through preferential Attachment, learning node embeddings with GNNs, dynamically optimizing network properties using RL, capturing hierarchical community structures with HRGs, controlling degree distributions using GANs, and uncovering latent patterns with VAEs. The empirical illustration of HMNM highlights its effectiveness in providing a more realistic, scalable, and comprehensive analysis of social networks compared to traditional models. Integrating diverse methodologies allows for accurately modeling of network structures, dynamic processes, and latent patterns. In conclusion, the HMNM offers significant advancements in network modeling, providing a robust and flexible framework for analyzing social networks. This model overcomes the limitations of traditional models and delivers deeper insights into the complexities and dynamics of social structures. Future research will optimize the HMNM and explore its applications across various domains. The R programming code used for the network simulations and visualizations is conceptual and demonstrates the HMNM framework. The results and metrics are illustrative placeholders, emphasizing the methodology rather than empirical validation.peerReviewedpublishedVersio