Toward an Integrative Psychometric Model of Emotions

Specific, situated, intra-individual, ambivalent, and open: integrating and advancing the research on entrepreneurial passion

While the research on passion for entrepreneurial activities has produced many definitions, measures, and models specifying components, predictors, and outcomes of the construct, integrating these disparate approaches with each other and with current developments in psychological science remains a challenge for the next generation of research studies. This review connects the research on entrepreneurial passion with current innovations and debates in measurement and method development, motivation, personality, and developmental psychology. The review proposes to reconsider how to measure entrepreneurial passion by (1) specifying the exact facets of entrepreneurial passion in theoretical models and measures, and (2) using psychometric and co-endorsement network models to examine the relationships among the facets and the facets' relationships with relevant predictors and outcomes. (3) The article proposes to link passion research to ongoing debates about states, traits, and emerging stability by formulating and testing process models that distinguish between state- and trait development and include recursive feedback loops. (4) The review connects research on entrepreneurial passion to current debates in emotion and motivation research by proposing to examine the ambivalent motivation and mixed emotions accompanying entrepreneurial passion with intra-individual methods. (5) To help passion researchers build on each other's work and enhance the trustworthiness of their work, the review calls for cumulative scientific insights by adopting multi-lab collaborations and other open science practices. (6) Finally, the review proposes a new, integrative theoretical model that distinguishes between the facets that drive affective thriving and those driving perseverance in the face of obstacles.

Annual Research Review: What processes are dysregulated among emotionally dysregulated youth? - a systematic review

Proliferation of the term "emotion dysregulation" in child psychopathology parallels the growing interest in processes that influence negative emotional reactivity. While it commonly refers to a clinical phenotype where intense anger leads to behavioral dyscontrol, the term implies etiology because anything that is dysregulated requires an impaired regulatory mechanism. Many cognitive, affective, behavioral, neural, and social processes have been studied to improve understanding of emotion dysregulation. Nevertheless, the defective regulatory mechanism that might underlie it remains unclear. This systematic review of research on processes that affect emotion dysregulation endeavors to develop an integrative framework for the wide variety of factors investigated. It seeks to ascertain which, if any, constitutes an impaired regulatory mechanism. Based on this review, we propose a framework organizing emotion-relevant processes into categories pertaining to stimulus processing, response selection and control, emotion generation, closed- or open-loop feedback-based regulation, and experiential influences. Our review finds scant evidence for closed-loop (automatic) mechanisms to downregulate anger arousal rapidly. Open-loop (deliberate) regulatory strategies seem effective for low-to-moderate arousal. More extensive evidence supports roles for aspects of stimulus processing (sensory sensitivity, salience, appraisal, threat processing, and reward expectancy). Response control functions, such as inhibitory control, show robust associations with emotion dysregulation. Processes relating to emotion generation highlight aberrant features in autonomic, endocrine, reward functioning, and tonic mood states. A large literature on adverse childhood experiences and family interactions shows the unique and joint effects of interpersonal with child-level risks. We conclude that the defective closed-loop regulatory mechanisms that emotion dysregulation implies require further specification. Integrating research on emotion-relevant mechanisms along an axis from input factors through emotion generation to corrective feedback may promote research on (a) heterogeneity in pathogenesis, (b) interrelationships between these factors, and (c) the derivation of better-targeted treatments that address specific pathogenic processes of affected youth.

Differences in emotional expression among college students: a study on integrating psychometric methods and algorithm optimization

BACKGROUND

College students are in an important stage of life development, and their emotional expression ability has a profound impact on their mental health, interpersonal relationships, and academic performance. There are significant differences in emotional expression among individuals, which are influenced by various factors such as gender, cultural background, and personality traits. However, traditional research on emotional expression often relies on a single measurement method, which has problems such as single data dimensions, limited analysis methods, and lack of real-time dynamism and personalization. To overcome these limitations, this study conducted a comprehensive analysis using psychometric methods and algorithm optimization techniques.

METHODS

The Emotional Intelligence Scale (EQ-i) and the depression-anxiety-stress-21 (DASS-21) were used to quantitatively evaluate the emotional state of college students, and their facial expressions and speech emotion data were collected. In order to improve the precision of data analysis, random forests, support vector machines, and neural network machine learning algorithms were applied, and the variance analysis was used to calculate and compare the emotional differences of different genders and academic backgrounds in different grades.

RESULTS

The research results showed that gender, major, and grade differences significantly affected the emotional expression of college students. The F-values for the total EQ-i score of different genders were 7.00, and the F-values for depression, anxiety, and stress scores between different grades were 22.45, 12.48, and 9.14. Male engineering students scored higher in emotional intelligence than female liberal arts students, but liberal arts students showed more significant improvement in later academic years, reflecting the differing impacts of disciplinary environments on emotional development. Female students generally exhibited higher levels of anxiety and stress, particularly those in liberal arts, while female engineering students faced additional psychological burdens due to gender imbalance and biases. Anxiety and stress levels increased across all students as they advanced in their studies, correlating with academic and graduation pressures.

CONCLUSION

This article was based on the integration of psychometric methods and algorithm optimization techniques, exploring the differences in emotional expression among college students, providing new ideas for personalized mental health interventions for college students, enriching the theoretical basis of emotional expression research, and providing important references for education and mental health practice.

Modelling nonlinear moderation effects with local structural equation modelling (LSEM): A non-technical introduction

Understanding the differential strength of effects in the presence of a third variable, known as a moderation effect, is a common research goal in many psychological and behavioural science fields. If structural equation modelling is applied to test effects of interest, the investigation of differential strength of effects will typically ask how parameters of a latent variable model are influenced by categorical or continuous moderators, such as age, socio-economic status, personality traits, etc. Traditional approaches to continuous moderators in SEMs predominantly address linear moderation effects, risking the oversight of nonlinear effects. Moreover, some approaches have methodological limitations, for example, the need to categorise moderators or to pre-specify parametric forms of moderation. This tutorial introduces local structural equation modelling (LSEM) in a non-technical way. LSEM is a nonparametric approach that allows the analysis of nonlinear moderation effects without the above-mentioned limitations. Using an empirical dataset, we demonstrate the implementation of LSEM through the R-sirt package, emphasising its versatility in both exploratory analysis of nonlinear moderation without prior knowledge and confirmatory testing of hypothesised moderation functions. The tutorial also addresses common modelling issues and extends the discussion to different application scenarios, demonstrating its flexibility.

Psychometric properties of the SocioEmotional Skills Instrument for Teachers using network approach: English and Spanish version

The importance of socioemotional teaching skills has been highlighted for its link with better academic, social, emotional, and behavioral results of students, as well as for its contribution to the work wellbeing, mental health, and prosperity of teachers. However, there are few instruments that measure these skills in teachers in the context of their professional practice. The purpose of this research was to analyze the psychometric properties of the socioemotional Skills Instrument for Teachers (SEMS-IT). An instrumental design and a sample of 853 Chilean secondary school teachers were used. To evaluate the dimensional structure of the instrument, a portion of the sample (n = 468) underwent a network estimation method with exploratory graph analysis (EGA) using a Gaussian GLASSO model. Then, in order to confirm the structural consistency and stability of the items, the analysis was replicated in a second sample (n = 385), where these results were additionally contrasted with those of the confirmatory factor analysis (CFA). The EGA findings confirmed a structure of four dimensions and 19 items in total: (a) cognitive management of teacher emotion (four items), (b) teacher empathic concern (four items), (c) teacher-student relationship (four items), and (d) adverse classroom climate (seven items), with a 7-point Likert scale response format. The CFA showed good and acceptable fit indicators, X2 (171) = 354.546 (p < 0.001), Comparative Fit Index (CFI) = 0.971, Tucker-Lewis index (TLI) = 0.966, Root Mean Square Error of Approximation (RMSEA) = 0.061, and Standardized Root Mean Square Residual (SRMR) = 0.062. In conclusion, a tool for the assessment of teachers' socioemotional skills, valid for school-based educational research, is provided. Implications of the findings at the theoretical and practical levels are discussed, as well as limitations and future projections for future research.

A network approach to emotion regulation and symptom activation in depression and anxiety

Background

Emotions can be regulated through several regulatory strategies that are involved in the development of psychopathological symptoms. Despite the well-established association between psychopathology and emotion dysregulation, little is known about the relationship between individual symptoms of depression and anxiety and emotion regulation strategies (ERS), as well as between ERS themselves.

Method

We conducted a cross-sectional study and examined the interactions between six ERS (reappraisal, engagement, rumination, suppression, arousal control, and distraction) and assessed their distinctive association with the activation of specific symptoms of depression and anxiety in a community sample of 376 adults (80.4% female; Mage  = 32.70; SDage  = 11.80). The Regulation Emotion Systems Survey (RESS) was used to measure ERS. The Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder (GAD-7) were used to assess psychological symptoms. An exploratory graph analysis was performed to examine the structural properties of the network of interactions between these behaviors. Additionally, to test the association of ERS with the activation of the depression symptoms network, an expected symptoms activity (ESA) was conducted.

Results

Six communities were found that correspond to the six ERS. Rumination and suppression have a significant association with symptom activation (particularly low self-esteem), whereas reappraisal reduces symptomatic activation. The effect of arousal control, engagement, and distraction appears to depend on the remaining ERS rather than having much influence on their own.

Conclusion

This study provides insight into how ERS interact with each other and with individual symptoms of depression and anxiety. Understanding the effects of these interactions on symptom activation and comorbidity can improve our understanding of psychopathology.

How self-states help: Observing the embodiment of self-states through nonverbal behavior

The concept of self-states is a recurring theme in various psychotherapeutic and counseling methodologies. However, the predominantly unconscious nature of these self-states presents two challenges. Firstly, it renders the process of working with them susceptible to biases and therapeutic suggestions. Secondly, there is skepticism regarding the observability and differentiation of self-states beyond subjective experiences. In this study, we demonstrate the feasibility of eliciting self-states from clients and objectively distinguishing these evoked self-states through the lens of neutral observers. The self-state constellation method, utilized as an embodied approach, facilitated the activation of diverse self-states. External observers then assessed the nonverbal manifestations of affect along three primary dimensions: emotional valence, arousal, and dominance. Our findings indicate that external observers could reliably discern and differentiate individual self-states based on the bodily displayed valence and dominance. However, the ability to distinguish states based on displayed arousal was not evident. Importantly, this distinctiveness of various self-states was not limited to specific individuals but extended across the entire recording sample. Therefore, within the framework of the self-state constellation method, it is evident that individual self-states can be intentionally evoked, and these states can be objectively differentiated beyond the subjective experiences of the client.

Emotions and music through an innovative project during compulsory secondary education

This article presents the results and main conclusions of a quasi-experimental study after the implementation of an innovative project extended as a multi-year programme, called 'MusMotion', applied in compulsory secondary education, which is based on the relationship between music and emotions, as well as its effects on the academic performance of adolescents. The research analysed and tested an educational innovation project that improves students' academic performance, as well as the classroom climate between teachers and students (N = 444). A key strand of this research concerns the use of music to support students' emotional development and awareness. As we will explain, the results of this research have shown positive outcomes that have direct implications for pedagogy and classroom practice. The results confirm that there is a relationship between emotions and students' academic performance, and the innovative educational programme MusMotion can help to improve students' academic performance and the classroom climate by improving their state of mind. Educational systems, through the management of emotions via music, could help many children who today may have difficulty with their emotions.

The inner workings of anger: A network analysis of anger and emotion regulation

OBJECTIVE

This study aimed to investigate the interrelations between emotion regulation strategies and different types of anger using network analysis.

METHOD

Data were drawn from a cross-sectional sample of 538 adults (55% females; mean age = 39.8 years, SD = 12.3) seeking treatment for anger. Data were collected between March and November 2019 in Sweden. Participants completed measures of anger problems (anger expression, anger suppression, angry reactions, anger rumination, trait anger, hostility, physical aggression, and verbal aggression) and emotion regulation (cognitive reappraisal, expressive suppression, anger relaxation, and five mindfulness strategies). To determine whether distinct clusters of anger nodes would emerge, exploratory graph analysis was employed. Based on clustering of nodes, we estimated separate networks including all measures of emotion regulation.

RESULTS

Two clusters emerged: one consisting primarily of cognitive components of anger, and another of behavioral. Across networks, anger nodes were strongly interconnected, and anger rumination and anger suppression were especially influential. Several direct links were found between specific emotion regulation strategies and cognitive components of anger, whereas most strategies were only indirectly related to angry behavior. Cognitive reappraisal showed no direct link with any of the anger nodes.

CONCLUSIONS

Our findings reveal potential pathways by which different emotion regulation strategies may influence different types of anger, which could serve as therapeutic targets.

Aesthetic emotions are affected by context: a psychometric network analysis

Aesthetic emotions are defined as emotions arising when a person evaluates a stimulus for its aesthetic appeal. Whether these emotions are unique to aesthetic activities is debated. We address this debate by examining if recollections of different types of engaging activities entail different emotional profiles. A large sample of participants were asked to recall engaging aesthetic (N = 167), non-aesthetic (N = 160), or consumer (N = 172) activities. They rated the extent to which 75 candidate aesthetic emotions were evoked by these activities. We applied a computational psychometric network approach to represent and compare the space of these emotions across the three conditions. At the behavioral level, recalled aesthetic activities were rated as the least vivid but most intense compared to the two other conditions. At the network level, we found several quantitative differences across the three conditions, related to the typology, community (clusters) and core nodes (emotions) of these networks. Our results suggest that aesthetic and non-aesthetic activities evoke emotional spaces differently. Thus, we propose that aesthetic emotions are distributed differently in a multidimensional aesthetic space than for other engaging activities. Our results highlight the context-specificity of aesthetic emotions.

Probing neurodynamics of experienced emotions-a Hitchhiker's guide to film fMRI

Film functional magnetic resonance imaging (fMRI) has gained tremendous popularity in many areas of neuroscience. However, affective neuroscience remains somewhat behind in embracing this approach, even though films lend themselves to study how brain function gives rise to complex, dynamic and multivariate emotions. Here, we discuss the unique capabilities of film fMRI for emotion research, while providing a general guide of conducting such research. We first give a brief overview of emotion theories as these inform important design choices. Next, we discuss films as experimental paradigms for emotion elicitation and address the process of annotating them. We then situate film fMRI in the context of other fMRI approaches, and present an overview of results from extant studies so far with regard to advantages of film fMRI. We also give an overview of state-of-the-art analysis techniques including methods that probe neurodynamics. Finally, we convey limitations of using film fMRI to study emotion. In sum, this review offers a practitioners' guide to the emerging field of film fMRI and underscores how it can advance affective neuroscience.

Basic Emotions or Constructed Emotions: Insights From Taking an Evolutionary Perspective

The ongoing debate between basic emotion theories (BETs) and the theory of constructed emotion (TCE) hampers progress in the field of emotion research. Providing a new perspective, here we aim to bring the theories closer together by dissecting them according to Tinbergen's four questions to clarify a focus on their evolutionary basis. On the basis of our review of the literature, we conclude that whereas BETs focus on the evolution question of Tinbergen, the TCE is more concerned with the causation of emotion. On the survival value of emotions both theories largely agree: to provide the best reaction in specific situations. Evidence is converging on the evolutionary history of emotions but is still limited for both theories-research within both frameworks focuses heavily on the causation. We conclude that BETs and the TCE explain two different phenomena: emotion and feeling. Therefore, they seem irreconcilable but possibly supplementary for explaining and investigating the evolution of emotion-especially considering their similar answer to the question of survival value. Last, this article further highlights the importance of carefully describing what aspect of emotion is being discussed or studied. Only then can evidence be interpreted to converge toward explaining emotion.

Embedding Research on Emotion Duration in a Network Model

Contrary to early theorizing, emotions often last for longer periods of time. Variability in people's emotion duration contributes to psychopathologies. Therefore, emotion theories need to account for this variability. So far, reviews only list predictors of emotion duration without integrating them in a theoretical framework. Mechanisms explaining why these predictors relate to emotion duration remain unknown. I propose to embed research on emotion duration in a network model of emotions and illustrate the central ideas with simulations using a formal network model. In the network model, the components of an emotion have direct causal effects on each other. According to the model, emotions last longer (a) when the components are more strongly connected or (b) when the components have higher thresholds (i.e., they are more easily activated). High connectivity prolongs emotions because components are constantly reactivated. Higher thresholds prolong emotions because components are more easily reactivated even when connectivity is lower. Indirect evidence from research on emotion coherence and research on the relationship of predictors of emotion duration with components outside of emotional episodes supports the usefulness of the network model. I further argue and show in simulations that a common cause model, in which a latent emotion causes changes in emotion components, cannot account for research on emotion duration. Finally, I describe future directions for research on emotion duration and emotion dynamics from a network perspective.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42761-023-00203-3.

Influence of Stress and Emotions in the Learning Process: The Example of COVID-19 on University Students: A Narrative Review

Emotional instability and stress are the main disturbances that condition the learning process, affecting both teachers and students. The main objective of this review is to analyze the influence of stress and emotions (as part of stress) on the learning environment. Stress is a physiological mechanism that the organism develops to adapt and survive external and internal challenges. In this context, stress tends to be seen as a negative condition in the learning process when it is chronic. Extreme stress situations, such as the COVID-19 pandemic, can generate anxiety and frustration in students. However, other studies indicate that controlled stress can positively enhance the learning process. On the other hand, the quality and intensity of emotions resulting from stress can influence as well the learning process. Positive emotions are healthy and can promote optimal learning. Emotions lead to sentimental, cognitive, behavioral, and physiological changes, which will have a strong influence on intellectual performance. The activation of coping strategies constitutes a key mechanism for dealing positively with problems and challenges, generating positive emotions essential for the self-regulation of learning. In conclusion, correct management of emotions in stressful situations could promote effective learning through enhanced attention and capacity to solve problems.

Characterizing emotional eating: Ecological momentary assessment with person-specific modeling

Emotional eating is a topic of clinical importance, with links to weight regulation and wellness. However, issues of concept clarity and measurement can interfere with efforts to understand and intervene on emotional eating. One explanation for prior difficulties in defining emotional eating may be that this construct is not uniform across individuals. The current study critically examined emotional eating by combining ecological momentary assessment (EMA) with an idiographic analytic approach. The study examined the heterogeneity in the emotions and dysregulated eating behaviors often thought to underlie emotional eating, by establishing and comparing latent factor profiles across individuals. Ten community adults with overweight or obesity completed a 21-day EMA protocol, with 5 daily prompts to report on relevant emotions and eating behaviors. P-technique factor analysis was used to examine the data. Results suggested variability across individuals in the number of factors that emerged, the items that loaded on each factor, and the strength of loadings. Dysregulated eating was not found to covary with affective states strongly enough to produce a distinct "emotional eating" factor for any individual, nor did the correlations between factors suggest strong relationships between emotions and dysregulated eating for most participants, even in this sample with 90% of participants self-identifying as "emotional eaters." Findings are consistent with a growing body of literature questioning the validity of the "emotional eating" construct as currently defined and measured, and supports conceptualizing emotional eating as a locally heterogenous construct that varies between people. Combining EMA with an intra-individual modeling technique appears to be a promising approach for understanding emotional eating. Additional work with larger samples is needed to capture the full range in individual profiles.

Examining Secondary School Choice Processes as a Predictor of Adjustment After the School Transition

The secondary school transition is an important moment in adolescents' lives. Taking a prospective approach, the present study examined whether educational identity regarding a secondary school choice and own and parental expectations during the last year of primary school predicted post-transition school and psychological adjustment in Dutch adolescents (N = 314, M_age  = 11.58). Additionally, the study qualitatively examined the reasons adolescents gave for their school choice, and linked these reasons to exploration behavior and post-transition adjustment. Identity processes and expectations predicted adjustment. Adolescents mostly reported multiple reasons for their school choice, with educational, practical, and social aspects of secondary schools appearing most important. The number of reasons mentioned was associated with pre-transition exploration behavior.

Using network analysis to detect associations between suspected painful health conditions and behaviour in dogs

Pain associated with chronic health conditions in non-human animals is an important animal welfare issue. To identify animals in pain and develop an understanding of the mechanisms by which pain affects behaviour, it is therefore important to establish the direct behavioural effects of painful health conditions. We reanalyse data from a cross-sectional survey that considered the presence or absence of a painful condition in dogs and quantified their affective predispositions using the Positive and Negative Activation Scale (PANAS). By applying ideas from network theory, we conceptualise pain as a stressor that exerts direct effects on a network of interacting behavioural variables, and subsequently estimated a network model of conditional dependence relations. Painful health conditions were positively conditionally associated with age (posterior mean partial correlation, ρ = 0.34; standard deviation [SD]=0.05), and negatively conditionally associated with the item 'your dog is full of energy' (ρ = -0.14; SD=0.06). In turn, the energy item was conditionally associated with other PANAS items which were marginally associated with pain, such as items representing ease of excitability and persistence in play. This suggests these marginal effects might be indirectly mediated via the energy item. Further, utilising the posterior predictive distribution we estimated that the median conditional probability (95% credible interval) of a painful health condition given an answer of 'strongly agree' on the energy item was 0.08 (0.05, 0.11), which increased to 0.32 (0.09, 0.58), given a response of 'strongly disagree'. This provides a potentially clinically useful interpretation of the conditional dependencies detected in the network.

Trust in scientists, risk perception, conspiratorial beliefs, and unrealistic optimism: A network approach to investigating the psychological underpinnings of COVID-19 vaccination intentions