Trait Model Research Articles

How Important Is Budding Speciation for Comparative Studies?

The acknowledgment of evolutionary dependence among species has fundamentally changed how we ask biological questions. Phylogenetic models became the standard approach for studies with 3 or more lineages, in particular those using extant species. Most phylogenetic comparative methods (PCMs) translate relatedness into covariance, meaning that evolutionary changes before lineages split should be interpreted together whereas after the split lineages are expected to change independently. This clever realization has shaped decades of research. Here, we discuss one element of the comparative method often ignored or assumed as unimportant: if nodes of a phylogeny represent the dissolution of the ancestral lineage into two new ones or if the ancestral lineage can survive speciation events (i.e., budding). Budding speciation is often reported in paleontological studies, due to the nature of the evidence for budding in the fossil record, but it is surprisingly absent in comparative methods. Here, we show that many PCMs assume that divergence happens as a symmetric split, even if these methods do not explicitly mention this assumption. We discuss the properties of trait evolution models for continuous and discrete traits and their adequacy under a scenario of budding speciation. We discuss the effects of budding speciation under a series of plausible evolutionary scenarios and show when and how these can influence our estimates. We also propose that long-lived lineages that have survived through a series of budding speciation events and given birth to multiple new lineages can produce evolutionary patterns that challenge our intuition about the most parsimonious history of trait changes in a clade. We hope our discussion can help bridge comparative approaches in paleontology and neontology as well as foster awareness about the assumptions we make when we use phylogenetic trees.

Self- and Team-Efficacy in Military Trainees: Development of Two Novel Military Trainee-Appropriate Assessments

Many currently published studies examining elements of self- and team-efficacy in military personnel have not utilized military-specific assessments, thereby limiting the generalizability of their findings to the broader military population. The present study evaluates the factor structure and performance correlates of the Trainee Self-Efficacy Scale (TSES) and the Team-Efficacy and Training Climate Inventory (TETCI) in two samples of military trainees. Exploratory factor analysis was conducted in sample 1 (N = 481). Confirmatory factor analysis, measure validity, and structure validation were conducted in sample 2 (N = 442). Factor analysis results revealed the TSES was best represented by a three-factor correlated traits model including constructs related to performance confidence, performance uncertainty, and performance optimism. The TETCI was best represented by a two-factor correlated traits model including constructs related to team member efficacy and leadership climate. TSES subscales exhibited small or moderate correlations with assessments of soldier performance (e.g., physical fitness, land navigation, and confidence in rifle marksmanship) in the expected directions. The TETCI subscales exhibited small positive correlations with an assessment of team performance. Findings indicate that the TSES and TETCI are parsimonious measures (10 and 7-items, respectively) that have the potential to be useful tools for the continued assessment of military trainees.

The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis.

Anxiety and depression are among the greatest contributors to the global burden of diseases. The close associations of personality traits with anxiety and depression have been widely described. However, the common practice of sum scores in previous studies limits the understanding of the fine-grained connections between different personality traits and anxiety and depression symptoms and cannot explore and compare the risk or protective effects of personality traits on anxiety and depression symptoms. We aimed to determine the fine-grained connections between different personality traits and anxiety and depression symptoms and identify the detrimental or protective effects of different personality traits on anxiety and depression symptoms. A total of 536 college students from China were recruited online, and the average age was 19.98 ± 1.11. The Chinese version of the Ten-Item Personality Inventory, Generalized Anxiety Disorder-7, and Patient Health Questionnaire-9 was used to investigate the personality traits and symptoms of anxiety and depression of participants after they understood the purpose and filling method of the survey and signed the informed consent. The demographic characteristics were summarized, and the scale scores were calculated. The network model of personality traits and symptoms of anxiety and depression was constructed, and bridge expected influence (BEI) was measured to evaluate the effect of personality traits on anxiety and depression. The edge accuracy and BEI stability were estimated, and the BEI difference and the edge weight difference were tested. In the network, 29 edges (indicating partial correlations between variables) bridged the personality community and the anxiety and depression community, among which the strongest correlations were extraversion-fatigue, agreeableness-suicidal ideation, conscientiousness-uncontrollable worry, neuroticism-excessive worry, neuroticism-irritability, and openness-feelings of worthlessness. Neuroticism had the highest positive BEI value (0.32), agreeableness had the highest negative BEI value (-0.27), and the BEI values of neuroticism and agreeableness were significantly different from those of most other nodes (p < 0.05). There are intricate correlations between personality traits and the symptoms of anxiety and depression in college students. Neuroticism was identified as the most crucial risk trait for depression and anxiety symptoms, while agreeableness was the most central protective trait.

Leaders Appear Agreeable, Extraverted, and Honest-Humble: Meta-Analysis and Reputational Trait Model

Leaders Appear Agreeable, Extraverted, and Honest-Humble: Meta-Analysis and Reputational Trait Model

Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach

ABSTRACTNarcissism is a multifaceted construct often linked to pathological conditions whose neural correlates are still poorly understood. Previous studies have reported inconsistent findings related to the neural underpinnings of narcissism, probably due to methodological limitations such as the low number of participants or the use of mass univariate methods. The present study aimed to overcome the previous methodological limitations and to build a predictive model of narcissistic traits based on neural and psychological features. In this respect, two machine learning-based methods (Kernel Ridge Regression and Support Vector Regression) were used to predict narcissistic traits from brain structural organization and from other relevant normal and abnormal personality features. Results showed that a circuit including the lateral and middle frontal gyri, the angular gyrus, Rolandic operculum, and Heschl’s gyrus successfully predicted narcissistic personality traits (p < 0.003). Moreover, narcissistic traits were predicted by normal (openness, agreeableness, conscientiousness) and abnormal (borderline, antisocial, insecure, addicted, negativistic, machiavellianism) personality traits. This study is the first to predict narcissistic personality traits via a supervised machine learning approach. As such, these results may expand the possibility of deriving personality traits from neural and psychological features.

Diversity of hazelnut varieties and changes in plant development during introduction in the semi-arid zone

Global climate change provide the emergence of new opportunities for the introduction of new crops into horticultural production in the areas of insufficient precipitation. In addition to the economic aspect, it is also of interest to the biologists of the development of this plant in a qualitatively new environment.The paper considers the variability of the main traits of plant morphometry, yield for four varieties of hazelnuts in order to identify the most promising forms for cultivating in the northern part of the Steppe of Ukraine characterized by an insufficient precipitation and harsh winters. Recent milder winter conditions and a certain balance in summer droughts have made the required horticultural production possible, thereby increasing the production of hazelnuts and addressing the dietary problems of people in terms of supply of necessary vitamins and micronutrient element from hazelnuts. Promising varieties for the production plantations have been specified, the mechanisms for the yield formation have been studied. Key traits of morphometry have been identified that condition the success of a variety under insufficient humidity. These were such traits as crown volume, leaf surface area, shell thickness, average weight of one nut, weight of dry nuts, yield, kernel yield. It has been established that the yield formation on account of large, well-shaped nuts is best in terms of yield. Some aspects of yield formation and the possibility of combining different varieties, especially when more intensive growing methods are applied, are of additional interest. High variability significantly prevents the modeling of traits, for example, such as yield per tree, from being significant in terms of the formation of high yield. Semi-intensive pruning of hazelnut bushes shows its suitability for use in modern garden plantings. Variety Barselonskiy showed extremely high variability for many key parameters, which may indicate insufficient stability of this variety from a genetic point of view and the presence of a fairly significant number of hidden biotypes, which is additionally negative for cultivation in modern semi-intensive and intensive technologies. Climate change makes it possible to continue to significantly expand the area under hazelnuts due to the previously considered unfavourable southern subzones of the Forest-Steppe and the Steppe zone of Ukraine. Such new and previously unnoticed effects have been noted as fruiting in the first year in production crops, the formation of up to 5–6 inflorescences for each nut-bearing branch in the second or third year. For further investigations, it is planned to analyze the nutritional qualities of the obtained products, in terms of the composition by microelements and the presence of biologically-active substances, to trace the dynamics of the accumulation of heavy metals and the potentially associated risks.

Alternative Confirmatory Factor Analytic Models for Examining Preservice Teachers' Non-Cognitive Skills

This study provides a comparative analysis of the inferences that can be reached about preservice teachers' emotional awareness and personality traits when several alternative factor analytic models are tested simultaneously. An empirical illustration is provided using two datasets collected for a research study aiming to profile the social-emotional behavior repertoire of preservice teachers. Four alternative factor analytic models were considered for both datasets: the unidimensional model, the correlated model, the higher- (or second-) order model, and the bifactor model. Results indicate that the higher-order factor model for emotional awareness (n = 670) and the bifactor model for personality traits (n = 670) were the preferred models that better represent the underlying factor structures. Multidimensionality and practical decisions concerning score reporting are discussed.

Self-perceived employability of undergraduate students during the COVID-19 pandemic: the role of traits, knowledge sharing and trust

PurposeThis study aims to explore the impact of personality traits on self-perceived employability (SPE) and test if the associations are mediated by knowledge sharing (KS) through online learning during the COVID-19 pandemic. In addition, the moderation effect of trust in the relationship between KS and SPE was examined.Design/methodology/approachBased on Big Five Personality Trait Model and KS model, the authors proposed and tested the research framework with 341 samples collected from university students who experienced online learning during the social distancing caused by the COVID-19 pandemic. The measurement model was assessed to confirm the validity and reliability of the structure, then hypothesis testing was performed with the partial least square-structural equational model (PLS-SEM).FindingsThe results showed that extraversion and agreeableness positively affected SPE through KS. Moreover, trust played a moderating role on the effect of KS on SPE.Practical implicationsBased on the research findings, the authors suggest that academic institutions, especially universities, should provide opportunities for students to explore their personality traits. Second, the university should organize specific activities that promote knowledge sharing among students. Third, the university should encourage the creation of platforms aimed at sharing knowledge in a reliable way that increases trust in responsiveness.Originality/valueThe present study contributes to the literature on SPE by presenting immediate empirical evidence on the relationship between personality traits and SPE, along with mediating and moderating effects. These findings provide meaningful implications for higher education institutions that implement online learning during challenging circumstances.

On definition and description in psychopathology: Reply to Widiger et al. (2023).

We reply to Wright et al.'s (2023) commentary and suggestion that personality trait models would be the preferred way to reconfigure the personality disorders (PDs). Though we agree that personality trait models are powerful descriptive tools, we highlight that they lack definitional or explanatory power, and that is why they have not been able to define or distinguish what PDs are (Hopwood, 2018; Mõttus et al., 2020; Pincus, 2011). Scientific models must do more than describe; they must define. This is why we propose a specific interpersonal model, contemporary integrative interpersonal theory, and why a generic interpersonal model has been formally adopted in psychiatric classification (e.g., International Classification of Diseases; 11th ed.; World Health Organization, 2019) but traits remain optional adjunct descriptors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A systematic mapping study on group work research in computing education projects

Context:For developing students’ group- and teamwork skills needed in the team-oriented work environments of the software industry, the role of project-based learning is considered central. Yet there does not appear to be a proper mapping of the current group work research in the computer science project education literature. Thus, the current state of group work research in the research area is somewhat unknown. Objective:This study aims to form an overview of how research has addressed students’ group work in the field of computer science (CS) and software engineering (SE) to identify research gaps as well as suitable topics for more detailed literature reviews. Methods:A systematic mapping study was used to investigate how group work in tertiary education has been undertaken in the literature during the past decade. Results:Based on the selected papers, the most investigated group work areas were related to the assessment of groups, group formation, communication, and cooperation. The research appeared to be quite narrowly focused on a few areas. Most of the papers were experience or evaluation research. A case study using interviews or questionnaires to gather data from a single course was the most representative type of study. The papers were mainly published in scientific conferences. The use of theoretical frameworks was limited, with a focus on a few established frameworks. Tuckman’s group development theory was the predominant framework, while other commonly used concepts and theories include social loafing, Kolb’s learning style theory, and the Big Five personality traits model. Conclusion:Out of 7515 papers screened, 225 were deemed eligible and analyzed. We conclude a need for more focused group work research in CS/SE student projects, in which education is inspected from particular perspectives. This would create identifiable lines of research and structure the research area. Relatedly, we suggest that the underused theoretical frameworks can inspire important research: group interventions would benefit from a socially shared regulated learning perspective, explicit use of justice theories would improve theoretical understandings of group behavior, and transactional distance would help analyze how students adopt a software process. Moreover, the research area could be precipitated by novel theoretical perspectives. For practitioners, those implementing a group project course can benefit from a large amount of literature on assessment and group formation, which are issues on which the teacher must take a position. We also include a lessons-learned summary for teachers. Generally, the present results outlining the field in a structured way can facilitate research-based teaching.

Evidence that specific personal relationships evoke maladaptive personality expression

ABSTRACT Introduction This research applied relational regulation theory (RRT) to maladaptive personality as identified in the DSM-5, dimension trait model. RRT describes how individual social network members help people regulate their own affect, thought and action. Previous research found that people expressed different levels of normal personality dimensions and affect depending upon the network members that people were with or thinking about. Methods College students (N = 719) rated their expression of maladaptive dimensions and affect when with important network members, as well as the interpersonal characteristics of network members. Results People’s maladaptive personality expression was strongly consistent across network members (recipient effects). Yet, personality expression also varied strongly depending upon which network member the recipient was with or thinking about (dyadic effects). PID-5 negative affectivity and PANAS negative affect more strongly reflected dyads than recipients. Antagonism and disinhibition more strongly reflected recipients than dyads. Network members who evoked maladaptive expressions were seen by recipients as unsupportive, unresponsive, as evoking conflict, attachment avoidance and attachment anxiety. However, the interpersonal constructs were mostly redundant in predicting maladaptive personality. Findings were replicated across random subsamples and gender. Conclusion The findings provide evidence that important personal relationships can evoke the expression of maladaptive personality.

Africa as an evolutionary arena for large fruits.

Strong paleoclimatic change and few Late Quaternary megafauna extinctions make mainland Africa unique among continents. Here, we hypothesize that, compared with elsewhere, these conditions created the ecological opportunity for the macroevolution and geographic distribution of large fruits. We assembled global phylogenetic, distribution and fruit size data for palms (Arecaceae), a pantropical, vertebrate-dispersed family with > 2600 species, and integrated these with data on extinction-driven body size reduction in mammalian frugivore assemblages since the Late Quaternary. We applied evolutionary trait, linear and null models to identify the selective pressures that have shaped fruit sizes. We show that African palm lineages have evolved towards larger fruit sizes and exhibited faster trait evolutionary rates than lineages elsewhere. Furthermore, the global distribution of the largest palm fruits across species assemblages was explained by occurrence in Africa, especially under low canopies, and extant megafauna, but not by mammalian downsizing. These patterns strongly deviated from expectations under a null model of stochastic (Brownian motion) evolution. Our results suggest that Africa provided a distinct evolutionary arena for palm fruit size evolution. We argue that megafaunal abundance and the expansion of savanna habitat since the Miocene provided selective advantages for the persistence of African plants with large fruits.

Evolutionary lineage explains trait variation among 75 coexisting grass species.

Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C3 vs C4 plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity. We measured 11 structural and physiological traits insitu from 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species. Critically, we found evidence that grass traits varied among lineages, including independent origins of C4 photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics. Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C4 species. These results indicate that further assessment of lineage-based differences at other sites and across other grass species distributions may improve representation of C4 species in trait comparison analyses and modeling investigations.

Range contractions and reduced body mass predicted for endemic skinks of the Cameroon Volcanic Line with future warming

AbstractAimThe vulnerability of montane species to environmental change has been increasingly recognized in recent years. However, most of these species are regionally endemic with restricted distributions, limiting dispersal necessary for avoiding extinction. The outcome of threats posed for montane lizards is further complicated in species exhibiting mass–temperature relationships where body size increases with cooling temperatures, and thus with altitude, causing intraspecific physiological and behavioural differences. We aimed to identify areas suitable for montane endemic skinks of the Cameroon Volcanic Line (CVL) under current and future climates to reveal patterns of persistence and vulnerability based on an intersection of climate and body mass.LocationCameroon Volcanic LineMethodsWe recorded occurrences and measured body mass in the field for two CVL‐endemic skink species. We supplemented occurrences with online repository records. We projected current and future habitat suitability in the region by implementing bioclimatic species distribution models‐based on occurrences. We tested for elevational variations in body mass, and integrated both occurrence and body mass information in a trait‐based model to estimate current and future body mass.ResultsProjected currently suitable habitat for both species was limited to higher elevation regions, which are inhabited by numerous other threatened herpetofauna. We additionally detected Bergmann clines in body mass for both species. Given this variation in body mass, trait model projections covered slightly larger geographical ranges than bioclimatic estimates. Under future warming, both models project substantial contractions in suitable areas, potentially constraining species to mountain tops. Through the trait‐based approach, we further detected potential warming‐induced body mass reductions in projected suitable areas.Main ConclusionsWe demonstrate how combining occurrence records with species trait information in ecological modelling can reveal complementary trends for comprehensive warming impact assessments. Overall, challenges toward the persistence of CVL‐endemic skinks should prompt urgent responses in national conservation management and local community engagement.

Examining procrastination using the DSM-5 personality trait model: Disinhibition as a core personality trait

Examining procrastination using the DSM-5 personality trait model: Disinhibition as a core personality trait

Testing associations between human anxiety and genes previously implicated by mouse anxiety models.

Anxiety disorders are common and can be debilitating, with effective treatments remaining hampered by an incomplete understanding of the underlying genetic etiology. Improvements have been made in understanding the genetic influences on mouse behavioral models of anxiety, yet it is unclear the extent to which genes identified in these experimental systems contribute to genetic variation in human anxiety phenotypes. Leveraging new and existing large-scale human genome-wide association studies, we tested whether sets of genes previously identified in mouse anxiety-like behavior studies contribute to a range of human anxiety disorders. When tested as individual genes, 13 mouse-identified genes were associated with human anxiety phenotypes, suggesting an overlap of individual genes contributing to both mouse models of anxiety-like behaviors and human anxiety traits. When genes were tested as sets, we did identify 14 significant associations between mouse gene sets and human anxiety, but the majority of gene sets showed no significant association with human anxiety phenotypes. These few significant associations indicate a need to identify and develop more translatable mouse models by identifying sets of genes that "match" between model systems and specific human phenotypes of interest. We suggest that continuing to develop improved behavioral paradigms and finer-scale experimental data, for instance from individual neuronal subtypes or cell-type-specific expression data, is likely to improve our understanding of the genetic etiology and underlying functional changes in anxiety disorders.

Assessment of five factor model of personality traits of senior high school students: Basis for faculty development program

Assessment of five factor model of personality traits of senior high school students: Basis for faculty development program

Personality Detector

Abstract: Personality detection has become an important area of research due to its potential applications in various fields such as marketing, psychology, and human resource management. In this paper, we present a personality detector that utilizes the Big Five personality traits model to analyze and predict the personality traits of individuals. The Big Five personality traits model is widely used in personality psychology, and it consists of five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. Our system utilizes a machine learning algorithm that analyzes various features such as text, social media posts, and speech to predict an individual's personality traits. The front-end of the system is developed using Python and Django, making it easy to use and accessible to anyone with an internet connection. We evaluated our system using a dataset of 1000 individuals and achieved an accuracy of 85% in predicting their personality traits

Where the Head Meets the Heart: ‘Enlightened’ Compassion Lies Between Big Five Openness/Intellect and Agreeableness

Enlightened compassion is a morally significant personality trait describing the tendency to show regard for others in an open-minded (vs. rigid or parochial) manner. We examine this trait through a “bottom-up” lens, asking: where is enlightened compassion located within the Big Five (B5) taxonomy? Across three studies comprising seven samples (total N = 2,522), we measure enlightened compassion as an interstitial facet lying between the Compassion aspect of B5 Agreeableness and the Openness aspect of B5 Openness/Intellect. The Enlightened Compassion Scale (EC Scale) has solid structural and content validity, converging strongly with Compassion and Openness (Study 1). Consistent with the bandwidth-fidelity trade-off in hierarchical models of personality traits, enlightened compassion demonstrates incremental validity over-and-above these B5 aspects when predicting theoretically relevant traits (e.g., moral imagination and moral expansiveness; Study 2) and behaviour (expansive charitable donation; Study 3). By locating enlightened compassion and its correlates within the organising framework of the B5, our work serves to deepen and integrate accumulated knowledge on this morally salient feature of personality.

Stand-Level Biomass and Leaf Trait Models for Young Naturally Regenerated Forests of European Hornbeam

European hornbeam (Carpinus betulus L.) is a tree species widely distributed in Europe and the Asian part of the Near East. However, since European hornbeam is not very attractive for commercial purposes, scientific interest in this species has been rather sparse. Our study focused on dense young (up to 10 years old) European hornbeam stands originating from natural regeneration from seeds in Slovakia because in future the importance of this species may increase due to the climate change. We combined previously constructed tree-level biomass models, data on basic leaf traits, i.e., weight and area, and measurements from thirty plots located at ten different sites across Slovakia to construct stand-level allometric relations of the biomass stock in tree components, i.e., leaves, branches, bark, stem under bark and roots, to mean stand diameter at stem base, i.e., at the ground level. Moreover, we calculated and modelled leaf characteristics, namely the specific leaf area (SLA), leaf area ratio (LAR) and leaf area index (LAI), at a stand level. The total tree biomass stock including all tree components ranged between 0.75 and 13.63 kg per m2, out of which the biomass of stem with bark was from 0.31 to 8.46 kg per m2. The biomass models showed that the contribution of roots (omitting those with a diameter under 2 mm) decreased with the increasing mean stand diameter at stem base, whereas the opposite pattern was observed for branches and stem biomass. Further, we found that the mean stand diameter at stem base was a good predictor of both LAR and LAI. The results indicated the high photosynthetic efficiency of European hornbeam leaves per one-sided surface leaf area. Moreover, the growth efficiency (GE), expressed as the biomass increment of woody parts per leaf area unit, of young European hornbeam trees was high. The models proved a close positive linear correlation between LAI and stand biomass stock that may be used for estimating the biomass in young stands from LAI that can be measured using non-destructive terrestrial or aerial methods. The results further indicated that young stands may sequester a non-negligible quantity of carbon; therefore, they should not be omitted from local or country-wide estimates of carbon stocks in forest vegetation.