Personality Features Research Articles

Nonacademic predictors of China medical licensing examination

BackgroundNational Medical Licensing Examination (NMLE) is the entrance exam for medical practice in China, and its general medical knowledge test (GMKT) evaluates abilities of medical students to comprehensively apply medical knowledge to clinical practice. This study aimed to identify nonacademic predictors of GMKT performance, which would benefit medical schools in designing appropriate strategies and techniques to facilitate the transition from medical students to qualified medical practitioners.MethodsIn 1202 medical students, we conducted the deletion-substitution-addition (DSA) and structural equation model (SEM) analyses to identify nonacademic predictors of GMKT performance from 98 candidate variables including early life events, physical conditions, psychological and personality assessments, cognitive abilities, and socioeconomic conditions. The candidate variables were assessed using psychometrically or cognitively validated and accepted instruments.ResultsWe identified seven nonacademic predictors for GMKT performance. Body mass index (BMI) and working memory reaction time showed direct negative effects on GMKT performance. Psychological and personality features (conscientiousness, state anxiety, and openness to experience) indirectly affected GMKT performance via BMI, while socioeconomic conditions (father’s education and mother’s occupation) indirectly affected GMKT performance by influencing psychological and personality features and further BMI.ConclusionThe identified nonacademic predictors for GMKT performance and their pathways may be useful for improving medical education by strengthening favorable and weakening, rectifying, or compensating unfavorable factors that are modifiable.

Временная перспектива личности как ресурс преодоления кризиса идентичности на различных этапах жизнеосуществления

<p style="text-align: justify;"><strong>Objective. </strong>Investigating the role of personality's time perspective in overcoming the identity crisis and determining its potential as a resource of personal growth at different stages of life realization. <br><strong>Background. </strong>The growth of identity crisis manifestations in modern conditions determines the necessity to search for new directions of psychological work on its prevention and effective resolution. The available theoretical data on the presence of interrelation between temporal and identification characteristics allows to consider the content features of personality's time perspective as a resource for overcoming the identity crisis. <br><strong>Study design. </strong>A set of diagnostic techniques aimed at studying the features of a personality's time perspective and the specifics of the manifestations of experiencing identity crises allowed us to collect data on samples formed in accordance with age periods. The primary data were subjected to a comparative analysis of the average values for the studied characteristics and a comparison of the features of the correlation relationships between the indicators of the time perspective and the identity crisis. Later, using the regression analysis of the analysis, the assumption was confirmed about the influence of time perspective indicators on the level of experiencing an identity crisis in the selected age groups. Also, using regression analysis, the hypothesis was tested that the variability of the time perspective in different age groups is conditioned by indicators of stress in crisis areas of life realization. <br><strong>Participants. </strong>The study involved 139 people aged 16 to 55 years. The total sample was divided into groups according to age periods: older adolescence (15-17 years, 38 people), adolescence (18-22 years, 47 people), early adulthood (23-29 years, 26 people), maturity/late adulthood (30-55 years, 28 people). All groups were equalized by gender. <br><strong>Measurements. </strong>Zimbardo's ZTPI time perspective methodology (modified by A. Syrtsova, E.T. Sokolova, O.V. Mitina); “Crisis Identity Questionnaire” by N.V. Dmitrieva and N.A. Samoilik; questionnaire of crisis events and experiences by V.R. Manukyan; methodology for the study of professional identity and personal identity by L.B. Schneider. The methods of statistical analysis (correlation analysis, Mann-Whitney U Test, Kruskal–Wallis test, regression analysis) were used in the processing of the obtained data. <br><strong>Results. </strong>Belief in a just world increases political trust; belief in a dangerous world reduces it. Political trust positively predicts readiness to participate in various forms of normative political activity. The presence of cross-cultural differences in the characteristics of the model between the Russian and Ukrainian samples is established. <br><strong>Conclusions. </strong>Content characteristics of the personality's time perspective are an important potential resource for overcoming the identity crisis. It has selective significance at different stages of life realization determining the age-specific features of a possible “therapeutic target” within the framework of psychological influence.</p>

Emerging Borderline Personality Features, Attachment Representations and Behavioral Dysregulation in School-Age Children

Emerging Borderline Personality Features, Attachment Representations and Behavioral Dysregulation in School-Age Children

The incremental validity of level of personality functioning over borderline personality features in associations with early adolescent social reward processing.

More work is needed to establish the validity of the Alternative Model of Personality Disorders (AMPD) in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Acceptance of the AMPD as the primary model of personality disorder requires identifying neurocognitive validators of AMPD-defined personality functioning and demonstrating superiority of the AMPD over the traditional categorical model of personality disorder. It is also important to establish the utility of the AMPD in a developmental context given evidence that personality disorder emerges in adolescence. We assessed the incremental validity of AMPD-defined level of personality functioning (LPF) versus borderline personality features (BPF) in explaining alterations in neural processing of social acceptance feedback in early adolescent girls. One hundred nine girls (Mage= 12.21, SD=1.21; N= 79 with a psychiatric history) completed a computerized peer interaction task to elicit neural response to social acceptance feedback via electroencephalogram (EEG). Subjects or caregivers reported adolescent psychopathology. In hierarchical regressions controlling for neural response to social rejection and internalizing and externalizing symptoms, LPF incremented BPF and all other covariates in predicting response to social acceptance, but BPF did not. Higher LPF impairment was associated with enhanced reactivity to social acceptance (St.b =0.274, p=0.018). LPF appears to provide additional information about neural response to social reward in early adolescence beyond that provided by borderline personality features. These findings add to an emerging literature demonstrating the validity and superiority of the AMPD and help build the rationale for moving toward the AMPD as the primary model of personality disorder classification.

A novel framework for entertainment robots in personalized elderly care using adaptive emotional resonance technologies

The aging population suffers from some difficult aspects, such as loneliness, dementia, and lack of meaning, which diminish their enjoyment of life. This work presents a novel model using robotics and artificial intelligence to create entertainment robots that can adapt their interaction based on the elderly’s emotion. The model is implemented through the use of the multimodal emotion recognition technology that holds the facial expression, voice tone, physiological expressions, and body postures. Supported by the emotional resonance algorithm and personalization features, these robots can deliver emotional resonance that corresponds to the user’s mood. With time, this model may learn and provide better feedback. Ethical factors are also taken into account. The robot handles multimedia content, natural language processing, and gentle movements that enhance interaction. The trial involved 20 elderly users, which showed effective outcomes of mood and engagement. Standardized psychological assessments, such as the Geriatric Depression Scale (GDS) and the Quality of Life in Alzheimer’s Disease (QOL-AD) scale, revealed that participants exhibited a 2.1-point decrease in GDS scores, indicating a reduction in depressive symptoms, and a 3.8-point increase in QOL-AD scores. This framework, is thus, a promising tool in transforming elderly care

Personalized games for computer science education in higher education: the effect of personalization feature on students’ engagement and flow state

Personalized games for computer science education in higher education: the effect of personalization feature on students’ engagement and flow state

Коммуникативный паспорт современного мигранта из Средней Азии

The study is devoted to understanding the communicative behavior of migrant workers from Uzbekistan, Tajikistan, and Kyrgyzstan who come to the Russian Federation for the purpose of employment. The study is based on the hypothesis that the dominant feature of their communicative behavior is bilingualism, therefore, the concept of "bilingual communicative behavior" of a person is introduced. It is proved that there are different types of bilingualism, among which the bilingualism of migrant workers seems to be poorly studied. In addition, there is no doubt about the proximity of bilingualism and diglossia. However, diglossia, unlike bilingualism, is characteristic of certain social relationships, and bilingualism is a feature of an individual linguistic personality. It has been established that it is bilingualism, or rather, the degree of proficiency in different languages, one of which is native and the second is acquired, that affects the socialization of migrants in the Russian Federation. The proof of this is the analysis of the communicative behavior of migrants in the everyday and institutional spheres of communication. As a result of the observations, it was found that the behavior patterns of people coming to the Russian Federation "for work" have similarities related to their nationality, level of education, spheres of communication, belonging to the post-Soviet space. The most significant is the institutional sphere of communication, which highlights with the greatest clarity the features of the bilingual communicative behavior of migrants from Central Asia, which allow us to talk about the concept of a "communicative migrant passport".

Изучение мотивационной сферы личности и психоэмоциональных особенностей у пациентов с наркологическими расстройствами на различных этапах лечебно-реабилитационного процесса (Часть 2)

<p style="text-align: justify;">The aim of the study was to analyze dynamic changes in the motivational sphere of personality and psychoemotional features of patients with drug addiction disorders at different stages of the treatment and rehabilitation process. The study involved 226 patients: 163 men (72.1%) and 63 women (27.9%) with narcological disorders. The following scales were used: the scale of stages of readiness for change and aspiration to treatment (Socrates), the scale of depression, anxiety and stress (DASS-21) and the scale of general self-efficacy (GSE). During the stabilising phase of therapy: 1) women showed significantly higher scores on the Socrates scale total score (p≤0.001), the Ambivalence subscale (p≤0.001) and the Action subscale (p≤0.05); 2) inverse correlations were found between the result on the Action subscale (Socrates) and signs of depression (r=-0.350, p≤0.05), anxiety (r=-0.452, p≤0.01) and stress (r=-0410, p≤0.01) (DASS-21). The results of the psychoemotional state revealed that patients with signs of stress were significantly more likely to undergo medical rehabilitation treatment and less likely to be discharged early, which allows the results to be used in targeted medical rehabilitation programmes.</p>

Automating Personal Budget Management with Firebase and Analytics

Managing personal finances efficiently is a critical aspect of modern living, yet many individuals struggle to track expenses, save effectively, and make informed financial decisions. This project, Automating Personal Budget Management with Firebase and Analytics, addresses these challenges by providing a comprehensive digital platform that simplifies and enhances financial management. The system leverages Firebase for seamless user authentication, real-time data storage, and synchronization, ensuring a secure and responsive experience. Users can register, log in, and access personalized features to track their income, expenses, and savings. The platform includes modules for adding, viewing, and categorizing expenses, as well as setting financial goals. By integrating analytics, the platform offers insightful visualizations and reports, empowering users with actionable data on spending patterns, budget allocations, and savings progress. These insights help users make informed decisions to optimize their financial health. This solution stands out for its scalability, intuitive design, and use of modern technologies like Firebase and analytical tools, making it a valuable tool for individuals seeking to automate and streamline their personal budget management.

Self-Transcendence as a Risk and Resilience Factor in Individuals at Clinical High Risk for Psychosis.

Self-transcendence is a personality feature and psychological resource that involves feelings of connectedness with the universe, all of humanity, and the individual self. Self-transcendence has been positively associated with both positive psychotic symptoms and clinical high risk for developing psychosis status, but studies reporting these findings focus solely on the connectedness-with-universe aspect of self-transcendence. The broader self-transcendence literature, which also includes connection with humanity and oneself, robustly supports self-transcendence as an indicator of well-being. Given this discrepancy, we sought to understand whether self-transcendence should be considered a risk or resilience factor for youth at clinical high risk. We operationalised self-transcendence using two more holistic measures novel to the clinical high risk population. Clinical high risk participants (n = 42) and healthy controls (n = 44) completed the Adult Self-Transcendence Inventory and participated in narrative life story interviews which were coded for self-transcendence themes. Clinical high risk individuals scored lower than healthy controls on measures of self-transcendence, functioning, and life satisfaction. However, there were no group differences in the relationships between self-transcendence and measures of well-being. Our findings suggest self-transcendence is a part of healthy personality development that may be impacted in clinical high risk individuals yet may still function as a psychological resource for this population, pointing toward new avenues for intervention in clinical high risk and other mental health populations.

Disentangling degree and tie strength heterogeneity in egocentric social networks

The structure of personal networks reflects how we organise and maintain social relationships. The distribution of tie strengths in personal networks is heterogeneous, with a few close, emotionally intense relationships and a larger number of weaker ties. Recent results indicate this feature is universal across communication channels. Within this general pattern, there is a substantial and persistent inter-individual variation that is also similarly distributed among channels. The reason for the observed universality is yet unclear—one possibility is that people’s traits determine their personal network features on any channel. To address this hypothesis, we need to compare an individual’s personal networks across channels, which is a non-trivial task: while we are interested in measuring the differences in tie strength heterogeneity, personal network size is also expected to vary a lot across channels. Therefore, for any measure that compares personal networks, one needs to understand the sensitivity with respect to network size. Here, we study different measures of personal network similarity and show that a recently introduced alter-preferentiality parameter and the Gini coefficient are equally suitable measures for tie strength heterogeneity, as they are fairly insensitive to differences in network size. With these measures, we show that the earlier observed individual-level persistence of personal network structure cannot be attributed to network size stability alone, but that the tie strength heterogeneity is persistent too. We also demonstrate the effectiveness of the two measures on multichannel data, where tie strength heterogeneity in personal networks is seen to moderately correlate for the same users across two communication channels (calls and text messages).

Disturbances in higher order consciousness encountered in neuropsychological rehabilitation and assessment.

The purpose of this invited paper was to summarize my clinical research on disturbances of higher order consciousness (i.e., primarily on self-awareness but including anosognosia and impaired awareness of another person's cognitive/emotional state) that contributed to my receiving the Distinguished Career Award from the International Neuropsychology Society. I reviewed my early clinical encounters with disturbances in higher order consciousness and then a series of studies performed with various colleagues over the last 45 years to better understand the nature of these disturbances. The findings obtained are also discussed within the context of other researchers' observations during this time frame. Disturbances in higher order consciousness include classic anosognosia, impaired self-awareness, denial of disability, and denial of ability. Proposed diagnostic features of each of these disturbances are outlined and a model for understanding their complex relationships suggested. Different treatment/rehabilitation approaches for these disturbances are also summarized. Disturbances in higher order consciousness are often revealed when exploring with the person their subjective experiences of their neurological and neuropsychological functioning following different brain disorders. These subjective experiences have diagnostic value and lead to different rehabilitation approaches. The neuropsychological investigation of disturbances in higher order consciousness should include integrating knowledge from the neurosciences with nonbiological understandings of how cultural and personality features of the person may also influences their subjective experiences associated with a known or suspected brain disorder.

Integrating Spatiotemporal and Travel-Related Information for Accurate Urban Passenger Profiling Using GANs

The elaborate description of passenger travel profiles is of significant importance in urban planning, socioeconomic structural design, and individual travel preference analysis. Traditional models often lack consideration of personalized features and exhibit suboptimal performance in constructing spatiotemporal dependencies. To address these issues, this paper proposes a method that integrates spatiotemporal information with travel-related information and employs generative adversarial networks (GANs) for adversarial training. This method accurately fits the true distribution of user travel data, thereby providing detailed profiles of public transportation passengers’ travel behavior. Specifically, the proposed approach considers the complete travel chain of individuals, establishes a spatiotemporal constraint representation model, and utilizes GANs to simulate the distribution of passenger travel, obtaining more compact and high-level travel vector features. The empirical results demonstrate that the proposed method accurately captures passengers’ travel patterns in both the temporal and spatial dimensions, offering technical support for urban transportation planning.

Scenic spot path planning and journey customization based on multilayer hybrid hypernetwork optimization.

In the face of increasingly diverse demands from tourists, traditional methods for scenic route planning often struggle to meet these varied needs. To address this challenge and enhance the overall service quality of tourist destinations, as well as to better understand individualized preferences of visitors, this study proposes a novel approach to scenic route planning and itinerary customization based on multi-layered mixed hypernetwork optimization. Firstly, an adaptive multi-route feature extraction method is introduced to capture personalized demands of tourists. Subsequently, a personalized tourist inference method based on a multi-layered mixed network is presented, utilizing the extracted personalized features to infer the true intentions of the tourists. Lastly, we propose a hypernetwork optimized route planning method, incorporating the inference results and personalized features to tailor the optimal touring paths for visitors. The results of our experiments underscore the efficacy of our methodology, attaining an accuracy score of 0.877 and an mAP score of 0.881 and outperforming strong competitors and facilitating the design of optimal paths for tourists.

Peer victimization and non-suicidal self-injury among depressed adolescents: a moderated mediation model

ABSTRACT Non-suicidal self-injury (NSSI) among teenagers with depression is a major and pervasive issue. Previous studies have established peer victimization as a risk factor for non-suicidal self-injury. However, little is known about how it influences teenagers to harm themselves non-suicidally. A total of 740 depressive outpatients aged 12–18 years with non-suicidal self-injury were selected. General demographic information was collected using the self-designed scale, and relevant information was collected using the Functional Assessment of Self-Mutilation, the Patient Health Questionnaire-9, the Multidimensional Peer Victimization Scale, and the Borderline Personality Features Scale for Children. After controlling for age and sex, it was discovered that depressive symptoms partially mediated the association between peer victimization and non-suicidal self-injury (p < 0.001). The mediating influence of depressive symptoms was modulated by borderline personality features. Half of the mediating effect is the moderating influence (p = 0.002). The moderated mediation model constructed in this study reveals the internal mechanism between adolescent peer victimization and non-suicidal self-injury, which is of great significance for the prevention and intervention of adolescent non-suicidal self-injury.

Individualized Machine-learning-based Clinical Assessment Recommendation System.

Traditional clinical assessments often lack individualization, relying on standardized procedures that may not accommodate the diverse needs of patients, especially in early stages where personalized diagnosis could offer significant benefits. We aim to provide a machine-learning framework that addresses the individualized feature addition problem and enhances diagnostic accuracy for clinical assessments. Individualized Clinical Assessment Recommendation System (iCARE) employs locally weighted logistic regression and Shapley Additive Explanations (SHAP) value analysis to tailor feature selection to individual patient characteristics. Evaluations were conducted on synthetic and real-world datasets, including early-stage diabetes risk prediction and heart failure clinical records from the UCI Machine Learning Repository. We compared the performance of iCARE with a Global approach using statistical analysis on accuracy and area under the ROC curve (AUC) to select the best additional features. The iCARE framework enhances predictive accuracy and AUC metrics when additional features exhibit distinct predictive capabilities, as evidenced by synthetic datasets 1-3 and the early diabetes dataset. Specifically, in synthetic dataset 1, iCARE achieved an accuracy of 0·999 and an AUC of 1·000, outperforming the Global approach with an accuracy of 0·689 and an AUC of 0·639. In the early diabetes dataset, iCARE shows improvements of 1·5-3·5% in accuracy and AUC across different numbers of initial features. Conversely, in synthetic datasets 4-5 and the heart failure dataset, where features lack discernible predictive distinctions, iCARE shows no significant advantage over global approaches on accuracy and AUC metrics. iCARE provides personalized feature recommendations that enhance diagnostic accuracy in scenarios where individualized approaches are critical, improving the precision and effectiveness of medical diagnoses. This work was supported by startup funding from the Department of Psychology at the University of Kansas provided to A.A., and the R01MH125740 award from NIH partially supported J.M.G.'s work.

Exploring How Older Adults Experience semAPP, a 360° Media-Based Tool for Memory Assessment: Qualitative Study.

Technology is already a part of our daily lives, and its influence is growing rapidly. This evolution has not spared the health care field. Nowadays, a crucial challenge is considering aspects such as design, development, and implementation, highlighting their functionality, ease of use, compatibility, performance, and safety when a new technological tool is developed. As noted in many works, the abandonment rate is usually higher when a user has a terrible experience with these instruments. It would be appropriate to incorporate the final users-whether they are patients, health care professionals, or both-in the stages of instrument design to understand their needs and preferences. Since most apps that fail did not include end users and health care professionals in the development phase, their involvement at all stages of app development may increase their commitment and improve integration, self-management, and health outcomes. This study aims (1) to develop semAPP (spatial and episodic memory assessment application), a 360° media-based tool, to assess memory in aging by simulating a real-life situation and (2) to test the usability of the app and the connected experience in an end-user population. A total of 34 older adults participated in the study: 16 (47%) healthy individuals and 18 (53%) patients with mild cognitive impairment. They used semAPP and completed qualitative and quantitative measures. The app includes 2 parts: object recognition and spatial memory tasks. During the first task, users have to navigate in an apartment freely and visit rooms, and then they must recognize the right map of the house. In the second task, users are immersed in a living room, and they have to encode and then recall some target objects, simulating a relocation. We deployed this app on an 11.2-inch iPad, and we tested its usability and the experience of users interacting with the app. We conducted descriptive analyses for both the entire sample and each subgroup; we also conducted parametric and correlation analyses to compare groups and to examine the relationship between task execution and the virtual experience, as well as the acceptance of technology. Both groups judged the app as an easy-to-use tool, and they were willing to use it. Moreover, the results match the idea that usability might be influenced by different factors depending on instrument and personal features, such as presentation, functionality, system performance, interactive behavior, attitudes, skills, and personality. The findings support the possibility of using semAPP in older patients, as well as the importance of designing and evaluating new technological tools, considering not only the general population but also the specific target ones.

AI-Powered VR for Enhanced Learning Compared to Traditional Methods

This paper evaluates a VR (Virtual Reality) application aimed at enhancing the learning of Python collection data types and structures for electrical and electronic engineering students. By incorporating gamification and personalisation features, the application provides an immersive environment where students can interact with virtual representations of complex programming concepts. To further enhance interactivity and engagement, the application integrates a virtual assistant and example generator, developed using Meta Voice SDK (Software Development Kit) and wit.ai. These AI (Artificial Intelligence)-NLP (Natural Language Processing) tools create personalised learning paths and generate dynamic examples based on individual learning progress. A user study was conducted with a total of 48 participants. During the user study, participants were divided into two equal groups of 24, both wearing EEG (Electroencephalography) headsets: one group engaged with the VR application, while the other read the traditional booklet, allowing for the recording and analysis of attention and engagement levels. These measures of engagement and attention were then compared to those extracted from a benchmark cohort of students whose learning experience was through more traditional booklets. The results indicated a statistically significant improvement in understanding Python collections among VR users compared to their baseline scores, highlighting the benefits of interactive and tailored learning environments. Additionally, EEG data analysis showed that VR users exhibited higher average levels of attention and engagement compared to those using the paper-based method, demonstrating the effectiveness of immersive technologies in sustaining learner interest and focus, particularly in enhancing learning for software development.

Nature of Users’ Persuasion and Exploration in Interactive Storytelling Video Games in the Netflix Games Library

As trailblazer in streaming entertainment, Netflix has redefined how people consume media, captivating audiences with its original programming. Despite this, the streaming giant could not translate similar success with its video game offering. This paper is an outcome of a unique experimental study which examines the built-in features of interactive storytelling games and their effect on induced persuasion and exploration among game players. This research involves eighty- eight players playing two popular games from the Netflix library. It tests the effects of artificial intelligence, feature interactivity, device responsiveness and personalization features of the game on induced persuasion and exploration among gamers. Using Bayesian regression and correlation, the results help to deduce that while built-in features can effectively persuade players, they fall short in encouraging deeper exploration within the game’s narrative. It also illustrates the growing significance of artificial intelligence in human computer interaction. The study also highlights the critical role of storytelling for the gaming business and its significance in developing new visual culture.

Evaluating the effectiveness of faculty teachers’ performance at Birzeit University as perceived by students

The current study investigated the effectiveness of teaching performance in seven faculties at Birzeit University from students’ point of view. A questionnaire, consisting of (50) items based on the domains of teaching planning, teaching execution, personal features and communications skills and evaluating students' learning, was developed and distributed to (405) male and female students. The findings of the study showed that the level of effectiveness of the teaching performance was considered average (62.4%—67.8%) according to the adopted scoring criteria. Results also revealed that there were significant statistical differences at the level of (α ≤ 0.05) attributed to gender in favor of females; significant statistical differences at the level of (α ≤ 0.05) were recognized between humanities and scientific faculties in favor of humanities faculties, while there were no significant statistical differences between the various humanities faculties.