Predicting anxiety, depression, and insomnia among Bangladeshi university students using tree-based machine learning models.

Background and Aims: Mental health problem is a rising public health concern. People of all ages, specially Bangladeshi university students, are more affected by this burden. Thus, the objective of the study was to use tree-based machine learning (ML) models to identify major risk factors and predict anxiety, depression, and insomnia in university students. Methods: A social media-based cross-sectional survey was employed for data collection. We used Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index (ISI-7) scale for measuring students' anxiety, depression and insomnia problems. The tree-based supervised decision tree (DT), random forest (RF) and robust eXtreme Gradient Boosting (XGBoost) ML algorithms were used to build the prediction models and their predictive performance was evaluated using confusion matrix and receiver operating characteristic (ROC) curves. Results: Of the 1250 students surveyed, 64.7% were male and 35.3% were female. The students' ages ranged from 18 to 26 years old, with an average age of 22.24 years (SD = 1.30). Majority of the students (72.6%) were from rural areas and social media addicted (56.6%). Almost 83.3% of the students had moderate to severe anxiety, 84.7% had moderate to severe depression and 76.5% had moderate to severe insomnia problems. Students' social media addiction, age, academic performance, smoking status, monthly family income and morningness-eveningness are the main risk factors of anxiety, depression and insomnia. The highest predictive performance was observed from the XGBoost model for anxiety, depression and insomnia. Conclusion: The study findings offer valuable insights for stakeholders, families and policymakers enabling a more profound comprehension of the pressing mental health disorders. This understanding can guide the formulation of improved policy strategies, initiatives for mental health promotion, and the development of effective counseling services within university campus. Additionally, our proposed model might play a critical role in diagnosing and predicting mental health problems among Bangladeshi university students and similar settings.

Posttraumatic Growth, Maladaptive Cognitive Schemas and Psychological Distress in Individuals Involved in Road Traffic Accidents-A Conservation of Resources Theory Perspective.

Road traffic accidents can have profound psychological impacts on the individuals involved, encompassing both negative distress and positive growth. This study, guided by the conservation of resources (COR) theory, investigates the intricate relationship between posttraumatic growth (PTG), maladaptive cognitive schemas, and psychological distress in individuals involved in road traffic accidents. PTG reflects an individual's ability to derive positive changes from adversity, while maladaptive schemas represent negative cognitive patterns. Using a 122 sample of individuals involved in road traffic accidents, we examined direct and indirect effects within this complex network. Our findings reveal significant direct effects of PTG on psychological distress (ß = 0.101, p = 0.02). Particularly noteworthy are the indirect effects mediated by cognitive schemas, emphasizing the role of impaired autonomy and perceived performance deficiencies (ß = 0.102, p = 0.05). This suggests that individuals involved in road traffic accidents experiencing higher PTG levels may indirectly experience greater psychological distress through these maladaptive cognitive schemas. This study not only advances our understanding of the psychological consequences of road traffic accidents but also aligns with self-determination theory, emphasizing autonomy and competence as fundamental needs. Individuals involved in road traffic accidents may undergo profound shifts in perspective following the trauma, which our results support. Recognizing the nuanced relationship between PTG, maladaptive cognitive schemas, and psychological distress is crucial for tailoring interventions and support systems for individuals involved in traffic accidents. As PTG can coexist with distress, interventions should foster adaptive growth while addressing maladaptive schemas to promote resilience in the face of traumatic events.

Predictors of Romanian Psychology Students' Intention to Successfully Complete Their Courses-A Process-Based Psychology Theory Approach.

Student retention is a frequently researched issue due to the incidence of student dropout and its significance to learning outcomes. However, there are research gaps that need to be addressed in understanding the factors influencing student dropout in the context of higher education in Romania. This cross-sectional investigation aims to fill these gaps by examining the relationships between satisfaction with the specialization, self-regulation of learning behavior, students' perceived stress, perceived acceptance from family and friends, and the intention to complete studies. The study utilizes various statistical analysis techniques, including mediation analysis and correlation analysis, to analyze the collected data. An online questionnaire was administered to non-randomized students majoring in Psychology, and a total of 144 valid and consented responses were obtained. The results reveal significant influences of satisfaction with the specialization, self-regulated learning, and students' perceived stress on the intention to successfully complete courses. Furthermore, academic self-efficacy was found to fully mediate the relationship between satisfaction with the specialization and academic adjustment. These findings contribute to a better understanding of the student dropout process in the Romanian higher education system. By identifying the factors associated with student retention, this study provides insights that can inform the development of interventions aimed at improving students' retention and overall learning outcomes.

A Network Analysis Approach toward Adaptive Overt Narcissism Network.

The relationship between narcissistic personality and art and beauty appreciation has recently become the focus of research investigations. Adaptive narcissists raise their sense of worth in order to shield themselves from harm caused by others. Because they aspire to be more attractive, healthier, and successful versions of themselves, they frequently have greater success in life than the majority of people. Grandiose and overtly narcissistic behavior are the main recognized characteristics of an overt narcissist, which is currently regarded as a personality disorder that puts mental health and wellbeing at peril. On a random sample collection of data from 1101 respondents to an online questionnaire, we conducted a network analysis of the Adaptive Overt Narcissism Scale (AONS) items. In this study, we used a network analysis approach to examine the network structure of adaptive overt narcissism, as well as its relationships with psychological functioning. The present study utilized network analysis to investigate the centrality measures of items in the Adaptive Overt Narcissism Scale (AONS) and their interrelationships. Results indicated that item Q6.8 ("I appreciate art and beauty") had low betweenness, closeness, and strength centrality measures, indicating that it was less influential in the network. However, it also had negative expected influence, suggesting that its absence would have a destabilizing effect on the network. These results highlight the importance of the appreciation of art and beauty in deactivating the adaptive overt narcissist network. Further research is needed to explore the mechanisms underlying this relationship and its implications for narcissism prevention and intervention.

The Effect of the Organizational Climate on the Integrative-Qualitative Intentional Behavior in Romanian Preschool Education-A Top-Down Perspective.

The concept of educational organizational climate relates to the relational, social, psychological, affective, intellectual, cultural and moral environment that characterizes educational/teaching and managerial activity at the level of a school organization. This study is based on the theory of planned behavior framework in measuring preschool teachers' intentional integrative-qualitative behaviors and Marzano's Model of Teaching Effectiveness. The Marzano Model outlines educational strategies and gives teachers and administrators tools to help teachers become more effective. A sample of 200 valid responses was gathered in an online investigation that targeted preschool educators from Romania. Marzano's Model of Teaching Effectiveness is an evaluation tool used to measure the success of highly effective teachers, which is further utilized in this study to measure preschool teachers' effectiveness in relation to intentional integrative-qualitative behaviors. The integrative-qualitative intentional behaviors are measured with the IQIB scale. This research assumes collegiality and professionalism as independent variables and interrogates preschool teachers' behavioral intention toward adopting integrative-qualitative behaviors through the sequential mediators of Planning and Preparing, Reflecting on Teaching and Classroom Strategies and Behaviors from a top-down perspective. The results revealed a significant indirect effect of Collegiality and Professionalism on preschool teachers' behavioral intention toward adopting intentional integrative-qualitative behaviors through the sequential mediators Planning and Preparing, Reflecting on Teaching and Classroom Strategies and Behaviors, confirming our hypothesis. Discussion and implications are offered from a top-down sustainable educational management perspective.

On the Technology Acceptance Behavior of Romanian Preschool Teachers.

This study investigates how compatibility and perceived enjoyment affect the link between intention to use and actual technology use in Romanian preschool education, building on earlier studies. METHODS: 300 participants were invited to participate in this research from 15 Romanian counties. 182 preschool teachers' questionnaires were utilized for data analysis after the return and screening of responses. A valid and accurate scale evaluating preschool teachers' behavior towards technology adoption was included in the questionnaire, along with self-reported demographic data, professional identification, and other information. Data was analyzed using SPSS V.16. RESULTS: (1) Intention to use, compatibility, perceived enjoyment, and actual use were positively associated. (2) The effect of compatibility and perceived enjoyment on the link between intention to use and actual technology use was carried out in the following way: Intention to use → Compatibility with technology → Perceived enjoyment → Actual use. We hypothesize that intention to use affects compatibility, compatibility affects perceived enjoyment, and, lastly, perceived enjoyment affects actual use. For a more robust validation of results, we have also modelled this relationship with the Radial Basis Function (RBF) neural network. CONCLUSION: Compatibility and perceived enjoyment partially mediate the relationship between intention to use and actual technology use in class by Romanian preschool teachers. According to the theory of planned behavior, this study brought to light the intricacy of the relationship between preschool teachers' intention to utilize technology in the classroom and their actual usage of it. Limitations and implications are discussed.

A Network Analysis-Driven Sequential Mediation Analysis of Students' Perceived Classroom Comfort and Perceived Faculty Support on the Relationship between Teachers' Cognitive Presence and Students' Grit-A Holistic Learning Approach.

The interaction between teachers and students is critical to the learning process. Student success and learner satisfaction have consistently improved in educational situations where instructors and students connect frequently and meaningfully. The Community of Inquiry (CoI) framework, as well as the sense of belonging concept, have received a significant amount of attention from researchers investigating online learning since its debut. The current study focuses on the CoI framework in general, and in particular on studies on teaching, social, and cognitive presences in connection to students' feeling of belonging and grit enhancement. This research investigated the opinion of 310 students at the Aurel Vlaicu University of Arad regarding their satisfaction with their teachers' presences, their academic sense of belonging, and their grit. Our methodology followed an innovative approach. First, we employed a network analysis on all subscales' mean scores, and then we performed a sequential mediation analysis based on both the network analysis results and the conclusions from the literature review. We tested whether students' perceived classroom comfort and perceived faculty support sequentially mediated the relationship between teacher's cognitive presence and students' grit. According to the scientific literature, teacher's cognitive presence consists of four fundamental categories: triggering events, exploration, integration, and resolution, which specifically the validation of knowledge by cooperation and reflection in a community of inquiry. We further tested if sense of belonging might mediate the relationship between teachers' cognitive presence and students' grit. The results show that students' perceived classroom comfort and perceived faculty support partially and significantly sequentially mediate the relationship between teachers' cognitive presence triggering events and students' grit. The results are then further used to suggest possible recommendations for designing holistic learning environments in Romanian higher education institutions.

A Parallel Mediation Analysis on the Effects of Pandemic Accentuated Occupational Stress on Hospitality Industry Staff Turnover Intentions in COVID-19 Context.

The purpose of this research was to analyze how different effects of the COVID pandemic, expressed through pandemic accentuated occupational stress, perceived job insecurity, occupational safety and health perception and perceived organizational effectiveness, may impact turnover intentions of the personnel in the hospitality industry. Our research team designed an online questionnaire which was analyzed with network analysis to depict the relationship between factors, and, then, a confirmatory factor analysis was employed to confirm the distribution of the items to the envisaged five factors. Based on a sample of 324 randomized Romanian hospitality industry staff, the results of our cross-sectional study revealed that occupational safety and health perception, perceived organizational effectiveness and perceived job insecurity in the pandemic accentuated occupational stress to indirectly and significantly impact hospitality industry staff turnover intentions (TI). The results indicated that, while the total effect of PAOS on TI was significant, the direct effect was still significant, while all three mediators remained significant predictors. Overall, mediators partially mediated the relationship between PAOS and TI, indicating that employees with low scores on occupational safety and health perception (OSHP), and perceived organizational effectiveness (POE) and high scores on perceived job insecurity (PJI) were more likely to have higher levels of TI turnover intentions.

A Cognitive Systems Engineering Approach Using Unsupervised Fuzzy C-Means Technique, Exploratory Factor Analysis and Network Analysis-A Preliminary Statistical Investigation of the Bean Counter Profiling Scale Robustness.

A bean counter is defined as an accountant or economist who makes financial decisions for a company or government, especially someone who wants to severely limit the amount of money spent. The rise of the bean counter in both public and private companies has motivated us to develop a Bean Counter Profiling Scale in order to further depict this personality typology in real organizational contexts. Since there are no scales to measure such traits in personnel, we have followed the methodological steps for elaborating the scale's items from the available qualitative literature and further employed a cognitive systems engineering approach based on statistical architecture, employing cluster, factor and items network analysis to statistically depict the best mathematical design of the scale. The statistical architecture will further employ a hierarchical clustering analysis using the unsupervised fuzzy c-means technique, an exploratory factor analysis and items network analysis technique. The network analysis which employs the use of networks and graph theory is used to depict relations among items and to analyze the structures that emerge from the recurrence of these relations. During this preliminary investigation, all statistical techniques employed yielded a six-element structural architecture of the 68 items of the Bean Counter Profiling Scale. This research represents one of the first scale validation studies employing the fuzzy c-means technique along with a factor analysis comparative design.

The Mediation Role of an Individual's and Couple's Psychological Factors, Including Parenting in the Prediction of Relational and Marital Satisfaction.

The goal of this study was to widen the scope of the social component of family sustainability. The fundamental goal of this non-experimental, quantitative study was to look at the links between parenting correlates, personality characteristics, marital satisfaction, and well-being in couples, as well as to construct explanatory prediction models for relational and marital satisfaction. The study focused on the effects of personality traits, parental self-efficacy, and attachment to marital and relational satisfaction. The test instruments applied were: the Experiences in Close Relationships-Revised, Marital Adjustment Test, Couple Satisfaction Index, Relationship Satisfaction Scale, Family Distress Index, Generalized Self-Efficacy Scale (adapted to the role of a parent), Mowen's Personality Scale, and demographic data. A total of 238 Romanians answered the online survey, recruited based on a convenience sampling method. Participants in this research were individuals who were both married and had at least one child. The main findings show that agreeableness, openness, conscientiousness, anxious and avoidant attachment, and marital adjustment predict the satisfaction in the relationship, and openness partially mediates the association between marital adjustment and relationship satisfaction. Parental self-efficacy appears to influence the association between relationship satisfaction and marital satisfaction. An increased parental self-efficacy score predicts an increased relationship satisfaction and marital satisfaction. The higher the parental self-efficacy, the higher the satisfaction in the relationship, which leads to an increase in satisfaction in the couple. These results show that marital adjustment and adaptation are related to relational satisfaction, and these relationship are partially mediated by an individual's openness. Despite some limitations, the current study significantly contributes to couples therapies and interventions in terms of physical and mental health, and the study provides insight into the experiences and perspectives of married individuals with children in Romania.

Pathways to inclusive and equitable quality early childhood education for achieving SDG4 goal-a scoping review.

According to Sustainable Development Goal 4.2 (SDG 4.2), Equal Access to Quality Pre-primary Education, governments throughout the world are working to ensure that all children have access to high-quality early childhood development, care, and pre-primary education by 2030. In order to organize available evidence into a coherent framework, the current scoping review represents an exploratory synthesis addressing the broad question of what qualitative and inclusive Early Childhood Education and Care strategies are currently being established globally to achieve SDG4 targets. The goal of this scoping review in this respect, was to map the available research and offer an overview of micro-, meso-, and macro-level perspectives on evidence-based interventions and strategies, for the promotion of SDG4 globally. A layered model of early childhood education that is both inclusive and egalitarian education emerged, starting with the micro level: child, family and community, mezo level: nursery, and kindergarten and macro level: national policies and SDG 4.2 Agenda for 2030. The mezzo level connects the micro and macro levels, being the most solicited level of implementing inclusive and qualitative ECEC strategies. Thus, starting with putting a real emphasis on children rights, creating a qualitative and inclusive culture with a holistic understanding of child development, then investing in teacher preparation and instilling a strong belief and positive attitudes toward equity in early childhood services, developing inclusive educational policies with an authentic community support offered by all stakeholders, then adapting curriculum and assessment methods to all early childhood educational contexts and lastly piloting and up-scaling good practices, and investing in infrastructure, facilities and innovative educational services, SDG4.2 targets could transparently and efficiently be attained by 2030, with all the setbacks arisen from the pandemic context. The data provide light on a vast topic range, including human rights and values, policy actions, and ideologies. The micro-level themes emphasized the importance of fostering equitable and inclusive environments for children., as well as instructional approaches that encourage positive attitudes toward diversity and instructors' levels of experience in dealing with diversity. We also discovered the significance of creating chances that promote socialization, connection development, and a sense of belonging. Meso-level principles emphasized the relevance of schooling in a child's holistic development and skill acquisition. Mainstream availability for all children, national curriculum regulations, teacher preparation for inclusive early childhood education, excellent funding and governance, evaluation and monitoring, and research on inclusive early childhood education comprise the macro level. As a concept and an approach, inclusive and qualitative education necessitates the preparedness of all relevant educational components to participate. Providing inclusive education in the early years requires setting the foundation for subsequent levels of schooling. The active engagement of a young kid should be directed by developmentally and individually suitable curricula. Access to and participation in age-appropriate general curricula becomes critical in identifying and providing specialized support services. Inclusive programming does not imply that the educational programs will necessarily be of good quality. Efficiency and wellbeing are synonymous with equity. Equitable education investment benefits everyone in society, not just the most marginalized. Investing in education will help communities achieve all of the Sustainable Development Goals related to education.

A Radial Basis Function Neural Network Approach to Predict Preschool Teachers' Technology Acceptance Behavior.

With the continual development of artificial intelligence and smart computing in recent years, quantitative approaches have become increasingly popular as an efficient modeling tool as they do not necessitate complicated mathematical models. Many nations have taken steps, such as transitioning to online schooling, to decrease the harm caused by coronaviruses. Inspired by the demand for technology in early education, the present research uses a radial basis function (RBF) neural network (NN) modeling technique to predict preschool instructors' technology usage in classes based on recognized determinant characteristics of technology acceptance. In this regard, this study utilized the RBFNN approach to predict preschool teachers' technology acceptance behavior, based on the theory of planned behavior, which states that behavioral achievement, in our case the actual technology use in class, depends on motivation, intention and ability, and behavioral control. Thus, this research design is based on an adapted version of the technology acceptance model (TAM) with eight dimensions: D1. Perceived usefulness, D2. Perceived ease of use, D3. Perceived enjoyment, D4. Intention to use, D5. Actual use, D6. Compatibility, D7. Attitude, and D8. Self-efficacy. According to the TAM, actual usage is significantly predicted by the other seven dimensions used in this research. Instead of using the classical multiple linear regression statistical processing of data, we opted for a NN based on the RBF approach to predict the actual usage behavior. This study included 182 preschool teachers who were randomly chosen from a project-based national preschool teacher training program and who responded to our online questionnaire. After designing the RBF function with the actual usage as an output variable and the other seven dimensions as input variables, in the model summary, we obtained in the training sample a sum of squares error of 37.5 and a percent of incorrect predictions of 43.3%. In the testing sample, we obtained a sum of squares error of 14.88 and a percent of incorrect predictions of 37%. Thus, we can conclude that 63% of the classified data are correctly assigned to the models' dependent variable, i.e., actual technology use, which is a significant rate of correct predictions in the testing sample. This high significant percentage of correct classification represents an important result, mainly because this is the first study to apply RBFNN's prediction on psychological data, opening up a new interdisciplinary field of research.

The use of theory of planned behavior to systemically study the integrative-qualitative intentional behavior in Romanian preschool education with network analysis.

Predicting preschool teachers' intention to adopt qualitative and inclusive early childhood intentional behaviors represents an important research field. The objective of this research is first to develop and validate a scale to assess the integrative-qualitative intentional behavior (IQIB-ECEC) of preschool teachers in order to achieve SDG4.2's objective of ensuring that all children have access to high-quality pre-primary education and then to systemically analyze the relationship between variables with Network Analysis. The theory of planned behavior (TPB) describes key individual beliefs (attitudes, subjective norms, and perceived behavior control) that affect people's intentions to engage in a certain conduct and has previously been used with success in evaluating people's intentions to adopt a certain behavior. This research represents one of the first Romanian attempts to use the theory of planned behavior to study the Integrative-Qualitative Intentional Behavior in Romanian Preschool Education and systemically analyze results with Network Analysis approach. This study used a randomized 300 Romanian preschool teachers enrolled in a National Training Program entitled Qualitative and Inclusive Early Childhood Education managed by the Romanian Educational Ministry. Data were collected via an online questionnaire. The scale validation followed a confirmatory factor analysis (CFA). The fitting of the IQIB-ECEC 19-item scale showed that all coefficients CFI (0.942), TLI (0.920), SRMR (0.0452), and RMSEA (0.0451) bring strong evidence in the favor of the statistical validity of the scale. The final IQIB-ECEC 19 items and 8 factors scale obtained a Cronbach's alpha of 0.77. The systemic Network Analysis approach was used in interpreting data. The centrality of the network model was further investigated and the clustering coefficients index were calculated. According to the results, perceived power/control beliefs and behavioral intention were detected as the most important dimensions, whereas behavioral beliefs were less important. These findings were discussed in terms of their theoretical and practical significance.