Search Results (10)

Artificial intelligence (AI) is increasingly embedded in students’ learning practices, yet little is known about how AI engagement evolves from an external technological aid into an agentic component of self-regulated learning. This study applies psychological network analysis to examine the structural relations among students’ knowledge of AI, perceived value and perceived cost of AI, intention to use AI, and three core self-regulated learning processes—forethought, performance control, and self-reflection—across different levels of AI use frequency. The study was conducted on a sample of 673 university students and early-career graduates. Networks were estimated using EBICglasso for the full sample and separately for low-, moderate-, and high-frequency AI users. Across all models, a stable two-system organization emerged, consisting of an AI appraisal subsystem (knowledge, value, cost, intention) and a self-regulation subsystem (forethought, performance control, self-reflection). However, the connectivity between these subsystems differed systematically by usage frequency. Among low-frequency users, perceived cost was more prominently positioned within the appraisal subsystem, suggesting that cost-related concerns may be more salient in lower-frequency use contexts. In contrast, in the moderate- and high-frequency groups, performance control appeared more centrally positioned at the interface between appraisal and self-regulation, suggesting stronger alignment between AI-related appraisals and performance-level regulatory processes in these groups. Students’ knowledge of AI displayed context-dependent structural roles across networks, consistent with a variable relational position across use-frequency groups. Overall, the findings suggest that AI appraisal and self-regulated learning form partially distinct but interconnected subsystems, and that their configuration may vary across AI use-frequency groups. Because subgroup comparisons were descriptive and formal stability analyses were not conducted, these findings should be interpreted as exploratory. The results do not support causal or developmental inference and require replication using bootstrapped stability analyses and formal network comparison procedures. Full article

Background: Psoriasis is a chronic immune-mediated inflammatory disorder strongly associated with cardiometabolic comorbidities. Although methotrexate (MTX) is widely used for moderate-to-severe disease, its influence on the relationships between inflammatory and metabolic biomarkers remains insufficiently characterized. Methods: This retrospective observational study included 132 hospitalized adult patients with psoriasis, stratified into untreated (n = 101) and MTX-treated (n = 31) groups. Inflammatory markers, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), neutrophil-to-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII), and metabolic indices, triglyceride–glucose index (TyG), metabolic score for insulin resistance (METS-IR), and atherogenic index of plasma (AIP), were analyzed. Group comparisons were performed using Mann–Whitney U and χ² tests. Spearman correlation matrices and regularized partial correlation networks (EBICglasso, γ = 0.5) were constructed separately for each group to explore inflammatory–metabolic connectivity. Results: MTX-treated patients exhibited lower NLR (p = 0.035) and fasting glucose levels (p = 0.004), while CRP, ESR, and composite metabolic indices did not differ significantly. In untreated patients, correlation analysis showed multiple significant cross-domain associations between inflammatory and metabolic markers. In contrast, fewer such associations reached statistical significance in the MTX-treated group. Network analysis indicated a less densely connected structure in the MTX group (9 vs. 12 non-zero edges); however, formal network comparison did not identify statistically significant differences between groups. Conclusions: Although fewer statistically significant cross-domain correlations were observed in MTX-treated patients, no statistically significant differences in network structure were detected between groups. These findings are exploratory and hypothesis-generating, not indicative of methotrexate-related modification of network structure, and are limited by the small size of the MTX-treated subgroup. Full article

Background: Emotional distress (ED) is common among patients with gynecological malignancies and is associated with reduced quality of life and suboptimal health outcomes. Total-score approaches may overlook the complex interrelationships among individual emotional symptoms. Objective: This study provides a theory-informed contextual application and empirical boundary test of symptom network analysis, organized by the Stress Process Model (SPM), to examine not only how ED symptoms cluster and connect with psychosocial correlates and quality-of-life domains, but also whether psychosocial stratification is reflected in altered symptom topology or primarily in differences in distress burden. Methods: A cross-sectional study was conducted among 415 patients with gynecological malignancies recruited from a tertiary hospital in China. ED was assessed using the Brief Profile of Mood States-Short Form (BPOMS-SF30). An exploratory three-track screening strategy was used to derive a focused 16-node set of frequent negative mood symptoms. Gaussian graphical models with EBICglasso regularization were estimated for the symptom network and for extended networks including demographic/clinical variables, SPM-related psychosocial variables, and quality-of-life indicators. Results: The ED network showed dense positive connectivity, with strong within-domain clustering and several cross-domain associations. Exhaustion, restlessness, and irritability were relatively more relationally prominent in the primary network, although centrality stability was low to moderate across models. Fatigue-related symptoms were closely connected with anxiety, depressive symptoms, and impaired quality of life. Among psychosocial variables, self-perceived burden showed the strongest conditional association with fatigue. Adjusting for demographic and clinical variables did not materially alter the core symptom network, and no significant subgroup differences in global strength or overall structure were observed across psychosocial strata. Conclusions: In this sample, psychosocial risk stratification appeared to relate more to the overall severity and burden of distress than to major reorganization of symptom topology. The study therefore contributes primarily as a theory-informed contextual application of network methods and as an empirical boundary test showing that several psychosocial strata did not exhibit major topological differences. Because the retained nodes were selected for prevalence, association strength, and selection stability, the observed prominence of fatigue- and activation-related symptoms should be interpreted as conditional on this focused symptom subset. Overall, the findings are correlational, exploratory, and hypothesis-generating. Full article

Academic functioning in university students emerges from the interplay of motivational, self-regulatory, emotional, and contextual processes. The present study examined the network structure linking academic motivation, self-regulated learning, academic engagement, academic burnout, generalized anxiety, self-esteem, and students’ ratings of instruction. Participants were 530 university students from Western Romania (Mage = 28.86, SD = 9.75; 87.5% women). Data were collected through an online cross-sectional survey using validated self-report instruments. A Gaussian Graphical Model was estimated using the EBICglasso procedure to examine the unique associations among the study variables and their relative structural importance within the network. The results indicated a moderately dense psychological network, with academic burnout emerging as the most structurally central node. Intrinsic motivation toward achievement, identified regulation, and performance control were positioned within the adaptive core of the network, whereas burnout, anxiety, amotivation, and low self-esteem clustered within the maladaptive region. Academic engagement occupied an intermediary position linking motivational and self-regulatory processes. Overall, the findings support a systems-oriented interpretation of academic functioning, suggesting that burnout represents a key convergence point in students’ psychological functioning, while self-determined motivation and self-regulated learning may serve as protective processes. These results highlight the value of network analysis for identifying psychologically meaningful intervention targets in higher education. Full article

Background: Despite the widespread implementation of treat-to-target strategies and modern disease-modifying antirheumatic drugs, a substantial proportion of patients with rheumatoid arthritis (RA) continue to report unmet needs (UNs), defined as a mismatch between patient expectations and symptom burden on the one hand and outcomes achieved with current care on the other. Patient–physician discordance in global assessments may reflect multidimensional influences, including pain mechanisms, psychosocial factors, functional impairment, and communication gaps, extending beyond inflammatory disease activity. Methods: In this cross-sectional study, 133 patients with RA and 57 healthy controls were included. UNs were operationalized as the signed difference between patient global assessment and physician global assessment (ΔPGA–PhGA). Clinical variables, patient-reported outcomes, and Short Form-36 (SF-36) domains were incorporated into two regularized partial correlation network models estimated using the extended Bayesian information criterion graphical least absolute shrinkage and selection operator (EBICglasso). Node centrality indices (strength, signed strength, betweenness, and closeness) were calculated. Network stability was evaluated using 2000 bootstrap resamples and correlation stability (CS) coefficients. Results: In the clinical network, pain intensity demonstrated the highest strength centrality and the strongest direct association with UNs. In contrast, Disease Activity Score in 28 joints with C-reactive protein (DAS28-CRP) showed no direct association with UNs after accounting for shared variance. In the SF-36-based quality-of-life network, UNs exhibited inverse associations, particularly with perceived health change and role–emotional functioning. Stability analyses indicated acceptable to good robustness (clinical network: CS = 0.59 for edge weights and 0.44 for strength; SF-36 network: CS = 0.59), supporting the reliability of the estimated network structures. Conclusions: UNs in RA are not solely determined by inflammatory disease activity but are embedded within interconnected clinical and psychosocial domains. Pain occupies a structurally central position in the clinical network, whereas perceived health change and emotional role limitations characterize the quality-of-life context of UNs. These findings underscore the importance of multidimensional and patient-centered assessment strategies in RA management. Full article

Background: Eco-anxiety is increasingly viewed as a multidimensional response to the climate crisis, but its links with religiosity and sustainable nutrition behaviors in highly religious settings are unclear. We identified eco-anxiety profiles in Turkish adults; compared religiosity, sustainable nutrition behaviors, and body mass index (BMI) across profiles; and examined the multivariate network connecting these domains. Methods: This cross-sectional online survey in Türkiye included 1105 adults (69.3% women; age 25.8 ± 8.4 years; BMI 23.5 ± 4.5 kg/m²). Participants completed the Eco-anxiety Scale, Duke University Religion Index, and Behaviors Scale Toward Sustainable Nutrition. Latent profile analysis used four eco-anxiety subscales. Between-profile differences were tested using canonical discriminant analysis and Kruskal–Wallis tests. A Gaussian graphical model estimated with EBICglasso assessed network connectivity. Results: Four profiles emerged: High (11.9%), Moderate (54.8%), Affective-dominant (8.3%), and Low (24.9%). Compared with the Low profile, the High profile showed higher sustainable nutrition scores for food preference, seasonal/local nutrition, and food purchasing (all p < 0.05); however, effect sizes were small (η²_H = 0.008–0.014), indicating modest practical differences. BMI did not differ across profiles (p = 0.211). In the network, seasonal/local nutrition had the highest strength centrality, whereas BMI was peripheral and weakly connected to other nodes. Conclusions: Eco-anxiety was heterogeneous and showed modest associations with sustainable nutrition behaviors at the group level, without differences in BMI. These preliminary findings suggest that eco-anxiety may co-occur with more sustainable food-related choices, generating hypotheses for future replication. Full article

This study investigates interrelations among social media addiction (SMA), Fear of Missing Out (FoMO), cyberloafing (CL), work engagement (WE), and organizational commitment (OC) using network analysis. An online survey in Germany/Switzerland (n = 452; OC assessed in the employed subsample, n = 173) measured the five constructs. Unregularized and EBICglasso partial-correlation networks were estimated, and centrality and bridge indices were computed. Two robust edges emerged: a strong SMA–FoMO association and a strong positive WE–OC link; the regularized network additionally indicated a triangular SMA–FoMO–CL pattern. FoMO and OC acted as bridge nodes between problematic social media behaviors and work attitudes, whereas direct SMA links to WE/OC were weak or absent. Findings position FoMO as a pivotal mechanism connecting social media use to organizational attitudes and support, distinguishing functional micro-breaks from disruptive CL. Limitations include the cross-sectional design, student-skewed sample, self-report measures, smaller OC subsample, and a German/Swiss context. Full article

In recent years, network psychometrics has emerged as an alternative to the reflective latent variable model. This model conceptualizes traits as complex systems of behaviors mutually interacting with each other. Although this model offers important advantages compared to the reflective model, questions remain regarding the necessary sample size and the influence of factors such as the number of nodes and edges. This study aims to evaluate the psychometric network model performance under different conditions of sample size, number of nodes, and number of edges. The methodology involved a simulation with 1000 replicates for each combination of sample size, number of nodes, and the value of gamma parameter, which is used to determine the magnitude of the edges considered significant. The effect of these conditions on the accuracy of edge estimations and centrality indices (strength and expected influence) was assessed using sensitivity, specificity, and bias indicators. Results suggest that sample size and network complexity have a more significant impact than γ, methodological guidelines being proposed to support decision-making in applied research. In summary, this study provides empirically grounded recommendations that can guide applied researchers in designing robust psychometric network analyses and ensuring reliable estimation of model parameters. Full article

In recent years, the role of flourishing in mental health has gained growing recognition, making the establishment of psychometrically and culturally validated instruments crucial for advancing theory and practice. The aim of this study is twofold: first, to adapt the Multidimensional Flourishing Scale for use in Turkey and investigate its psychometric properties; second, to explore the interrelationships between indicators of flourishing and psychological distress symptoms using network analysis. A total of 529 undergraduate students, comprising 316 females (59.7%) and 213 males (40.3%), with a mean age of 21.65 years (SD = 1.67), participated in the study. The Multidimensional Flourishing Scale, the Flourishing Scale, and the Kessler Distress Scale (K10) were utilized for data collection. Confirmatory factor analysis, Pearson correlation analysis, and the EBICglasso algorithm for network analyses were performed. The findings revealed that the Turkish version of the Multidimensional Flourishing Scale demonstrated a three-dimensional structure consistent with its original version, with satisfactory psychometric properties, including structural and convergent validity as well as reliability. Domain-level network analysis demonstrated that psychological well-being emerged as the most central node within the network, closely followed by psychological distress. Additionally, psychological distress was negatively associated with all domains of flourishing. At the item level, two symptoms of psychological distress, feeling depressed and feeling restless or fidgety, as well as three indicators of flourishing, feeling positive, feeling happy, and perceiving life as full of meaning, emerged as the most central nodes. These findings provide valuable insights into the central features of flourishing and psychological distress, which could potentially guide clinical practice. Further discussion and implications are elaborated upon in the study. Full article

Sexuality is an important sphere of every person’s life. Sexual dysfunctions and sexual dissatisfaction may also be present in cardiac diseases. Individuals affected by heart failure (HF) deserve special attention since it can be the final stage of many cardiac diseases. Therefore, it is important to verify potential correlates of sexual well-being in individuals with HF. This study was conducted online between 2019 and 2023, and 262 Polish women aged between 18 and 59 years (M = 45.48; SD = 7.65) participated in it. The Short Sexual Well-Being Scale, Depression Anxiety and Stress Scale, Fatigue Assessment Scale, and authors’ questionnaire were used. Relationships between tested variables were verified with the use of network analysis performed with the EBICglasso estimator. Centrality assessment showed that sexual well-being had the highest values of betweenness, closeness and degree, followed by fatigue and depression measures. Sexual well-being was negatively related to the number of declared sexual dysfunctions, fatigue, stress and depression levels. Participants’ age and HF duration were not related to the sexual well-being of tested women. Multiple additional partial correlations were detected. The obtained results show that sexuality may be a central sphere of life in women with HF and that one’s sexuality should not be negated when working with cardiac patients. Full article