Search Results (1,472)

Background: Micromanagement is an extensively prevalent yet relatively under-theorized management process in healthcare organizations. This narrative review synthesizes the literature on micromanagement and related leadership practices in healthcare, focusing on its antecedents, manifestations, consequences, and mitigation strategies. Methods: A structured literature search was conducted on 10 May 2024 across eight electronic databases. Eligible studies included qualitative, quantitative, mixed-methods, and applied studies published between 2003 and 2024. The main outcomes were the underlying causes and behavioral measures of micromanagement, examined directly, or closely related constructs such as excessive supervision, reduced autonomy, authoritarian leadership, toxic leadership, and controlling managerial behavior. The secondary outcomes involved organizational and patient-related effects and their respective interventions. Results: A total of twelve studies were selected. The identified antecedents of micromanagement were authoritarian leadership styles, autocratic and toxic leadership personality traits, overly intrusive supervisory practices, poor employee empowerment, complicated regulation, unclear definition of professional roles, and inherent structural challenges. Micromanagement behavior was seen in authoritative decision-making, transactional supervision, systematic reduction in employee autonomy, and institutionalized distrust. The consequences recorded include high levels of occupational stress, poor organizational productivity, poor quality of healthcare services, high employee turnover rates, and psychological problems. Conclusions: This review represents a preliminary conceptual synthesis of the literature that addresses micromanagement in healthcare. The evidence base is inconsistent, with many studies focusing on constructs that relate to micromanagement while not studying it directly. In future research, validated tools to assess micromanagement should be designed, as well as leadership interventions that benefit both workplace and patient outcomes. Full article

Background/Objectives: Dietary adherence and physical activity are pivotal yet understudied behavioral components of self-management of type 2 diabetes mellitus (T2DM) in the Middle East and North Africa region. This study aimed to quantify dietary adherence and physical activity levels, examine their association, and identify sociodemographic and clinical factors independently associated with these outcomes among adults with T2DM in southwest Saudi Arabia—a region chronically underrepresented in the literature. Methods: A descriptive cross-sectional study (n = 257; December 2023–March 2024) was conducted at a specialist diabetes center. The Perceived Dietary Adherence Questionnaire (PDAQ; 0–56 after removal of the fat-avoidance item with near-zero item-total correlation) and General Practice Physical Activity Questionnaire (GPPAQ) were administered alongside body mass index (BMI) and glycated hemoglobin (HbA1c) extracted from medical records. Bonferroni-corrected non-parametric bivariate tests, multiple linear regression with variance inflation factor diagnostics, and binary logistic regression were applied. Results: Mean 8-item PDAQ was 20.44 ± 10.04/56 (36.5%); carbohydrate spacing was the critical deficit (16.4%). GPPAQ distribution: 10.1% inactive, 28.0% moderately inactive, 49.0% moderately active, and 12.8% active, with sensitivity analysis ranging 28.0–47.5% in the two lowest categories. PDAQ–GPPAQ correlation was weak (Spearman r = 0.18; 95% CI: 0.06–0.29; r² = 0.032). BMI alone accounted for 81.0% of PDAQ score variance (cross-sectional; direction of association not established; full model Adj. R² = 0.826; LOO-CV R² = 0.820, indicating model stability). Employment type showed the strongest cross-sectional association with GPPAQ-derived inactivity classification (housewife OR = 5.77; retired/seeking OR = 4.98 vs. employed), largely driven by the occupational component of the composite score. Conclusions: Dietary adherence was substantially below the maximum achievable score; BMI was the factor most strongly associated with PDAQ scores in cross-sectional analysis, though the direction of this relationship cannot be established. Physical activity levels were substantially associated with occupational patterns; housewives and retired/other participants faced approximately five-fold greater odds of being classified as inactive or moderately inactive compared with employed individuals. The weak PDAQ–GPPAQ correlation (r² = 0.032) suggests these behaviors are not strongly co-determined and points to the potential value of distinct, hypothesis-generating intervention approaches for dietary quality and leisure-time physical activity in T2DM populations. Full article

Background: Fasting plasma glucose, glycated hemoglobin (HbA1c), and oral glucose tolerance testing remain central to the diagnosis and monitoring of dysglycemia, but they mainly reflect the average glycemic exposure or discrete time-point measurements and may not capture intraday and interday glucose fluctuations. Glycemic variability (GV) has been associated with oxidative stress, endothelial dysfunction, inflammation, and diabetes-related complications, although much of the evidence derives from experimental, clinical, and diabetes-care settings rather than occupational cohorts. Aim: This narrative review examines the physiological basis, measurement, and potential occupational relevance of GV and continuous glucose monitoring (CGM) in working populations. Methods: Literature was narratively selected from biomedical databases, major guidelines, consensus statements, and occupational-health sources, prioritizing reviews, clinical guidelines, cohort studies, mechanistic studies, and CGM studies. No systematic search, risk-of-bias assessment, or quantitative synthesis was performed. Main findings: CGM is an established technology in selected diabetes-care contexts and provides metrics such as coefficient of variation, time in range, time above range, and time below range. Its use in occupational medicine, however, remains investigational outside selected clinical circumstances. Work-related factors such as shift work, circadian disruption, sleep loss, psychosocial stress, irregular meal timing, sedentary behavior, and variable physical workload may influence glucose regulation, but direct evidence linking these exposures to CGM-measured GV in workers remains limited. Implications: Potential applications include research on occupational determinants of metabolic health, monitoring of workplace lifestyle interventions, and individualized management of workers with diabetes in safety-sensitive roles, provided that consent, confidentiality, clinical follow-up, equity, and data-governance safeguards are ensured. Conclusions: GV assessment may complement traditional metabolic markers in selected occupational-health contexts, but routine CGM-based surveillance of general worker populations is not currently supported by sufficient evidence. Further longitudinal and interventional studies are required. Full article

As accessibility development in public buildings has gradually shifted from facility compliance toward experience- and performance-oriented evaluation, the quantitative assessment of indoor mobility experiences among blind users still lacks a systematic sensor-supported analytical framework. To address this gap, this study proposes an indoor accessibility assessment approach that integrates multi-sensor data acquisition with explainable machine learning, using a tactile museum as the experimental setting. Sixty-four participants with first-level blindness were recruited to complete a real-world directed walking task. A multimodal database was constructed by integrating objective data collected from an ultra-wideband (UWB) indoor positioning system, an intelligent gait analysis system, and video-based behavioral recording, including spatiotemporal trajectories, gait characteristics, and behavioral events, together with post-task accessibility satisfaction ratings. Based on this dataset, a random forest model was developed using the Overall Accessibility Satisfaction Score (OAS) as the response variable. SHAP, partial dependence analysis, and GAM smoothing were further applied to interpret the associations between key variables and predicted satisfaction. The results showed that walking distance, number of turns, self-reported collision perception, and selected gait indicators made relatively high contributions to the model interpretation, and these variables exhibited certain nonlinear associations with predicted satisfaction. These findings suggest that combining multi-source sensor-based behavioral measurement with explainable machine learning has potential for sensor-supported post-occupancy evaluation of indoor accessibility environments and can provide exploratory references for the quantitative assessment and optimization of accessibility in public buildings. Full article

Background. Behavioral procrastination has been increasingly recognized as a maladaptive self-regulatory pattern associated with unhealthy lifestyle behaviors, psychological stress, and adverse cardiometabolic profiles. However, its relationship with accelerated cardiovascular aging remains poorly understood. This study aimed to evaluate the association between behavioral procrastination and heart age acceleration in a large occupational cohort of Spanish workers. Methods. A multicenter cross-sectional study was conducted including 92,184 actively employed Spanish workers undergoing routine occupational health examinations between 2021 and 2024. Behavioral procrastination was assessed using the Pure Procrastination Scale-9 (PPS-9). Estimated heart age and heart age acceleration were calculated using a cardiovascular risk-factor-based algorithm. Multivariable linear and logistic regression analyses were performed to evaluate associations between procrastination score, continuous heart age acceleration, and accelerated cardiovascular aging phenotypes after adjustment for demographic, lifestyle, anthropometric, and cardiometabolic variables. Restricted cubic spline analyses and sex-stratified analyses were additionally conducted. Results. Higher procrastination levels were associated with progressively worse cardiometabolic and cardiovascular aging profiles. Mean heart age acceleration increased from −3.1 ± 6.0 years in participants with very low procrastination to 14.0 ± 6.4 years in those with very high/chronic procrastination (p < 0.001). The prevalence of accelerated cardiovascular aging (>0 years) increased from 27.2% to 94.2% across increasing procrastination categories, whereas severe accelerated cardiovascular aging (≥10 years) increased from 1.7% to 75.6% (both p < 0.001). In fully adjusted multivariable analyses, each 5-point increase in PPS-9 score was associated with a 0.50-year increase in heart age acceleration (B = 0.50; 95% CI 0.48–0.52; p < 0.001). Participants with very high/chronic procrastination exhibited significantly higher odds of accelerated cardiovascular aging (OR 1.89; 95% CI 1.65–2.18) and severe accelerated cardiovascular aging (OR 2.51; 95% CI 2.16–2.92). Associations were significantly stronger among women (p-interaction < 0.001). Findings remained robust in sensitivity analyses excluding participants with diabetes mellitus. Conclusions. Behavioral procrastination was associated with higher estimated heart age acceleration and less favorable cardiovascular aging profiles in this large occupational cohort. Higher procrastination severity was consistently related to greater estimated heart age acceleration and a higher prevalence of cardiovascular aging phenotypes, even after extensive multivariable adjustment. These findings indicate that higher procrastination levels were associated with less favorable cardiovascular aging profiles beyond traditional biomedical risk factors. However, given the cross-sectional design, no conclusions regarding causality or temporality can be drawn. Full article

The transition toward next-generation energy systems requires advanced computational tools capable of supporting accurate, adaptive, and data-driven energy performance assessment. Within this context, Energy Performance Indicators (EnPIs) established under the ISO 50001 framework remain essential for monitoring energy efficiency and continuous improvement; however, conventional indicators are often based on static or simplified relationships that do not adequately capture the dynamic, nonlinear, and multivariable behavior of modern buildings and energy management systems. This systematic review analyzes the integration of ISO 50001-based EnPIs with intelligent algorithms and artificial intelligence techniques for enhanced energy management. The review follows a PRISMA-inspired methodology, using Scopus as the primary database and Web of Science and Google Scholar as complementary sources. From 5442 initial records, 2691 studies were screened and 283 articles were selected for detailed analysis, supported by a bibliometric keyword co-occurrence analysis using VOSviewer 1.6.20. The results show a clear evolution from traditional energy indicators and normalized baselines toward computational modeling approaches based on regression analysis, machine learning, deep learning, forecasting, anomaly detection, and optimization algorithms. These methods improve the predictive capability, adaptability, and operational relevance of EnPIs by incorporating climatic, occupancy, temporal, and operational variables. The reviewed evidence indicates that intelligent algorithms can strengthen ISO 50001 energy management systems by enabling dynamic baselines, early detection of abnormal consumption patterns, predictive decision-making, and continuous operational optimization. Nevertheless, challenges remain regarding data quality, model interpretability, methodological standardization, and practical integration into certified energy management frameworks. Overall, this review highlights that the future of energy performance assessment does not rely on replacing conventional EnPIs, but on transforming them into intelligent, computationally supported indicators for sustainable, resilient, and next-generation energy management systems. Full article

A formal thermodynamic mapping is established between the attractive Fermi–Hubbard model and the repulsive Bose–Hubbard model at finite temperature and at imaginary chemical potential $\mu =i\theta$. By utilizing a large N-expansion, it is shown that the partition functions of the two models are related by a plain shift $\theta \to \theta +\pi$. This condition maps the BCS–BEC crossover of attractive fermions to a Bose–Fermi crossover (fermion-like occupation) of repulsive bosons. A central feature of this correspondence is the thermal kernel $g(\beta E,\varphi )$ (with $\beta$ the inverse absolute temperature, E the energy scale, and $\varphi$ the phase angle), whose analytic continuation $g_B(\beta E,\varphi )=g_F(\beta E,\varphi +\pi )$ governs the bosonic (B) and fermionic (F) sectors. Interestingly, the particular angles $\varphi =2\pi /3$ and $4\pi /3$ for fermions correspond to $\varphi =\pi /3$ and $5\pi /3$ for bosons, marking the boundaries of an universal thermal window. It is further argued that the present mechanism shows how an emergent, fermionization-like phenomenon can occur at finite interaction strength through a thermodynamic effect induced by the imaginary chemical potential. It is emphasized that this does not imply a transmutation of quantum statistics at the operator level, but rather a thermodynamic exclusion-like behavior driven by the imaginary chemical potential, unlike the Tonks–Girardeau limit, where fermionization arises from an infinite repulsive interaction and anyonic or Floquet-engineered systems where transmutation emerges from modified statistics or dynamics. Effectively, the phase $\varphi$ is a statistical parameter; by twisting the thermal phase, it generates fermion-like behavior without hard-core constraints or infinite repulsion through purely thermodynamic mechanisms. The gap equation and number equation for the bosonic model are derived, highlighting the role of the imaginary chemical potential as a statistical regulator. The results obtained here provide a unified framework for understanding crossovers in interacting lattice systems. Full article

The contamination of aquatic environments by cadmium and other toxic heavy metals represents a major environmental concern requiring efficient and operationally sustainable remediation strategies. In this work, iron oxide materials were synthesized through a microwave-assisted hydrothermal method and evaluated for Cd(II) removal from aqueous systems. Different precursor compositions and organic additives were initially screened in order to identify the most suitable adsorbent formulation. The selected Fe-Tart material was characterized by FTIR, SEM-EDS, and XRD analyses, revealing hydroxylated and poorly crystalline iron oxide structures with heterogeneous surface organization. Batch adsorption experiments were performed under controlled conditions to investigate the influence of pH and equilibrium adsorption behavior, while adsorption data were analyzed using Langmuir and Freundlich isotherm models. Cd(II) uptake showed strong pH dependence, with adsorption progressively increasing from acidic to near-neutral conditions and reaching approximately 80% removal at pH 7–8. The Langmuir model provided the best fitting results (R² = 0.988), suggesting preferential occupation of energetically comparable surface sites with a maximum adsorption capacity of 6.51 mg g⁻¹. The adsorption behavior was interpreted within a pH-dependent surface complexation framework involving hydroxylated iron oxide surfaces. Although the adsorption capacity remained lower than that reported for some highly engineered adsorbents, the results indicate that microwave-assisted synthesis may provide a relatively simple and rapid route for preparing iron oxide-based materials potentially applicable to water remediation systems. Full article

For life-threatening events, such as fire hazards, performing real experiments (human-based experiments) to investigate the movement dynamics of occupants is often impractical due to different ethical, safety, and cost constraints. Consequently, realistic crowd movement models are essential for analyzing evacuation behavior. In this work, a modified social force model is proposed to simulate more reasonable movement patterns and prevent the unrealistic behavior of directly moving to and getting close to a fire source. The proposed model considers changes in stress levels caused by exposure to fire and incorporates their effects on escape behavior. Unlike most previous work, the non-homogeneity of occupants’ characteristics and physical abilities are considered. Simulation results show that the proposed model can provide more reasonable movement trajectories to avoid fire sources during emergency evacuation. Furthermore, the impacts of the location of the fire and the width of the exit on the performance of the evacuation process are investigated. Full article

Background and Objectives: Gambling disorder (GD) is a behavioral addiction associated with distress, comorbidity, and functional impairment. This exploratory cross-sectional study examined associations between DSM-5-TR symptom burden, personality dimensions, cognitive emotion regulation, quality of life, and sociodemographic variables in a Romanian clinical sample. Materials and Methods: The sample included 122 adults with psychiatrist-confirmed pathological gambling/GD recruited from “Prof. Dr. Alexandru Obregia” Clinical Hospital of Psychiatry, Bucharest. Personality was assessed with the Personality Clinical Form (PCF; 109 valid profiles), cognitive emotion regulation with the Cognitive Emotion Regulation Questionnaire, and quality of life with the Quality of Life Inventory. Symptom burden was measured using a nine-item binary DSM-5 symptom burden index. Results: The symptom burden index showed a pronounced ceiling effect: median = 9.00 (IQR = 9.00–9.00; range = 4–9), with 91.0% classified as severe and 77.9% meeting all nine criteria. In PCF analyses, symptom burden was positively associated, after Benjamini–Hochberg correction, with broad personality pathology, including maladaptive personality dimensions, personality-functioning indicators, and personality-disorder feature scales; the strongest association involved borderline features. Catastrophizing and Blaming Others were positively associated with severity, whereas Positive Reappraisal, Putting into Perspective, and Positive Refocusing were negatively associated. Quality of life was very low overall and associated with personality and coping variables, but not directly with symptom burden. Criterion-count rank distributions differed by marital status and perceived social support; occupational status showed an omnibus distributional difference, but no pairwise contrast survived correction. Conclusions: GD was characterized by severe symptom burden and restricted score variability. Findings support multidimensional assessment of personality functioning, emotion regulation, quality of life, and social–contextual vulnerability. Full article

Architectural design decisions in educational buildings often rely on spatial parameters such as ceiling height and window layout, yet systematic methods for evaluating their influence on user experience during early design stages remain limited. This study investigates how spatial height, window position, and window-to-wall ratio affect students’ classroom usage intention (UI) through the mediating role of psychological experience. An evidence-based pre-occupancy evaluation approach was developed by integrating immersive virtual reality (VR) experiments with structural equation modeling (SEM). The study employed 61 university students for evaluating parametrically controlled virtual classrooms to examine perceived affective and cognitive experience (ACE), including emotional comfort, attentional focus, and spatial attractiveness, as well as classroom usage intention (UI). Using the data collected through VR experiment and followed by a questionnaire survey, using a stimulus–organism–response framework, the study modeled transmission pathways from spatial stimuli to behavioral outcomes. The results indicate that ACE is the strongest and most direct predictor of UI, highlighting psychological experience as the key pathway translating environmental exposure into behavioral preference. The relationship between perceived architectural attributes and psychological responses was context-dependent, suggesting a potential divergence between analytical spatial judgment and holistic emotional experience under explicit evaluation tasks. VR experience quality significantly influenced ACE but did not directly affect UI. The findings suggest the value of integrating VR and SEM as a pre-design evaluation tool and emphasize prioritizing experiential coherence as a measurable criterion for early-stage decision-making, rather than establishing direct causal links to long-term experiential responses. Full article

Educational buildings are characterized by daily movement and continuous interaction between formal and informal learning spaces. Understanding how students navigate and occupy these environments and how these experiences affect their academic performance is essential for developing responsive, human-centered architectural strategies. This research investigates spatial behavior, movement patterns, and physical classroom environments, and their relationship with academic achievement among students in the College of Architecture and Digital Design building at Dar Al-Uloom University. A mixed-methods approach is adopted, combining student surveys, movement mapping, and grade analysis. Movement mapping was used to document circulation patterns, spatial occupancy, and pause behavior across different periods of the academic day. In addition, academic performance categories, together with observed movement and space-use patterns, are used to contextualize spatial engagement. Additionally, an investigative comparative analysis is conducted across two campuses (male and female). The findings indicate that higher-performing students generally exhibit greater movement diversity and spatial engagement, with observable differences in spatial behavior between male and female students. Full article

The AMA Guides to the Evaluation of Permanent Impairment, Sixth Edition, have undergone a substantial transformation from a static publication to a continuously refined digital resource. This transition reflects both the rapid evolution of medical knowledge and longstanding concerns regarding the usability, consistency, and reproducibility of impairment ratings. Central to this transformation was the establishment of the AMA Guides Editorial Panel in 2019, which introduced a structured governance framework and evidence-based methodology for ongoing refinement. Unlike prior editions that relied on periodic print revisions, AMA Guides Digital permits continuous updating of individual chapters as new scientific evidence and clinical practices emerge. This narrative review examines the historical evolution of the AMA Guides, the development of AMA Guides Digital, the governance and methodological contributions of the Editorial Panel, and major system-specific refinements implemented between 2021 and 2025. Particular emphasis is placed on the Mental and Behavioral Disorders chapter (2021), the Nervous System chapter (2023), the Musculoskeletal chapters (2024), and the Pulmonary chapter (2025). These developments demonstrate a broader shift toward transparency, methodological rigor, harmonization across body systems, and alignment with contemporary clinical practice while maintaining continuity with the foundational principles of the Sixth Edition. The transition to a continuously refined digital model represents a paradigm shift in impairment evaluation with important implications for clinical, occupational, and medicolegal practice. Full article

The discharge of metal-containing effluents into aquatic systems remains a major environmental concern because metal ions can persist in water bodies and accumulate in biological systems, potentially affecting ecosystem and human health. Among these contaminants, Cr(III) is frequently encountered in waste streams generated by industrial activities, making its removal an important objective in water quality management. This study investigated the adsorption behavior of Cr(III) using lignocellulosic biosorbents obtained from tamarind shell (Tamarindus indica) after water, H₂O₂, and HCl pretreatments, with particular emphasis on equilibrium behavior, thermodynamic characteristics, and pretreatment-induced physicochemical modifications. Batch adsorption experiments were conducted to evaluate equilibrium behavior. The highest adsorption capacity (41.6 mg g⁻¹) was obtained with the water-treated biosorbent at 60 °C. The equilibrium data were best represented by the Sips model, suggesting that Cr(III) adsorption occurred on surfaces containing adsorption sites with different energetic characteristics. Thermodynamic analysis revealed that the adsorption process was spontaneous, while the enthalpy changes indicated predominantly endothermic behavior for the pretreated biosorbents. ATR-FTIR, SEM, EDS, and XRD analyses were performed to characterize the biosorbents before and after adsorption. The characterization results indicated that oxygen-containing functional groups, particularly hydroxyl and carbonyl functionalities, were associated with the adsorption process. SEM images showed morphological changes associated with pore occupation, while EDS confirmed chromium adsorption and suggested possible ion-exchange mechanisms. XRD patterns indicated a mainly amorphous structure. The results demonstrated that pretreatment-induced modifications strongly influenced the adsorption performance of tamarind shell. Water pretreatment produced the most favorable adsorption behavior, yielding the highest adsorption capacity among the evaluated biosorbents. The combined interpretation of equilibrium, thermodynamic, and characterization results revealed a close relationship between surface properties and Cr(III) uptake. Full article

Interior built environments influence user behavior through more than deliberate rational evaluation. They shape attention, movement, affective comfort, perceived safety, wayfinding, and well-being through bounded cognition, affective appraisal, heuristics, embodied perception, and automatic approach–avoidance processes. The research gap addressed in this review concerns the fact that prior work on interior environments, wayfinding, indoor environmental quality, neuroarchitecture, atmospherics, and behavioral decision-making remains fragmented across separate studies, and existing reviews rarely explain how these mechanisms can be organized into a design-usable framework for interior built environments. This narrative review synthesizes foundational and recent literature across building design, environmental psychology, neuroarchitecture, virtual reality, indoor environmental quality, wayfinding, and behavioral decision-making to clarify how decision mechanisms translate into interior design variables such as lighting, color, spatial organization, materiality, form, sensory atmosphere, environmental legibility, thermal comfort, and controllability. The review distinguishes bounded rationality, heuristics and biases, dual-process accounts, affective and atmospheric processing, prospect–refuge dynamics, mere exposure, and room-effect research rather than treating them as a single “non-rational” category. It proposes an integrative framework in which interior cues are processed through perceptual and affective appraisal; moderated by individual, cultural, contextual, temporal, and ethical factors; and expressed through behavioral outcomes such as navigation, approach or withdrawal, dwell time, perceived quality, usability, stress regulation, and well-being. The paper contributes to human-centered building design by formalizing a mechanism-based account of how interior environments can support behavior without reducing users to passive recipients of environmental manipulation. It concludes with practical implications for design briefing, post-occupancy evaluation, VR-based testing, healthcare and workplace audits, safety-critical settings, and future longitudinal validation. Full article