Search Results (3,016)

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: Human nutritional requirements are closely linked to energy expenditure, which depends on daily and occupational activities. Studies on groups performing tasks requiring increased physical effort may support determining their energy and nutritional needs. The study population consisted of soldiers performing a wide range of tasks domestically and during missions abroad, whose physical effort may be comparable to that of athletes in demanding sports disciplines. The aims of this study were (1) to assess the energy expenditure of soldiers performing training tasks in two different special forces units, as a basis for evaluating the physical demands of their work; (2) to evaluate the daily energy expenditure value as a basis for planning the energy and nutritional value of the daily food ration, as well as to develop a proposal for a nutritional standard dedicated to collective feeding in special forces units. Methods: The study included soldiers from the Special Unit “GROM” and from the Special Branch of the Military Police (MP). Energy expenditure was measured using heart rate monitoring and analysis of heart rate variability. Results: The average daily energy expenditure related to field training was 4175 ± 723.7 kcal for GROM soldiers and 5014.8 ± 666.3 kcal for soldiers of MP. Conclusions: To ensure safe and adequate nutrition for special forces soldiers, the energy value of the daily food ration—after applying a 5–10% safety margin—should be no less than 4400 kcal. Considering the significant increase in energy expenditure during intense training, the average value of this increase was determined to be approximately 500 kcal. It was proposed to increase the energy value of the daily food ration by 500 kcal. Based on the findings, nutritional requirements were determined as a proposal for a basic nutritional standard for soldiers of Polish special units. Full article

Landfill leachate represents a long-term source of contamination that may significantly affect groundwater and receiving water bodies through the migration of organic, inorganic, and toxic pollutants. This study evaluated the long-term migration of landfill leachate and its potential environmental impacts using the LandSim Release 2 probabilistic software model applied to two municipal waste landfills in the Republic of Serbia: the regional sanitary landfill “Gigoš” in Jagodina and the sanitary landfill “Meteris” in Vranje. The modelling framework integrated laboratory leachate analyses, hydrogeological conditions, engineered barrier system characteristics, and receptor-oriented contaminant transport assessment. Model validation was performed through comparison of simulated and laboratory-measured concentrations. Two scenarios were analyzed for each site: an engineered sanitary landfill scenario with a functional containment system and a conservative barrier-failure scenario representing complete loss of engineered barrier functionality. Ten representative leachate parameters were included, covering nitrogen compounds, inorganic ions, toxic substances, and heavy metals/metalloids. The results showed that engineered protection systems significantly delay contaminant migration and reduce receptor concentrations, while barrier-failure conditions lead to earlier pollutant breakthrough and higher environmental risk. The simulations demonstrated that under the engineered sanitary landfill scenario, receptor concentrations of all analyzed contaminants remained below the corresponding maximum allowable concentrations, with contaminant migration occurring only after several centuries. In contrast, the conservative barrier-failure scenario resulted in substantially earlier contaminant breakthrough, with nitrogen compounds and phenols representing the greatest environmental concern due to their rapid migration and exceedance of regulatory thresholds, while the “Meteris” landfill generally exhibited higher receptor concentrations than the “Gigoš” landfill. These findings highlight the importance of predictive modelling and long-term monitoring for sustainable landfill management and groundwater protection. 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

Sharps injuries and biological exposures remain a leading occupational safety risk in healthcare training environments. Preventing such injuries requires not only trainees’ declarative knowledge of biological hazards, but their threat appraisal—the cognitive process through which individuals evaluate personal risk and that motivates consistent adherence to standard precautions in practice. This cross-sectional study (N = 581) examined whether biological risk knowledge predicts cognitive threat appraisal in Italian health professions students surveyed prior to their first supervised clinical internship, and whether this relationship varies by gender. Drawing on Protection Motivation Theory (PMT), a multiple linear regression showed that biological risk knowledge significantly predicted personalized threat appraisal (β = 0.214, p < 0.001). Gender was also associated with threat appraisal, with female students reporting higher levels than male peers at equivalent knowledge levels (β = 0.184, p = 0.035). The overall model explained 16% of variance in threat appraisal (adjusted R² = 0.150), indicating that mandatory pre-placement occupational safety training is associated with risk appraisal activation, but only partially, and that a causal interpretation requires longitudinal confirmation. These findings suggest that knowledge transmission alone is insufficient to reduce biological risk exposure in clinical settings: appraisal-activating components—including scenario-based learning and near-miss incident review—should be integrated into occupational safety curricula for health professions students, with attention to gender differences in risk perception. Full article

The final stage of urban logistics does not end at the building entrance but continues within complex, vertically structured indoor environments, where conventional ground-based delivery systems face limitations in efficiency, flexibility, and scalability. This study introduces the concept of last-meter delivery, defined as unmanned aerial vehicle (UAV)-enabled transport from the building envelope to the recipient within global navigation satellite system (GNSS)-denied, building-regulated indoor space, and systematically reviews the literature from two traditionally separate domains: indoor-UAV operation in GNSS-denied spaces, and outdoor-UAV-based logistics. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 297 studies are synthesized through a two-stream thematic synthesis. The review makes three contributions. First, a unified analytical framework is developed across four dimensions (spatial mobility, logistical capability, social acceptance, and operational coordination) through which the two bodies of literature are shown to be largely complementary, with the gaps in one stream coinciding with the strengths of the other. Second, indoor aerial delivery is found to be subject to a distinct set of operational constraints, including micro-scale navigation accuracy, strict geometric safety envelopes, close human–UAV interaction, and privacy sensitivity, implying that indoor transport-UAVs cannot be realized through simple miniaturization of outdoor platforms but require precision-oriented, human-centric, and building-aware design. Third, the four dimensions are translated into a building-management-oriented indicator framework covering spatial compliance, handover standardization, building information modeling (BIM) integration, occupant consent, and liability allocation, reframing last-meter requirements in terms that are actionable for building planners and facility managers. By framing these challenges within the last-meter perspective, this review identifies the gap between current last-mile theories and emerging in-building aerial logistics and provides a structured foundation for future research. Full article

Musculoskeletal disorders (MSDs) represent a critical global challenge to workforce productivity. In Thailand, these disorders are particularly prevalent in labor-intensive industries such as ice manufacturing, where workers face significant ergonomic hazards. Addressing this gap, the present study aimed to assess the occupational health, safety, and ergonomic risks facing workers in ice production facilities. This cross-sectional descriptive study investigated production workers who were employees in two of eight ice manufacturing plants in Surat Thani, Thailand, using the Rapid Entire Body Assessment (REBA) method. A structured occupational health and safety risk assessment questionnaire and the REBA evaluation form were used to collect data. All participants were male, averaging 30.4 (±8.5) years old. Regular pain areas included the upper/lower back, hips/thighs, shoulders, wrists, and ankles. Ergonomic assessments showed high overall risk due to heavy lifting, repetitive tasks, and cold environments. Based on REBA scores, 13.04% were in the very-high-risk group (score ≥ 11) and 65.22% in the high-risk group (score 8–10). Most production workers in ice plants faced high ergonomic risks, especially from postures affecting the upper and lower back. Training should be provided to promote awareness of risky postures and proper lifting techniques. Mechanical aids and back-support equipment are also recommended to help prevent musculoskeletal injuries. 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

Autonomous drone navigation relies on onboard sensors to perceive obstacle information in real time. However, indoor environments contain abundant wall structures that occlude the sensor’s field of view, rendering obstacle information within occluded regions undetectable to the drone. Existing trajectory planning algorithms fail to adequately account for the safety risks introduced by sensor occlusion. To address this limitation, this article proposes a novel trajectory planning framework to enhance drone flight performance in indoor environments. Specifically, a 3D occupancy grid map is first constructed from sensor data, and an initial trajectory is generated from the current position to the goal. A sensor occlusion detection algorithm then classifies the current scene into three categories: occlusion-free, partial occlusion, and full occlusion. For occlusion-free scenarios, the initial trajectory is directly forwarded to the controller. For partial and full occlusion cases, an occlusion-aware trajectory replanning algorithm generates multiple candidate trajectories in unknown regions. These candidates are evaluated by a scoring function comprising three metrics: safety, efficiency, and smoothness. Upon detection of a collision between the currently executing initial trajectory and an obstacle, the active trajectory is immediately switched to the highest-scoring candidate trajectory, thereby ensuring both flight safety and navigation efficiency of the drone. Extensive experiments are conducted across multiple occlusion scene configurations to validate the performance of the proposed method. Experimental results demonstrate that the proposed method is capable of providing safe and efficient trajectories for drones under both partial occlusion and full occlusion conditions. Full article

This study evaluated the reliability and application of relative potency factors (RPFs) for assessing hepatic mixture risks of per- and polyfluoroalkyl substances (PFASs) in Korean finished drinking water. A total of 1254 finished water samples collected from 70 drinking water treatment plants between 2018 and 2024 were analyzed for eight PFAS compounds. Hepatic RPFs proposed by the National Institute for Public Health and the Environment (RIVM) were assessed using a structured scoring system and applied to estimate PFOA-equivalent mixture risks. Hazard quotients (HQs) based on hepatic toxicity reference doses were also calculated for comparison. PFAS concentrations generally declined over time, including PFOA from 0.0032 to 0.0014 μg/L, PFOS from 0.0008 to 0.0003 μg/L, and PFHxS from 0.0072 to 0.0004 μg/L between 2018 and 2024. The RPF-based method produced higher cumulative risk estimates than the individual toxicity-based approach, suggesting that single-compound HQs may underestimate risks from co-occurring PFASs. Although total risks were generally below the non-carcinogenic threshold of 1.0, the 95th percentile PFOA-equivalent risk for PFNA exceeded the individual threshold of 0.1. These findings support endpoint-specific RPF-based assessment for PFAS mixtures in drinking water. Full article

This research focuses on developing a deep learning-based framework to forecast maintenance expenditures within the residential sector. To maintain building value, resident safety, and energy efficiency, consistent facility maintenance is indispensable. This necessity is especially heightened given the recent increase in the construction of supertall and high-performance buildings. However, estimating repair costs for residential facilities is challenging due to the diverse building types, ownership structures, and occupancy patterns compared to other property uses. Therefore, this research proposes a deep-learning model to establish a highly reliable and scientific method for estimating repair costs using empirical data gathered from actual residential facilities. Among the deep learning algorithms, Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs) were adopted to develop models and optimize them through a fixed split. The framework and results of this paper facilitate the prediction of maintenance costs for residential facilities, which can contribute to budget planning, long-term facility management, preventive maintenance, resource management, and advanced decision-making. Moreover, it will contribute to the advancement of facility management of residential facilities. Full article

Objectives: Patient safety is central to healthcare quality, yet dental practice also involves occupational risks for professionals. This study examined the lifetime prevalence and types of patient- and staff-safety incidents among Korean dental professionals and explored associated demographic, professional, and institutional factors. Methods: A cross-sectional survey was conducted among 439 dental professionals in South Korea. Participants reported lifetime experience of predefined safety incidents, institutional safety factors, and demographic and occupational characteristics. Descriptive statistics, profession-based comparisons, and multivariable logistic regression were applied. Results: Overall, 89.1% of respondents reported at least one safety incident. The most common patient-safety events were aspiration or ingestion of teeth or prosthetic materials and instrument-related injury, whereas sharps injuries and verbal abuse were the leading staff-safety issues. Dentists and dental hygienists differed significantly in response knowledge, liability insurance coverage, and safety education. The presence of institutional safety protocols was associated with higher reported incident experience, which may reflect greater recognition and reporting rather than a causal increase in harm. Conclusions: Safety incidents are highly prevalent in Korean dental practice and represent an underrecognized quality-of-care and workforce-safety issue. Integrated strategies including occupational-hygiene measures, structured safety education, non-punitive reporting, and stronger organizational preparedness are needed to improve dental healthcare delivery. Full article

This study employed a quantitatively driven mixed-methods approach to investigate crop-specific musculoskeletal disorder (MSD) prevalence and ergonomic risks among Taiwanese watermelon farmers, comparing them with pear (canopy-based) and pineapple (static-stooping) cohorts. A total of 218 participants were recruited (60 watermelon, 60 pear, 63 pineapple, and 35 non-farmers). Structured questionnaires quantified MSD prevalence and ergonomic exposures, while qualitative interviews provided a supportive operational context. Watermelon farmers reported a prominent lower-limb dominant discomfort profile, with a hip/thigh disorder prevalence (36.7%) significantly higher than pear (13.1%) and pineapple (11.1%) farmers. Multivariate logistic regression showed that daily working hours (aOR = 1.38) and uncomfortable posture duration (aOR = 1.33) were independent predictors of hip/thigh disorders. This elevated prevalence may be associated with the combined effects of prolonged deep squatting, dynamic heavy lifting, and unstable sandy terrain. Furthermore, low personal protective equipment adoption was primarily related to environmental incompatibility (sand accumulation and thermal stress). Although the cross-sectional design limits causal inferences, these findings highlight the need for targeted, crop-specific ergonomic interventions, such as breathable, sand-resistant joint supports. Full article

Battery locomotives used in underground coal mining operations require continuous maintenance, and failures occurring during these operations pose significant occupational safety and health (OSH) risks. Traditional Risk Assessment Methods (TRAMs), particularly the Risk Matrix Method (RMM), often fail to capture the uncertainty and subjectivity inherent in complex mining environments. This study develops a fuzzy logic-based risk assessment framework to improve the evaluation of accident risks associated with maintenance and repair activities in battery locomotive workshops of an underground coal mine in Turkey. Two fuzzy inference models (FL-Basic and FL-Advanced) based on expert knowledge and linguistic variables were designed using Mamdani-type inference with centroid defuzzification. The mathematical formulation of the fuzzy inference and defuzzification steps is presented explicitly, and a six-step algorithm formalises the proposed framework. The rule base of FL-Advanced systematically upweights the severity dimension relative to RMM through reassignment of 16 of the 25 consequent categories. The outputs of these models were compared with RMM to analyse their effectiveness in identifying critical hazards. Application results from Karadon Hard Coal Company show that the proposed FL-Advanced model significantly reduces ambiguity, prioritises high-severity risks more realistically, and provides a more consistent decision-making structure for OSH specialists. The study highlights the advantages of fuzzy logic for modelling uncertain, incomplete, and human-dependent data in hazardous underground mining conditions. Full article