Search Results (23,060)

Soil health refers to the combined physical, chemical, and biological properties of soils that allow them to function as a living system that sustains life. While numerous reviews summarize several methods to measure soil health, this review critically evaluates how the Soil Management Assessment Framework (SMAF) performs across diverse ecosystems, including croplands, agroforestry, coastal mangrove, and rangelands. We explore the evolutionary shift from single indicators to integrated assessment frameworks, tracing how targeted management practices, such as conservation tillage, crop rotation, cover cropping, organic amendments, and water management, alter physical, chemical, and biological indicator performance. The SMAF framework and scoring system are outlined using examples from around the world. This synthesis concludes that while SMAF provides an exceptionally rigorous, non-linear platform for quantitative Soil Quality Index (SQI), its practical execution remains deeply constrained by data-intensive requirements, selection of appropriate indicators, and adaptation to local contexts. To close this gap, we outline critical future directions, integrating the framework with AI and machine learning, real-time Internet of Things (IoT) field sensors, and dynamic digital twins. Ultimately, this work aims to shift soil monitoring from descriptive reporting to predictive, automated intelligence to provide the exact data needed for sustainable land management decisions. Full article

The physical learning environment shapes students’ well-being, health, and learning, yet its assessment remains fragmented. Existing tools focus on isolated dimensions, particularly indoor environmental quality, and rarely document transparently how design factors are weighted or how performance thresholds are derived. This study develops the Integrated Classroom Index (ICI), an original multi-criteria index integrating three design principles: personalization, environmental comfort, and stimulus. Following a sequential mixed-methods design, a literature review defined 12 design parameters and 39 indicators, whose content was validated by 42 interdisciplinary experts through a Kappa concordance analysis. A specialized subgroup of 18 experts then assigned the weights using the Analytic Hierarchy Process (AHP). Each principle is standardized to a 0 to 1 range and combined through local and principle weights, classifying classrooms as excellent, adequate, sufficient, insufficient, or poor, with guardrails that prevent trade-offs between critical dimensions. The retained parameters reached Good to Perfect agreement (Kappa up to 1.00), the AHP was fully consistent (consistency ratio = 0.083), and the principle weights were 0.59 for personalization, 0.32 for environmental comfort, and 0.09 for stimulus. The ICI offers a transparent, reproducible, and auditable framework for evaluating and improving classroom design quality. Full article

Employment is a key social determinant of health, yet autistic individuals face high levels of unemployment, with consequences for well-being and social inclusion. This exploratory study examined stakeholder perceptions regarding the inclusion of autistic individuals in public administration employment within the Italian context, considering its potential role in advancing health equity through stable and regulated work environments. A cross-sectional online survey was conducted to explore perceptions of current inclusion measures, the importance of specific inclusion domains, and the usefulness of potential support tools. Participants (n = 62) included autistic adults, family members, and professionals with expertise in autism. Quantitative data were analyzed using non-parametric tests, while qualitative responses were examined through reflexive thematic analysis. Quantitative findings showed that educators express more positive views on existing measures and greater support for new interventions compared to family members; autistic participants report intermediate perspectives. Qualitative analysis identified five areas: recognition of autistic perspectives, need for interventions, support figures, work personalization, and staff training. Although the study does not evaluate intervention effectiveness, the findings highlight stakeholder priorities and perceived needs related to employment inclusion. While exploratory and based on a limited sample, the results may inform future research and the development of more inclusive public employment practices. Full article

Background/Objectives: Musculoskeletal discomfort disorders (MSDs) are common occupational health problems among nurses, particularly in critical care settings due to physically demanding tasks and prolonged patient care activities. However, evidence regarding MSDs among critical care nurses in Malaysian teaching hospitals remains limited. This study aimed to determine the prevalence, severity, and associated workplace factors of musculoskeletal discomfort among critical care nurses in Kelantan, Malaysia. Methods: An analytical cross-sectional study was conducted among 308 critical care nurses working at Hospital Pakar Universiti Sains Malaysia, Kelantan. Data were collected using a structured self-administered questionnaire and the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ). Descriptive statistics, simple logistic regression, and multiple logistic regression analyses were performed using IBM SPSS version 30. Results: The prevalence of severe musculoskeletal discomfort among respondents was high, with 82.1% reporting severe discomfort. Several workplace-related factors were significantly associated with severe musculoskeletal discomfort in the bivariable analysis, including awkward back bending, carrying heavy equipment, manual orthopedic patient handling, insufficient rest breaks, awkward working positions, working while injured, and inadequate training on injury prevention. Multiple logistic regression analysis identified manual orthopedic patient handling (AOR = 1.882, 95% CI: 1.033–3.426, p = 0.039) and insufficient rest breaks during shifts (AOR = 2.581, 95% CI: 1.466–4.543, p = 0.001) as significant predictors of severe musculoskeletal discomfort. Conclusions: Musculoskeletal discomfort is highly prevalent among critical care nurses. Workplace ergonomic strain and inadequate recovery periods significantly contribute to severe musculoskeletal discomfort. Strengthening ergonomic practices, safe patient handling strategies, and occupational health interventions is essential to improve nurses’ well-being and maintain quality patient care. Full article

Accurate state of health (SOH) estimation of lithium-ion batteries (LIBs) is critical to ensuring the safety and reliability of battery management system (BMS). To achieve precise estimation, this study proposes a hybrid framework that integrates variational mode decomposition (VMD), kernel principal component analysis (KPCA), polar lights optimizer (PLO), and physics-informed neural network (PINN) for SOH estimation. First, multidimensional health features are extracted and decomposed by VMD into intrinsic mode functions (IMFs), which are then compressed into a one-dimensional principal component via KPCA, retaining over 95% of the original information. Subsequently, the PLO algorithm is used to adaptively optimize three key hyperparameters of the PINN-based model: the learning rate, the number of collocation points, and the regularization loss weight. Finally, the optimized PINN is deployed to predict the SOH of the Center for Advanced Life Cycle Engineering (CALCE) battery dataset. Experimental results demonstrate that the proposed VMD-KPCA-PLO-PINN exhibits high prediction accuracy under both 7:3 and 5:5 training-to-testing data partitions. For example, under the 5:5 partition, the proposed model achieves an average $R^2$ of 0.983 and an average RMSE of 0.0085 on the tested CALCE cells. Full article

Background and Objectives: Overweight and obesity among medical students represent significant public health concerns as unhealthy weight status during medical training may affect future health and professional counseling practices. Understanding the factors associated with BMI categories may help inform future university-based health promotion strategies. This study aimed to assess the prevalence of overweight and obesity and examine sociodemographic, lifestyle, and dietary factors associated with BMI categories among medical students. Methods: This cross-sectional study was conducted among medical students at the College of Medicine, King Faisal University, between December 2025 and January 2026. Students were selected using proportionate stratified random sampling according to academic year and gender. Of the 422 students invited to participate, 382 students completed the study questionnaire and anthropometric assessment, yielding a response rate of 90.5%. Height and weight were measured in person using calibrated equipment. Data on demographic characteristics, lifestyle habits, dietary patterns, smoking, sleep, and physical activity were collected through a structured face-to-face questionnaire. Multinomial logistic regression analysis was performed to examine factors associated with BMI categories, using normal weight as the reference category. Results: A total of 382 medical students were included, with a median age of 21 years. The prevalence of overweight was 19.9%, and the prevalence of obesity was 14.1%, resulting in a combined overweight and obesity prevalence of 34.0%. In the adjusted multinomial logistic regression model, male gender was associated with being overweight compared with having normal weight (aRRR = 2.71, 95% CI: 1.22–5.98). Obesity showed associations with below-average financial status (aRRR = 13.53, 95% CI: 1.98–92.22), current smoking (aRRR = 17.00, 95% CI: 2.50–115.47), soft drink intake of 2–3 times/week (aRRR = 4.57, 95% CI: 1.13–18.49), and lower physical activity, including no activity (aRRR = 11.61, 95% CI: 2.07–65.01), rare activity (aRRR = 7.54, 95% CI: 2.21–25.80), and physical activity several times/month (aRRR = 5.86, 95% CI: 1.78–19.31). Always eating breakfast was associated with overweight (aRRR = 2.23, 95% CI: 1.05–4.73). Several adjusted estimates had wide confidence intervals, indicating limited precision. Conclusions: Overweight and obesity were common among medical students at King Faisal University and were associated with several sociodemographic, lifestyle, and dietary variables. Because of the cross-sectional design and the imprecision of some adjusted estimates, these findings should be interpreted as associations rather than causal relationships. Future longitudinal and multicenter studies using validated lifestyle measures are recommended to clarify temporal relationships and guide university-based health promotion strategies. Full article

This study aims to assess the impact of an 8-week multidisciplinary intervention on the physical and psychosocial health in active women over 55 years old, paying attention to the need of supervision. Eighty-one women were assessed for pelvic floor strength (using PERFECT’s guidelines), body composition and satisfaction with life, and later blindly assigned to a supervised or reduced-supervision pelvic floor exercise program (i.e., therapeutic exercises guided by a professional, twice a week, or identical exercises performed at home). All of them received six additional educational sessions together, interspersed along the program, for nutritional and psychological counseling. Twenty-eight women of 36 [66.50 (4.68) years] in the supervised group, and another 20 of 34 [64.65 (5.12) years] (reduced-supervision) ended the intervention. Although both groups improved in all four dimensions of pelvic floor muscle strength, with endurance showing differences between-groups. Completion rate was lower in the reduced-supervision group (58.8% vs. 77.7%). Lack of motivation was their main reason to leave. No significant changes were found in body composition or life satisfaction. However, the results suggest that comparable pelvic floor strength benefits can be achieved with fewer resources when health awareness is emphasized. Ongoing supervision appears important to minimize dropout in these sensitive interventions. Multidisciplinary, movement-based programs show strong potential for public health promotion in older women. Pelvic floor training should be incorporated into preventive care for this population and supervised or follow-up formats seem essential to support adherence and long-term effectiveness. Full article

Background/Objectives: In recent decades, health care for those living with chronic and disabling conditions has expanded beyond symptom and disease management to include efforts to promote health and quality of life. This narrative review synthesizes insights from a 26-year longitudinal study examining health promotion and quality of life among persons living with the chronic and disabling condition of multiple sclerosis (MS). Methods: The longitudinal study, launched in 1999, included a sample of 621 community-residing persons with MS. Our longitudinal research design allowed us to investigate unique issues related to the speed, sequence, direction, and duration of changes in a wide range of MS outcomes. Guided by Braun and Clarke’s thematic analysis framework, we have critically reviewed the more than 100 peer-reviewed publications and presentations generated by the study, in which we have identified overarching “Big Picture” themes, and we have contextualized them in relation to other MS research. Results: Five major themes were supported by the findings in this narrative review: (1) Strong interest in health promotion behaviors; (2) Positive view of overall health; (3) Mediation of the impact of functional limitations on quality of life; (4) Physical activity impacts the trajectory of functional limitations over time; and (5) Association of health behaviors with quality of life and health outcomes. Conclusions: Interventions that recognize and incorporate the positive health behaviors and perceptions of persons living with a long-term chronic condition can assist persons aging with chronic conditions to adjust to changes in their environment and the demands of self-management. Full article

Background and Objectives: Physical inactivity is a major modifiable lifestyle factor associated with type 2 diabetes mellitus (T2DM). However, real-world primary care datasets often rely on pragmatic clinical estimates of physical activity (PA) and may lack HbA1c, fasting glucose, dietary data, diabetes duration, and detailed medication information. Therefore, PA–T2DM associations in routine care must be interpreted within the limitations of cross-sectional observational data. Materials and Methods: This cross-sectional observational study analyzed 863 adult patients from a real-world primary care cohort. Participants were categorized into low, moderate, and high PA groups according to self-reported habitual weekly activity levels estimated during routine physician interviews. PA categories were based on clinically meaningful weekly activity thresholds consistent with public health recommendations. The primary outcome was documented T2DM. Secondary variables included lipid profile, blood pressure, body mass index, waist circumference, smoking status, and statin therapy. Multivariable logistic regression models were used to assess associations between PA category and T2DM, with high PA as the reference group. Results: T2DM prevalence showed a graded inverse cross-sectional association across PA categories, being highest in the low PA group (29.7%), intermediate in the moderate PA group (16.7%), and lowest in the high PA group (8.9%) (p < 0.001). In the fully adjusted model, low PA was strongly associated with higher odds of T2DM compared with high PA (odds ratio [OR] 4.32, 95% confidence interval [CI] 2.61–7.15, p < 0.001). Moderate PA was also associated with higher odds of T2DM compared with high PA (OR 2.07, 95% CI 1.23–3.48, p = 0.006). LDL-C differed significantly across PA groups, with the lowest values observed in the high PA group, whereas most other cardiometabolic parameters were comparable. Conclusions: Lower self-reported PA was strongly associated with higher T2DM prevalence after multivariable adjustment in this real-world primary care cohort. These findings support routine PA assessment as part of lifestyle-based cardiometabolic risk stratification. Because dietary intake, HbA1c, diabetes duration, glucose-lowering medication details, and regulatory biomarkers were not available, causal and mechanistic conclusions cannot be drawn. Future studies should integrate PA, nutritional assessment, glycemic markers, medication data, and physiological regulatory measures to better characterize lifestyle-related diabetes risk. Full article

Background/Objectives: In rural settings, work, family, and environmental conditions are closely intertwined, requiring Primary Health Care to recognize care needs arising from productive work and everyday family responsibilities. This study aimed to analyze overall and domain-specific levels of perceived workload related to agriculture/fishing and family involvement in the household among rural and small-scale fishing workers, examine associated factors, and discuss analytical implications for nursing care organization in Primary Health Care. Methods: This cross-sectional study was conducted in three island territories in Rio Grande, southern Brazil, following the STROBE guidelines. Data were collected using a structured questionnaire on sociodemographic, family, and occupational characteristics and the NASA Task Load Index (NASA-TLX), applied separately to assess workload related to agriculture/fishing and family involvement in the household. Results: The sample included 146 rural and small-scale fishing workers. Perceived workload could suggest high in both dimensions, with higher levels in agriculture/fishing (mean 84.0 ± 16.5; 89.7% high/very high) than in family involvement in the household (mean 76.1 ± 24.5; 75.4% high/very high). Agriculture/fishing workload perceived could suggest highest scores for overall effort level, temporal demand, and physical demand, whereas family involvement could suggest highest scores for performance-related workload and overall effort level. In the adjusted model, agriculture/fishing perceived workload may be associated with longer daily working time (b = 1.69; 95% CI: 0.82 to 2.56; p < 0.001) and shorter rest time during work (b = −0.05; 95% CI: −0.08 to −0.01; p = 0.011). Perceived workload related to family involvement in the household may be associated with monthly income up to two minimum wages (b = 19.90; 95% CI: 7.78 to 32.10; p = 0.001). The adjusted R² values were 17.3% and 6.7%, respectively. Conclusions: Perceived workload appears to be related to high levels in both productive and family household contexts. The findings might contribute to providing analytical support for future discussions on nursing care organization in Primary Health Care, potentially by considering working conditions, family responsibilities, and territorial context when discussing care needs among rural and small-scale fishing workers. Full article

Dementia affects approximately 9.6% of Americans aged 65 or older, with these numbers predicted to continue to rise, making it a significant growing public health concern that physical therapists may encounter. Dementia affects a large amount of the PT patient population, yet physical therapists report reduced confidence in treating this population due to the lack of education in academia and reduced exposure to dementia care in clinical practice. This experimental pre-post test study examined the effect of the Leveraging Existing Abilities in Dementia™ training program on confidence in handling various situations and the utilization of communication and treatment strategies discussed in the LEAD™ training program when treating individuals with dementia. Eight rehabilitation providers completed the 12 h LEAD™ training program. Pre-program, post-program, and 3-month surveys were administered to capture confidence in communication, implementation strategies and dementia knowledge. (p = 0.003). At baseline, participants were unfamiliar with 5 of 10 validated dementia care practices, but by 3-month follow-up, 90% reported using these strategies at least weekly. Notable gains included intent to use the K.I.S.S. method (+73%) and spaced retrieval (+29%). Although dementia is highly prevalent, many rehabilitation providers lack confidence in dementia care due to limited training. The LEAD™ program shows potential to bridge this gap, but continued evaluation is needed to assess long-term effects on practice and patient outcomes. Full article

Wireless Internet-of-Things (IoT) data acquisition is an emerging instrumentation paradigm for nuclear and particle physics facilities, offering a flexible complement to established wired architectures based on VME, CAMAC, and OPC-UA. Despite growing deployment activity, the evidence base remains fragmented. It is spread across conference proceedings, technical notes, and journal publications in instrumentation, nuclear science, and telecommunications. This scoping review systematically maps the evidence on wireless IoT DAQ in this context, following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) framework. A structured search of IEEE Xplore, Scopus, Web of Science, and the CERN Document Server, covering publications from 2015 to 2025, identified 47 papers meeting eligibility criteria after screening. LoRaWAN^® dominates current deployments, appearing in 72% of identified systems, driven by its infrastructure independence and sub-GHz propagation characteristics suited to shielded environments. Radiation monitoring at Large-Hadron-Collider-scale facilities is the most evidence-rich application domain; cyclotron equipment health monitoring is the most active non-CERN domain. Five priority evidence gaps are identified: empirical RF propagation data for African geological formations, long-term total-ionising-dose degradation data from deployed nodes, standardised wired-to-wireless DAQ integration interfaces, sub-millisecond wireless synchronisation, and documentation of Global South facility deployments. The review is grounded in direct operational experience across ATLAS/CERN detector instrumentation, the Dolosse DAQ framework at NRF–iThemba LABS, and the proposed Paarl Africa Underground Laboratory (PAUL). Full article

Reliable state of health (SOH) and remaining useful life (RUL) estimation is essential for lithium-ion battery diagnostics, prognosis, and management across cell, module, and pack levels. Yet the reported performance metrics often remain tied to controlled cell datasets, with batteries degrading due to chemistry shifts, protocol variation, temperature changes, inconsistent and insufficient measurements, and pack-level heterogeneity. This critical review investigates what evidence is required before an SOH/RUL estimator can be considered trustworthy, transferable, and suitable for battery management system deployment. Based on a de-duplicated classified set of 176 scientific works and a supplementary evidence audit workbook, this review synthesizes model-based, machine learning, deep learning, transfer learning, physics-informed, impedance-based, thermographic, relaxation-based, and digital twin approaches through observability, robustness, uncertainty calibration, transferability, and deployment feasibility. A compact mathematical framework formalizes the health inference, domain shift, cross-fidelity degradation, calibrated uncertainty, and BMS-facing validation criteria. The analysis argues that deployment-ready battery health intelligence should be evaluated as an evidence system rather than as a point prediction task. The proposed multi-fidelity validation framework links synthetic cells, controlled aging, module (pack) testing, fleet shadow operation, and closed-loop safety-governed deployment using acceptance criteria, based on worst-domain error, calibration data, warning risk, and computational feasibility. Full article

The present study takes place in the context of the COVID-19 pandemic and the Greek economic crisis, in which the health systems reached their limit and the physical and psychological exhaustion of professionals increased, testing supportive leadership in hospitals. An ex post facto, descriptive, and correlational study was designed, with non-probabilistic sampling, applied to 741 health professionals from public and private hospitals located in Attica and Piraeus. An 18-item ad hoc questionnaire was used, validated through an exploratory factor analysis (KMO = 0.805; 4 dimensions) and with a high reliability (α = 0.87). The staff showed a moderately positive assessment of the leadership and the supervisor dynamics, but a low enjoyment of work during the crisis. The hypothesis of generalized stress was discarded, with differences found according to gender (more conflict and less recognition perceived by women) and age (more conflicts between the supervisors and younger staff), without important differences according to level of education or work position. It can be concluded that support, psychological capital, and work relations, appeared as relatively independent constructs, modulated by organizational and personal factors, which underlines the need for specific interventions oriented towards the well-being and recognition of health professionals in contexts of crisis. Full article

Consumer smartwatches are increasingly used to monitor health, physical activity, rehabilitation, and performance in real-world environments. Although these devices provide continuous and scalable data, many user-facing outputs are not direct physiological measurements, but estimates generated from sensor signals, proprietary algorithms, user characteristics, and contextual assumptions. This review article provides a practical framework for evaluating smartwatch-derived metrics by distinguishing between relatively direct sensor measurements and higher-level algorithmic outputs. We review how common and emerging metrics are generated, including cardiovascular measures, energy expenditure, aerobic capacity, sleep and readiness scores, body composition, movement mechanics, cuffless blood pressure, sweat loss and hydration, and non-invasive glucose monitoring. Across these domains, validity varies substantially by device, algorithm, population, activity type, environment, and intended application. Smartwatch-derived data may be most useful for tracking within-person trends and complementing laboratory, clinical, or self-reported assessments, but caution is warranted when using these outputs for precise physiological quantification, diagnostic classification, or cross-device comparisons. Future progress will require stronger validation frameworks, greater algorithmic transparency, standardized reporting, harmonized data infrastructure, and careful alignment between wearable metrics and meaningful health, rehabilitation, and performance decisions. Full article