Search Results (980)

This study compared velocity-based training (VBT) with percentage-based training (PBT) on acceleration (30-m sprint) and explosive power in high school triple jump athletes. Twelve male national-level athletes were randomized (1:1, concealed allocation; blinded assessors) to VBT (n = 6) or PBT (n = 6). Both groups completed identical lower-body resistance training three times per week for eight weeks; the VBT group additionally received real-time barbell-velocity feedback with velocity-loss (VL) based set termination (15–20%). Performance was assessed using 30-m sprint, standing long jump (SLJ), standing triple jump (STJ), and vertical jump (VJ) at pre- and post-test. Statistical analysis included baseline-adjusted ANCOVA and effect sizes (Hedges’ g). VBT improved 30-m sprint (−1.08%, d = 0.89), SLJ (+2.07%, d = 1.02), STJ (+1.64%, d = 0.63), and VJ (+6.01%, d = 1.39; all p < 0.001). PBT also improved SLJ (+1.03%, d = 0.69; p < 0.001) and showed a moderate, statistically significant within-group gain in STJ (+0.56%, d = 0.72; p = 0.001), while improvements in 30-m sprint and VJ were modest. Between-group effects favored VBT across all outcomes. These preliminary findings suggest that VBT may provide more targeted neuromuscular adaptations than PBT, particularly in explosive movements relevant to triple jump performance. However, due to the modest sample size and limited precision, the results should be interpreted with caution and confirmed in larger, adequately powered randomized trials. Nevertheless, this study offers practical insight into load prescription for youth jump athletes and represents one of the first randomized trials to directly compare VBT and PBT in this population. Full article

Objectives: This study aims to assess differences in analgesia prescribing in UK primary care between individuals with osteoarthritis who have a recorded exposure to cannabis use and those who do not. Methods: This population-based retrospective cohort study included opioid-naïve patients with osteoarthritis (aged 25–85 years) who were active in Clinical Practice Research Datalink Aurum between 1 January 1995 and 15 December 2023. Patients with osteoarthritis who had current or historic cannabis use recorded were matched to two unexposed individuals by age, sex, smoking status, and health authority. Patients were followed up to assess prescriptions of analgesia. Cox regression was performed adjusted for age, sex, and ethnicity. Results: 662 exposed patients were matched to 1319 unexposed patients. Cannabis-exposed individuals were more likely to be prescribed opioids (adjusted hazard ratio (HR): 2.06; 95% confidence interval (CI): 1.74–2.43; p < 0.001), gabapentinoids (HR: 3.31; 95% CI: 2.34–4.67; p < 0.001), non-steroidal anti-inflammatory drugs (HR: 1.99; 95% CI: 1.72–2.31; p < 0.001), tricyclic antidepressants (HR: 2.64; 95% CI: 2.03–3.44; p < 0.001), other antidepressants (HR: 7.22; 95% CI: 5.24–9.94; p < 0.001), and paracetamol (HR: 3.30; 95% CI: 2.43–4.48; p < 0.001). Conclusions: This study suggests there is an association between coded exposure to cannabis in UK primary care records and increased prescribing of analgesia. Given the relative scarcity of recorded cannabis use relative to its prevalence in the general population, these findings must be interpreted cautiously. The increased hazard of using analgesia and mortality within the cannabis-exposed cohort may be confounded by socioeconomic status and a higher likelihood of coding cannabis use in those experiencing adverse effects after consumption or cannabis misuse disorder. Full article

Background and Objectives: Neonates and children are at high risk of medication errors (ME) with intravenous (IV) infusion therapies, particularly when strategies such as the “rule of six” with individualized, weight-based concentrations are used. Standard concentrations (SCs) have been proposed to reduce variability, improve safety, and facilitate the use of electronic prescribing and smart infusion technologies. The impact of SCs for continuous IV infusions on ME rates in neonatal and pediatric settings was systematically evaluated. Methods: A systematic review was conducted in MEDLINE, Embase and CINAHL (database inception-August 2025) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies implementing SCs for neonatal or pediatric IV infusions and measuring outcomes referring to ME rates were included. The relative risk reduction/increase in MEs was calculated. Results: Five uncontrolled before-after studies published between 2005 and 2020 were included. The relative risk reductions ranged from 41.2% to 95.1% for overall ME and from 49.7% to 100% for selected error types. In two studies, the relative risk for two error types (paper-generated prescriptions, administration) increased after implementing SCs. Reviewed benefits included decreased calculation and preparation errors, reduced medication process times, improved workflow efficiency and high staff satisfaction. Conclusions: SCs may contribute to safer IV infusion practice in the neonatal and pediatric setting, especially combined with smart technologies and training. However, current evidence is limited and heterogeneous. Larger, prospective experimental studies are needed to confirm their long-term impact on pediatric ME rates. Full article

Background: While the positive relationship between mental health and physical activity (PA) is well established, numerous barriers are reported. This study analyzed PA levels and associated barriers in young people attending a national child and adolescent mental health service using a quantitatively driven mixed methods design. Methods: From contacted patient families (n = 1284) meeting inclusion criteria, 23.67% (n = 304; age 12 to 18 years) completed a questionnaire (quantitative component/supplementary qualitative component). Statistical tests and thematic analysis were used to interpret data. Results: 57.24% (n = 174) of participants practiced PA/sport. Those in a sporting discipline did more PA overall, and males were almost twice as likely (OR = 1.98) to do PA/sports than females. PA levels were significantly different across mental disorder groups (highest in personality disorders and related traits, and lowest in disruptive behavioral or dissocial disorders). Participants supported the positive association between mental health and athletic performance, including the use of exercise prescriptions. Barriers to PA included excessive screentime, reduced mental health support/awareness, lack of appropriate facilities, financial difficulties, etc. Conclusion: Further research is needed. However, such results will serve to inform the development of the first documented sport mental health clinic for young people. Full article

Background/Objectives: Type 2 diabetes (T2D) and chronic kidney disease (CKD) frequently coexist in older adults. Sodium–glucose cotransporter-2 inhibitors (SGLT2i) are recommended for renal and heart protection, yet their use in routine care remains inconsistent. We aimed to investigate differences in SGLT2i prescribing between regional and university hospital settings and assess whether such disparities persist after accounting for patient characteristics. Methods: In this retrospective analysis, patients were stratified by follow-up site (regional vs. university hospital). The primary outcome was SGLT2i use. Logistic regression models were adjusted for strong determinants of prescribing decisions, including age, sex, hypertension, dyslipidemia, heart failure, and estimated glomerular filtration rate. We tested the robustness of the results using additional analyses, including exclusion of frail patients and adjustment with propensity score methods, such as matching and inverse probability weighting (IPTW). Results: The study included 135 patients, of whom 80 were followed at the regional hospital and 55 at the university hospital. SGLT2i use was significantly lower in the regional setting (27.5% vs. 63.6%, p < 0.001). In adjusted models, university follow-up remained strongly associated with SGLT2i prescription [odds ratio 3.60, 95% confidence interval (CI) 1.61–8.03, p = 0.0018]. IPTW demonstrated 4.40-fold higher odds of SGLT2i use in the university hospital setting (95% CI 2.07–9.36, p < 0.001). Conclusions: These findings indicate that the lower use of SGLT2i among older adults with T2D and CKD followed in regional hospitals may reflect patterns consistent with clinical inertia, underscoring the importance of efforts to promote equitable and guideline-aligned prescribing practices across levels of care. Full article

Background: Accurate assessment of aerobic capacity is essential for performance monitoring in masters athletes, particularly in high-intensity team sports. The objective of this study was to evaluate the validity and agreement of three indirect maximal oxygen uptake (VO₂max) protocols (Åstrand–Ryhming, YMCA, and Polar OwnIndex Fitness test) against the gold-standard cardiopulmonary exercise testing (CPET) in masters basketball players. Methods: A cross-sectional comparative study included 50 male masters basketball players (aged 51–81 years, M = 64.3 ± 7.9). Validity was determined by comparing results from the three indirect protocols to direct VO₂max measurement via CPET. Agreement was assessed using Pearson correlations (r), systematic error, mean absolute error (MAE), and Bland–Altman limits of agreement. Results: The Åstrand–Ryhming test and YMCA tests showed the closest agreement with CPET (systematic error < 4%, MAE ≈ 17–18%, r > 0.50). The Polar OwnIndex test substantially overestimated VO₂max (mean error ≈ 30%, MAE = 32%). The Åstrand–Ryhming test at low workload yielded the strongest correlation (r = 0.75). Conclusions: The Åstrand–Ryhming and YMCA submaximal tests demonstrated acceptable validity and low systematic bias for estimating VO₂max in masters basketball players, positioning them as practical alternatives to CPET. Conversely, the Polar OwnIndex test showed poor agreement and clinically significant overestimation. These findings support the use of submaximal cycling protocols for fitness monitoring and tailored training prescription in this specific older athlete population. Future longitudinal research is warranted to confirm their ability to track fitness changes over time in this population. Full article

Background/Objectives: Chronic pain conditions are common among older residents in long-term care facilities (LTCFs), often leading to increased demand for analgesic drugs. Despite this, pain is frequently underdiagnosed and undertreated, especially in individuals with cognitive impairments such as dementia. Both underuse and overuse of analgesics remain a challenge in LTCFs, affecting patient outcomes and quality of life. This systematic review aimed to identify patient- and facility-level factors associated with variation in analgesic use in LTCFs. Methods: This review followed PRISMA guidelines. A comprehensive literature search was conducted in PubMed, CINAHL, Cochrane Library, and Scopus for studies published between 2013 and 2024. Eligible studies were focused on adults aged ≥ 60 years in LTCFs and examined patient and facility factors related to analgesic prescription. Risk of bias was assessed independently by two reviewers using STROBE, JBI, and MMAT tools. Disagreements were resolved by a third reviewer. Results: A total of 6266 studies were retrieved; 13 papers met the eligibility criteria after screening. Dementia was the most frequently reported factor associated with lower analgesic prescribing, largely due to difficulties in assessing pain and communication barriers. Other patient-related factors included pain severity and comorbidities. Facility-level factors such as staffing levels, staff qualifications, and facility size were also associated with variation in prescribing practices. Conclusions: Dementia highly impacts pain management due to assessment and communication challenges. Improved pain assessment tools and staff training are needed to recognize pain in cognitively impaired residents and ensure appropriate analgesic use in LTCFs. Full article

Variable Rate Seeding (VRS) in soybean (Glycine max [L.] Merr.) cultivation is a critical strategy for managing soil spatial variability, which often constrains yield. However, conventional practices that increase plant density in low-yield zones to compensate for poor fertility may unintentionally intensify intraspecific competition for already limited resources. This study addresses the need for a mechanistically sound basis for VRS prescriptions that moves beyond this counterproductive assumption. Field experiments were conducted in the Cerrado region of Brazil to evaluate different soybean population densities within management zones (MZs) delineated according to Liebig’s Law of the Minimum. This approach identified soil potassium (K) as the most growth-limiting nutrient and was used to define MZs representing distinct yield potentials. Three seeding densities were tested, Low (200,000 seeds ha⁻¹), Medium (240,000 seeds ha⁻¹), and High (280,000 seeds ha⁻¹), with particular emphasis on comparing the medium and high populations in potassium-limited zones. Results revealed that, contrary to the conventional strategy, increasing the soybean population from medium to high in low-fertility (low-K) MZs significantly decreased grain yield. This yield reduction was attributed to intensified intraspecific competition, which promoted excessive vegetative growth (increased plant height) at the expense of root development and photosynthetic efficiency. Notably, maintaining a moderate population (240,000 seeds ha⁻¹) in these low-fertility zones produced yields statistically equivalent to those in higher-fertility areas. These findings demonstrate that applying Liebig’s Law of the Minimum to identify the most limiting factor provides a robust, mechanistically sound foundation for developing VRS prescriptions. For nutrient-limited zones, the optimal and most resilient strategy is not to increase sowing density but to maintain a moderate population that balances yield potential with resource availability. Future research should investigate the phenotypic plasticity of different cultivars under this VRS strategy and assess its economic viability at a commercial scale. Full article

Early diagnosis of pediatric flatfoot is critical to provide effective and timely orthotic intervention to prevent long-term complications. Current methods like manual measurements or three-dimensional (3D) scanning are often not ideal for rapid screening. This study addresses this gap by developing a regression model to predict foot arch height (AH) among Chinese primary schoolchildren by using simple two-dimensional (2D) footprint parameters, thus enabling orthosis prescription in an accessible and timely manner. A correlational study is conducted with 57 Hong Kong children who are 8–12 years old with flatfeet. Anthropometric footprint measurements, including four footprint indexes, Clarke’s Angle (CA), Chippaux–Smirak Index (CSI), Staheli Index (SI), and Sztriter–Godunov index (KY) are obtained from 2D footprints, whereas the arch height (AH) is measured by a caliper. One-way ANOVA is used to identify the measurements associated with flatfoot severity. A stepwise regression analysis is also used to determine the key footprint predictors of AH. The results show that the footprint indexes, heel width, ball width, medial ball length, arch depth and arch breadth significantly differentiated flatfoot severity. The stepwise regression model explains 44% of the variance by identifying the CA, heel width (HW) and arch depth (AD) as the strongest predictors of AH. The CA, HW and AD measured from the 2D footprints can serve as practical predictors of AH in Chinese flatfooted children. This study offers a transformative, accessible tool for pediatric flatfoot screening. Unlike resource-intensive 3D scanning or clinical assessments, our approach uses simple 2D footprints to estimate AH. This enables rapid, preliminary screening in diverse settings, empowering individuals to identify potential issues and seek timely professional evaluation. By democratizing access to early detection, it streamlines referrals, reduces unnecessary complex assessments, and facilitates earlier, personalized orthotic intervention for improved long-term foot health. Full article

The increasing complexity of urban environments has exposed the limitations of prescriptive approaches in urban design and planning, highlighting the need for more adaptive, data-informed, and methodologically rigorous processes. Evidence-Based Design and Planning (EBDP) offers a promising response by embedding evidence as a continuous and iterative element throughout design and decision-making. Yet, its adoption in practice remains uneven, constrained by project limitations, data availability, and the challenge of operationalising analytical workflows. This paper addresses these challenges by proposing a transferable framework for EBDP, developed through the review of six realised projects, ranging from public space enhancements to metropolitan masterplans and policy studies, undertaken in both professional practice and academic research. Examined alongside existing theoretical models, these cases revealed recurring patterns that informed the framework. The resulting model consists of four interlinked phases: clarification and evidence-based project definition; integration of an evidence base through analysis and modelling; generation of options synthesising diverse evidence; and evaluations to guide adaptation and decision-making. Rather than a linear or prescriptive sequence of stages, the framework uses iteration and flexible feedback processes anchored by a unifying Hybrid Spatial Model to synthesise evidence, support the generation of design options, and underpin engagement and feedback processes considering project objectives. This paper offers a systematic yet flexible framework for EBDP that can be adapted across scales, project types, and contexts. Full article

Diabetes mellitus increases the risk of developing coronary artery disease, stroke, aortic disease, heart failure, atrial fibrillation, and peripheral arterial disease. This condition negatively impacts prognosis by increasing the risk of future cardiovascular (CV) events. Patients with type 2 diabetes mellitus need a comprehensive and personalized assessment and definition of the CV risk profile. In very high-risk individuals, special attention is required due to the high risk of adverse events despite appropriate management and treatment. Key interventions to reduce this risk include CV prevention and cardiac rehabilitation. Traditional and non-traditional CV risk factor management, dietary modifications, regular physical activity, aerobic and resistance exercise training, psychosocial and frailty management, optimal pharmacological therapy, and investigation of comorbidities are recommended to reduce the development of CV disease and mortality. Therefore, our manuscript provides updated and critical evidence on the comprehensive management of patients with type 2 diabetes mellitus in clinical practice from the perspective of CV prevention and cardiac rehabilitation, with a focus on individuals at very high risk. Further, practical guidance on individualizing exercise prescriptions based on patient-specific risk profiles and comorbid conditions is provided. Full article

This paper presents a comprehensive design framework for Enterprise Architecture aimed at facilitating decision-driven analytics in smart factories. The motivation behind this research lies in challenges faced by manufacturing companies, such as skilled labor shortages and increasing global competition, alongside the imperative for sustainable production. This journal provides a novel approach for designing and documenting prescriptive analytics use cases in manufacturing environments. The framework addresses the need for effective integration of advanced data analytics and prescriptive analytics solutions within existing production environments, thereby enhancing operational efficiency and decision-making processes. A Design Science Research approach is used to iteratively derive a framework based on stakeholder needs and activities along the prescriptive analytics use case development cycle. The resulting framework is demonstrated and evaluated in an IoT Factory setup in a research facility. From a practical perspective, the framework supports manufacturing companies in systematically designing prescriptive analytics use cases. From a research perspective, it contributes to the body of knowledge on Enterprise Architecture Management (EAM) by operationalizing the design of prescriptive analytics use cases in manufacturing contexts. The main contributions of this study include the development of a framework that supports the planning, design, and integration of prescriptive analytics use cases. This framework fosters interdisciplinary collaboration and aids in managing the complexity of data-driven projects. Full article

Acute pain is a significant clinical challenge in primary and secondary care. If inadequately managed, acute pain is a major risk factor for the development of chronic postsurgical pain and persistent postoperative opioid use. In this perspective article, we offer the authors’ viewpoints informed by selective literature with the aim of helping identify avenues to improve the quality and safety of acute pain management. Current evidence in the quality and safety of pain management shows that the role of primary care staff in education, follow-up, and tapering remains largely unaddressed, while patient perspectives and experiences reveal gaps in communication, stigma, and trust. Screening tools, guidelines, and strategies to reduce variations in the prescription and use of opioids remain inconsistently developed. In conclusion, if pain is multifaceted and should be approached in a multidisciplinary way, strong integration between primary and secondary care is essential. Communication with primary care, tapering, or referral should be facilitated. Patient experience should receive more attention, and future studies should focus on implementing guidelines and multidisciplinary guidance, as well as providing continuous feedback to clinicians on their practice and outcomes. Full article

Holy Week, the most significant period of the Christian liturgical year, was marked by solemn and complex rituals enacted within the sacred spaces of medieval religious communities. In the case of Cistercian female monasteries, scholarly attention has largely centered on Easter dramatic representations such as the Depositio or the Visitatio Sepulchri, while the official liturgy—Hours, Masses, processions, and the official rituals of the Easter Triduum—has remained comparatively understudied. This article addresses that gap by examining the Holy Week liturgy as performed by the Cistercian nuns of Lichtenthal (Baden-Baden, Germany), on the basis of an exceptional and understudied source: the original Ecclesiastica Officia (mid-13th century, Karlsruhe, Badisches Generallandesarchiv, 65/323). Containing comprehensive normative prescriptions for the Easter liturgy adapted for the Lichtenthal community, this manuscript enables a detailed reconstruction of the nuns’ primary collective experiences during these days. The study brings together evidence from architecture, works of art, and liturgical books, while integrating insights from sensory studies, in order to underscore the bodily and multi-sensory dimensions of the rituals. In doing so, it highlights the implications of the nuns’ active participation in Holy Week ceremonies and contributes to a deeper understanding of medieval female religious ritual experience, challenging conventional notions of enclosure and liturgical practice. Full article

Research on big data analytics (BDA) and supply chains often inventories “capabilities” but rarely explains how firms progress through adoption—or how governance over data and related resources shapes resilience outcomes. Drawing on 16 semi-structured interviews with senior managers in the manufacturing sector, we analyze organizational practices around data, analytics, and decision-making and synthesize a governed-adoption process framework. The framework specifies how five governance levers—ownership, standards, stewardship, access, lineage—operate differentially across four adoption gates (data plumbing—descriptive monitoring—predictive alerting—prescriptive decisioning). To move beyond staged descriptions, we make the underlying generative mechanisms explicit—Comparability, Explainability, Authorization, Fidelity, Executability—and link them to dynamic-capability micro foundations (sensing, seizing, reconfiguring) via decision-latency outcomes (“resilience timers”: Time-to-Detect, Time-to-Decide, Time-to-Reconfigure, Time-to-Recover). Brief deviant-case contrasts (e.g., notification without action; dashboards without owners) clarify boundary conditions under which governance enables or impedes resilient action. We also state concise, testable propositions (e.g., standards+lineage as a necessary condition for improving Time-to-Detect; ownership+access as necessary for improving Time-to-Decide) and provide gate exit-criteria to support evaluation and future comparative tests. Claims are bounded to analytic generalization from a single-country, manufacturing-sector qualitative sample; we make no assertion of statistical validation. Practically, the framework prioritizes governance work ahead of tool spend, helping organizations convert dashboards into repeatable decisions at speed. Full article