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When means and standard deviations are an incomplete summary of a continuous variable: problems, solutions, and utilising the reference ranges to check normality
Full text linkThe mean and standard deviation are commonly used to summarise continuous data, often without regard for the distribution of the data. For data in a non-normal distribution, the median and interquartile interval are often more appropriate. This article outlines circumstances where the mean and standard deviation alone are insufficient summary variables, and provides a simple appraisal method for reviewers without the raw data
The journey to diagnosis for patients with CIDP: results from a real-world international survey
Full text linkIntroduction: Chronic Inflammatory Demyelinating Polyradiculoneuropathy (CIDP) is a rare autoimmune disorder affecting the peripheral nerves, typically characterized by muscle weakness and sensory deficits. This study seeks to describe CIDP patients’ journey to diagnosis alongside factors influencing misdiagnosis and time to diagnosis. Methods: We analyzed demographics and diagnostic data reported by neurologists and their patients in Adelphi’s CIDP Disease Specific Programme™. This digital, multinational real-world survey was held in the UK, France, Germany, Italy and Spain between September 2022 and April 2023 ( n = 542). Results: Mean (SD) age was 54.0 (12.4) years; 62% of patients were male. Half of the patients reported at least one comorbidity, with anxiety, depression and diabetes being the most common. The mean (SD) number of diagnostic procedures undergone per patient was 19.6 (9.4). An electromyogram and nerve conduction study (98%), complete blood count (82%) and administration of anti-ganglioside antibodies (78%) were carried out most frequently. Most patients had been diagnosed with typical CIDP (68%) and 37% had been misdiagnosed at least once. The most common misdiagnosis was Guillain-Barré syndrome, in 37% of cases. No significant associations were found between misdiagnosis and the variables sex, disease severity at symptom onset, age category, BMI or CIDP subtype. The median (Q1 - Q3) time between symptom onset and diagnosis was 7.0 (3.2–13.0) months. A multiple linear analysis on the log-transform of the time to diagnosis indicated that patients with a long time to diagnosis more often presented with mild symptoms at onset, had variant CIDP and had been misdiagnosed. Conclusion: Median time to diagnosis for CIDP patients was 7 months; over a third had at some point been misdiagnosed. Mild symptoms, having variant CIDP and having been misdiagnosed were associated with longer time to diagnosis. Further research into the causes of diagnostic delay and the impact of late diagnosis and treatment is needed
Towards a Holistic Understanding of Digital Innovation: A Multidimensional Approach
No full textThis study develops and empirically validates an integrative model explaining how firms achieve digital innovation through the interplay among digital strategy, absorptive capacity, digital technology deployment, and environmental dynamism. Drawing on the content-context-process-outcome framework, digital strategy provides the guiding content; absorptive capacity and environmental dynamism act as contextual enablers; and digital technology deployment functions as the central process driving innovation outcomes. Survey data from 250 Chinese firms were analyzed using partial least squares structural equation modeling (PLS-SEM) and contextualized and externally validated through cross-case and cross-industry validation. The findings reveal an inverted U-shaped relationship between digital technology deployment and innovation, challenging the linear assumption of prior research. While deployment is essential, overinvestment without strategic alignment leads to diminishing returns, underscoring the need for strategic coherence and absorptive alignment. Digital strategy and absorptive capacity directly and indirectly enhance innovation through digital technology deployment, while environmental dynamism amplifies the strategic-innovation linkage. Theoretically, the study contributes to the engineering management literature by advancing a holistic, dynamic, and nonlinear understanding of digital innovation as an optimization and orchestration process rather than a purely technological one. It offers a generalizable framework that strengthens integrative and system-oriented perspectives in engineering management research
Women Entrepreneurship in the Age of AI and ESG: Micro- and Macro-Level Drivers of Adoption
Full text linkArtificial intelligence (AI) holds significant potential to advance women entrepreneurship and environmental, social, and governance (ESG) goals, yet adoption in emerging markets is constrained by both individual and institutional barriers. This study applies a two-panel Delphi method with 11 women entrepreneurs (Study 1) and 18 institutional experts (Study 2) to explore micro- and macro-level drivers of AI adoption. Across three rounds, participants rated competences, motivations, risks and institutional factors, with consensus assessed through Kendall's. Results show that women entrepreneurs view AI as a values-driven tool for sustainability but face challenges in skills, trust and resources, while institutional experts highlight regulatory frameworks, policy support and cultural norms as decisive enablers or barriers. The study contributes to Institutional Theory by integrating micro- and macro-level perspectives and offers practical insights for designing gender-sensitive policies and support mechanisms. Future research should extend these findings through longitudinal and cross-country analyses of women-led ESG ventures
Mapping live music urban ecologies – potential and challenges.
No full textMusic makes a significant economic contribution and is a source of cultural sustenance across cities and regions (EC 2006; IFPI-Oxford Economics, 2020), drawing attention - and bringing both economic and cultural capital - to localities. Each regional context produces a complex live music ecosystem of musical and non-musical actors and concerns - from venues, promoters and musicians to licensing, health, policing, and transport. This chapter explores the contextual and theoretical aspects of researching live music in urban spaces, through use of the live music ‘ecologies’ (Behr et al. 2016). It provides the background to, and an overview of, research and knowledge exchange in this area with an aim of evaluating them from the perspective of their potential and challenges in informing music industries and facilitating evidence-based policymaking that combines the interests of the live music sector, and broader night-time economy, with their urban and civic contexts
Declaring Worldviews in SSM for Sustainability & Community Learning
Full text linkFor over fifty years, Soft Systems ideas and the Soft Systems Methodology (SSM) have played a pivotal role in understanding various problem situations and initiating action. Often tackling the grandest challenges of our time, SSM will retain continued relevance in helping decision-makers address sustainability challenges within organisations and their communities. In this paper, we are concerned with the meaningful co-creation of sustainable value through community-based learning using SSM. More specifically, recognising that a sustainability paradigm, characterised by the need to create a just and safe space for humanity to thrive within the means of a living planet (as called for by Raworth, 2017), is often marginalised or overlooked. This paradigm presents us with an ethical imperative, complex and messy challenges/issues, and a set of ideals (articulated in the United Nations Sustainable Development Goals) that are significantly off track. This paper employs a variation of the Delphi method, drawing on the authors’ collective interest and experience in applying SSM in communities, to propose a double-loop learning cycle to explore the underlying assumptions of our worldviews and mental models within communities. We suggest that an SSM learning cycle can be enhanced by initiating conversations on relevant models for sustainability (such as Doughnut Economics, UN SDGs, and the principles for a Circular Economy), to find common ground for triggering new learning. This idea is contextualised and proposed as the value(s)-action gap phenomenon, which can help explain the difference between an individual, an organisation, and/or a community's intention(s) and their actual action(s).In doing so, find common ground, shift to higher levels of systems consciousness from an ego-centric to an ecosystem level of awareness, engage communities, and take an intergenerational perspective. We suggest that incorporating a double-loop learning cycle into SSM can support organisations and their communities in putting shared values into meaningful action
Reno-protective effects of statins among patients with chronic kidney disease in Hong Kong: a target trial emulation
Full text linkBackground: Many existing randomised controlled trials lack sufficient power to assess primary kidney outcomes. This study aimed to evaluate whether statin therapy offers a clinically meaningful reno-protective effect in patients with chronic kidney disease (CKD). Methods: In this retrospective cohort study, electronic health records in Hong Kong were extracted to perform sequential target trial emulation. Eligible adults (aged 18+ years) with CKD who met the indication for statin initiation between Jan 1, 2008 and Dec 31, 2017 were included; those with history of estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m2 were excluded. Participants were categorised as statin initiators or non-initiators at each calendar month during inclusion period, where statin initiators were propensity score-matched with non-initiators. Follow-up data were collected for all participants until the occurrence of outcomes, death, loss to follow-up (2 years after last records), or the end of data availability (Dec 31, 2022), whichever occurred first. The hazard ratio (HR) of all-cause mortality, eGFR deterioration (eGFR <15 mL/min/1.73 m2, ≥30% eGFR decline, and ≥50% eGFR decline) and composite outcomes (all-cause mortality, eGFR <15 mL/min/1.73 m2, and ≥50% eGFR decline) was estimated by pooled logistic regression using intention-to-treat (ITT) and per-protocol (PP) approach. Findings: 1,437,014 eligible person-trials were identified (statin initiators n = 30,907; non-initiators n = 1,406,107), from which 30,892 statin initiators and 108,380 non-initiators were included after propensity-score matching. Relative to non-initiators, significant risk reduction was found among statin initiators in all-cause mortality (HR [95% confidence interval (CI)], ITT: 0.97 [0.95–0.98]; PP: 0.91 [0.88–0.93]), progression to eGFR <15 mL/min/1.73 m2 (ITT: 0.91 [0.89–0.93]; PP: 0.77 [0.74–0.80]), ≥50% eGFR decline (ITT: 0.95 [0.93–0.98]; PP: 0.89 [0.84–0.93]), and composite outcomes (ITT: 0.96 [0.94–0.97]; PP: 0.90 [0.88–0.92]). Statin therapy initiation was also associated significantly with reduced risk of ≥30% eGFR decline using PP approach (0.94 [0.92–0.96]). Interpretation: Over a 10-year follow-up period, initiating statin therapy in patients with CKD was associated with a small yet significant decrease in all-cause mortality and a modest reno-protective effect. Future research should aim to clarify the effects of statin intensity, duration, and adherence
From Pre-Swelling to Performance Enhancement: Mechanisms and Effects of an Instant Ultra High-Performance Bituminous Material Modifier
Full text linkTo elucidate the modification and pre-swelling mechanisms of instant bituminous modifiers and their contribution to bituminous materials’ performance, this study investigates an instant ultra-high-performance bitumen modifier (SHVE-M). Fluorescence microscopy (FM), gel permeation chromatography (GPC), physical property tests, viscoelastic properties tests, dynamic shear rheometer (DSR), and mixture pavement performance tests were employed to systematically characterise the instant modified bitumen (SHVE-MB) and its mixture (SHVE-MBM). The results indicate that SHVE-M forms a stable “bitumen phase–polymer spherical phase” structure. ImageJ-win64 analysis revealed that SHVE-M exhibits a modifier area fraction of 46.68% and an average area fraction of 0.22‰, while SHVE-MB achieves a modifier area fraction of 17.54% and an average area fraction of 0.18‰. This morphology is supported by a large molecular size (LMS) content of 43% in SHVE-M. In terms of physical properties, the SHVE-MB (prepared via 10 min shearing) exhibited a penetration of 46.2 dmm, a softening point of 91.7 °C, and a ductility of 34.3 cm. These values are highly comparable to the conventional wet-process HVE-MB (prepared via 4 h maturation), with negligible differences of 0.5 dmm, 1.7 °C, and 1.4 cm, respectively. Quantitatively for viscoelasticity, SHVE-MB achieved a dynamic viscosity of 425,283.4 Pa·s at 60 °C and an elastic recovery rate of 92.1%, paralleling the 414,623.7 Pa·s and 93.6% of HVE-MB. Regarding mixture performance, the high-temperature dynamic stability (DS) of SHVE-MBM reached 7974 times/mm, approaching the 8256 times/mm of HVE-MBM. The water stability was excellent with a splitting tensile strength ratio (TSR) of 97.4% (vs. 98.0% for HVE-MBM). Furthermore, the low-temperature fracture toughness (KIC) reached 39.8 N/mm1.5, significantly outperforming SBS-MBM (27.9 N/mm1.5) and remaining close to HVE-MBM (43.9 N/mm1.5). These findings indicate that SHVE-MB effectively bridges the performance gap between instant and traditional high-viscosity modified bitumen, and the pre-swelling mechanism of SHVE-M is well characterized in this study
An Integrated Robust Optimization and Simulation Framework for Sustainable and Resilient Automotive Supply Chain Management
Full text linkThis study proposes an integrated decision-support framework that combines robust multi-objective optimization and discrete-event simulation to enhance sustainability and resilience in automotive supply chain management. Automotive supply chains are highly complex and exposed to significant uncertainty arising from demand fluctuations, supply disruptions, and procurement constraints, particularly in emerging economies. To address these challenges, the proposed framework incorporates mixed-integer programming with a multi-objective formulation to balance production, supply, holding, and penalty costs. Additionally, robust optimization based on the Bertsimas–Sim approach is employed to hedge against demand uncertainty. Additionally, a discrete-event simulation model is developed to validate and refine the optimization results under stochastic operating conditions, and to assess the practical performance of the proposed strategies. The framework is applied to a real-world automotive case study, where flexible production policies, including fractional production and urgent procurement, are evaluated in terms of their economic and social sustainability impacts. The results demonstrate that integrating robust optimization with simulation improves supply chain resilience, reduces vulnerability to uncertainty, and supports more sustainable operational decision-making. The proposed approach provides valuable insights for managers seeking to design resilient and sustainable automotive supply chains under uncertain environments
A Single-Phase AC Chopper with Grounded-Load and Robust Switching Strategy
Full text linkA robust single-phase AC–AC chopper topology with a grounded load is proposed for compact, high-efficiency power conversion. The converter comprises one P-type and one N-type AC switching-cell leg, enabling four-quadrant operation while simultaneously being inherently immune to shoot-through conditions. The legs are connected to a grounded load via a coupled inductor, and together with a three-step switching strategy, form a topology which is tolerant to supply voltage polarity detection errors of at least ±20° around the mains zero-crossing, without the need for large, bulky snubbers. An analytic method is presented for sizing the current-limiting inductors, which accounts for the effects of circuit parasitics. SPICE simulations and measurements from a 1.5 kW GaN-based prototype validate the design, demonstrating low output voltage THD and high robustness. The converter is suitable for space-constrained, high-performance AC–AC conversion applications
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