Pragmatic Framework Research Articles

Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening

Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.

Drivers of vascular growth and remodeling: A computational framework to promote benign adaptation in the Ross procedure

In the sixties, Dr Donald Ross designed a surgical solution for young patients with aortic valve disease by using the patients’ own pulmonary valve. The Ross procedure is the only aortic valve replacement technique that can restore long-term survival and preserve quality of life. The main failure mode of the Ross procedure is wall dilatation, potentially leading to valve regurgitation and leakage. Dilatation occurs due to the inability of the pulmonary autograft to adapt to the sudden increase in loading when exposing to aortic pressures. Previous experimental data has shown that a permanent external support wrapped around the artery can prevent the acute dilatation of the arterial wall. However, the textile support leads to stress-shielding phenomena due to the loss of mechanical wall compliance. We present a pragmatic and modular computational framework of arterial growth and remodeling predicting the long-term outcomes of cardiovascular tissue adaptation, with and without textile wrapping. The model integrates mean, systolic and diastolic pressures and assumes the resulting wall stresses to drive the biological remodeling rules. Rather than a single mean pressure or stress deviation from the homeostatic state, we demonstrate that only pulsatile stresses can predict available experimental results. Therefore, we suggest that a biodegradable external support could induce benign remodeling in the Ross procedure. Indeed, a biodegradable textile wrapped around the autograft fulfills the trade-off between prevention of acute dilatation on the one hand and recovery of arterial wall compliance on the other hand. After further validation, the computational framework can set the basis for the development of an actual biodegradable external support for the Ross procedure with optimized polymer mechanical properties and degradation behavior.

Field dynamics as context – A multi-perspective combined analysis of the effects of context on entrepreneurship

Addressing the growing need for nuanced understandings of entrepreneurial contexts, this article presents a multifaceted pragmatic framework for scrutinising the ‘field of entrepreneurship’ and its associated dynamics. Drawing on Bourdieu's theory of practice and the institutional logics perspective, we introduce the concept of the field as a mid-level analytical lens—positioned between micro and macro perspectives—that captures the complex interplay of agency and structure in entrepreneurial activity. Our conceptualisation of the field enables the dissection of structural logics and actor dispositions, alongside the institutional processes that shape the entrepreneurial landscape. In response to calls for innovative methodologies in entrepreneurship research, we propose a combined analytical approach to unpack the layered complexities of entrepreneurial contexts, from individual actors to broader institutional influences. The utilisation of this ‘field of entrepreneurship’ concept, with a particular focus on field dynamics, serves as a pragmatic analytical unit, contributing to the broader discourse by balancing simplicity, accuracy, and generalisability. This research consequently offers a novel methodological avenue for exploring what facilitates or impedes entrepreneurial activity within varying contexts.

Ethical considerations in closed loop deep brain stimulation

BackgroundClosed-loop deep brain stimulation (DBS) uses feedback to infer a clinical state and adjust stimulation accordingly. This novel mechanism has several potential advantages over conventional DBS including reducing stimulation-induced side effects, improving battery longevity, and alleviating symptoms not optimally treated with standard protocols. However, several ethical challenges may arise with the implementation of this technology, particularly with respect to clinical decision making. ObjectiveTo discuss potential ethical and clinical dilemmas encountered in using closed-loop DBS for neurological and psychiatric disorders. MethodsThe relevant literature is reviewed and supplemented with discussion of ethically challenging clinical scenarios. We outline an ethical framework for addressing these issues and provide practical recommendations for clinicians and researchers. ResultsEthical considerations in closed-loop DBS revolve around five key principles: 1) risk/benefit analysis; 2) inclusion and exclusion criteria; 3) respect for patient autonomy; 4) quality of life and patient benefit; and 5) concerns associated with recording neural activity. Conclusion(s)Developing and implementing a pragmatic framework for ethical considerations in closed-loop DBS will be critical as this technology is utilized in patients with both neurologic and psychiatric indications.

Heart Failure Remote Monitoring: A Review and Implementation How-To.

Heart failure (HF) is a significant clinical and financial burden worldwide. Remote monitoring (RM) devices capable of identifying early physiologic changes in decompensation have the potential to reduce the HF burden. However, few trials have discussed at length the practical aspects of implementing RM in real-world clinical practice. The present paper reviews current RM devices and clinical trials, focusing on patient populations, outcomes, data collection, storage, and management, and describes the implementation of an RM device in clinical practice, providing a pragmatic and adaptable framework.

A linguistic-pragmatic analysis of cat-induced deixis in cat-human interactions

The present paper contributes to the emerging field of embodied interaction. It reports on research into deictic interactions between a human and a non-human, specifically a cat, interlocutor, applying a pragmatic framework developed for human–human communicative interactions. We analyse video recordings of interactions where a cat is a deictic agent pointing the human interlocutor either to the door or the food bowl. We show that these interactions show triadic pointing, hence, focusing joint attention on a common object as a proxy for the event i.e., providing food in the bowl and opening the door. We show that the cat also checks whether the human understands her intentions and that she confirms the human's interpretation. We do not restrict ourselves to vocal communication - as is often done in human language studies -, but we examine how in cat-human communication the cat and human bodies are used to express deixis. Thus, we conceptualize deixis as an embodied interpersonal i.e., interspecies phenomenon. We show that the cat interlocutor uses her body, e.g. eyes/body/tail/ears, as well as her voice, meowing/purring, within this complex deictic interaction.

Pioneering sustainable power: Harnessing material innovations in double stage segmented thermoelectric generators for optimal 4E performance

This study presents groundbreaking advancements in sustainable power through a comprehensive exploration of double-stage segmented thermoelectric generators (DSSTEGs) optimized for efficient solar energy conversion. Specifically comparing DSSTEGs with other solar thermoelectric generator (STEG) configurations through geometry parametric optimization, we elucidate the intricate interplay between material properties and design parameters using a finite element method-driven numerical approach. The focus is on achieving 4E optimization (energy, exergy, environmental, and economic factors). Our results demonstrate that a skutterudite content of 6.17% maximizes DSSTEG performance, showcasing its superiority over conventional STEGs. The optimized DSSTEG excels with remarkable CO2 savings of 23.78 kgyr−1 and an impressive high output power of 50.08 W at the optimal skutterudite content. Moreover, the DSSTEG design demonstrates a balanced cost-effectiveness with an outstanding $0.05 per watt output, surpassing conventional STEGs' cost-efficiency. These findings offer a pragmatic framework for integrating innovative materials and optimized designs in concentrated solar energy applications, signifying a significant stride in the field of thermoelectric generators. The pivotal role of materials and design in defining and optimizing performance for enhanced solar energy conversion is highlighted, propelling the path towards a more sustainable and efficient energy future.

Environment and child well-being: A scoping review of reviews to guide policies.

Acting on social determinants is the most effective, efficient, and fairest strategy to improve population health and health equity. Because of their vulnerability and dependence, children are particularly exposed to the deleterious effects of their living environment. Taking these issues into account in the development of public policies and identifying levers for action are crucial. The objective of this scoping review of reviews is to identify the main environmental determinants on children's health and development, and their mechanisms of effect, to be addressed by public policies. We conducted a scoping review of reviews in accordance with the method developed by Arksey and O'Malley, and Levac and colleagues' methodology advancement and the PRISMA guideline. Inclusion criteria were identified with the PICos (population-phenomena of interest-context-study design) framework. We used the PubMed database and conducted a thematic analyze. Forty-seven articles were selected. Their analysis allowed us to identify five categories of interdependent environmental determinants of child health: i) urban design ii) contaminants, iii) parenting environment, iv) social conditions, v) climate change. Together and in a systemic way, they act on the health of the child. The review carried out allows us to propose a pragmatic framework for clarifying the effects of the physical, social, and economic environment on children's health and wellbeing.

UISCEmod: Open-source software for modelling water level time series in ephemeral karstic wetlands

Characterizing ephemeral karstic wetlands through hydrological modelling is key for sustainable protection of their ecosystems and to understand and mitigate the impact of flooding events. UISCEmod is a new open-source software for modelling water level time series, focused on ephemeral karstic wetlands, that requires minimal input information. UISCEmod contains both experimental and lumped hydrological models, and the calibration process is automated following a Bayesian approach. The main outputs of UISCEmod include volume, stage, inflow and outflow model time series, calibrated model parameters, and the associated uncertainties. UISCEmod was evaluated at 16 representative sites in Ireland obtaining Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) above 0.85 for both stage and volume time series for most of the sites, showing its potential for covering the need for a simple, pragmatic, and flexible framework for modelling water levels in ephemeral karstic wetlands with relatively limited input data requirements.

A Pragmatic Framework for Data-Driven Decision-Making Process in the Energy Sector: Insights from a Wind Farm Case Study

In an era of big data, organizations increasingly aim to adopt data-driven decision-making processes to enhance their performance. This paper investigates the data-driven decision-making process by developing a framework tailored for application in the energy sector. The proposed framework integrates interdisciplinary approaches to comprehensively address the “data, information, knowledge” triad, applying it to both operational and maintenance decision-making. Designed to be managerially focused rather than technically oriented, the framework aims to engage all employees, including those without technical backgrounds, enabling them to effectively contribute to the decision-making process from their respective roles. To demonstrate the practical application of the proposed framework, this paper presents a case study of an energy organization managing a wind farm project, which implemented the framework to improve its decision-making process. The case study examines how the organization identified its objectives and information needs, formulated key performance questions for each stakeholder, explicitly defined and measured the key performance indicators, employed data collection and organization methods, managed the progression from data to information to knowledge, and transformed the acquired knowledge into informed decisions. By adopting this pragmatic framework, energy organizations are anticipated to solve problems, predict trends, and discover new opportunities, thereby enhancing their efficiency and predictability.

Community and identity in environmental activism on Twitter: A discourse-based approach

Online communities play an integral role in understanding environmental activist identities. Using #climatestrikeonline tweets as a case study we discuss the benefits of applying the framework of digital pragmatics (under the umbrella of discourse analysis) to study the repositories of online media texts that share the attributes of both interpersonal and mass communication (Koteyko, Nerlich, and Hellsten 2015). Our analysis draws on two arguments central to discourse-based approaches: (1) that social meanings must be analysed across different modes (e.g., by including visuals) and (2) that analysis of digital artefacts needs to consider both their content features and the contexts in which they emerge. We demonstrate how using digital pragmatics to study networked communication about climate change can help us understand how engagement and collaboration are achieved in online communities of practice.

The Comprehensive Instructional Language Learning Model: Exploring its Feasibility and Characteristics

The necessity for a comprehensive theoretical framework is underscored, given that current theories, such as behaviorism, cognitivism, or constructivism, concentrate on distinct facets of language learning. Scholars contend that language learning and teaching necessitate a comprehensive theoretical framework. The theory under consideration is characterized as possessing descriptive, instructional, and evaluative qualities, thereby offering a pragmatic framework for practitioners in English language teaching. This article introduces a comprehensive theoretical framework for language learning that seeks to encompass all the elements inherent in language learning, namely cross-linguistic applicability, psychological adequacy, contextual variables, and a comprehensive and cooperative learning process that is initiated with input, followed by competency building, and ends with engagement. The theory is expounded upon through the utilization of the Evaluative Matrix of a Comprehensive Instructional Language Learning Theory (EMCILLT), which evaluates the various aspects of the teaching-learning experience, utilizing Grice’s maxims (1975) quantity, quality, manner, and relevance. This comprehensive model that encompasses all the aspects of the learning process serves as a basis for comprehending and delineating the intricate nature of language learning. Moreover, it assists teachers in engaging in self-evaluation of their instructional strategies and practices and/or in evaluating methods, approaches, and techniques to enhance the overall teaching-learning experience.

Integrating machine learning and environmental variables to constrain uncertainty in crop yield change projections under climate change

Robust crop yield projections under future climates are fundamental prerequisites for reliable policy formation. Both process-based crop models and statistical models are commonly used for this purpose. Process-based models tend to simplify processes, minimize the effects of extreme events, and ignore biotic pressures, while statistical models cannot deterministically capture intricate biological and physiological processes underpinning crop growth. We attempted to integrate and overcome shortcomings in both modelling frameworks by integrating the dynamic linear model (DLM) and random forest machine learning model (RF) with nine global gridded crop models (GGCM), respectively, in order to improve projections and reduce uncertainties of maize (Zea mays L.) and soybean (Glycine max [L.] Merrill) yield projections. Our results demonstrated substantial improvements in model performance accuracy by using RF in concert with GGCM across China’s maize and soybean belt. This improvement surpasses that achieved using DLM. For maize, the GGCM+RF models increased the r values from 0.15 to 0.61–0.64–0.77 and decreased nRMSE from approximately 0.20 to 0.50–0.13–0.17 compared with using GGCM alone. For soybean, the models increased r from 0.37 to 0.70–0.54–0.70 and decreased nRMSE from 0.17 to 0.35–0.17–0.20 compared with using GGCM alone. The main factors influencing maize yield changes included chilling days (CD), crop pests and diseases (CPDs), and drought, while for soybean the primary influencing factors included CPD, tropical days (based on exceeding a maximum temperature), and drought. Our approach decreased uncertainties by 33–78% for maize and by 56–68% for soybean. The main source of uncertainty for GGCM was the crop model. For GGCM+RF, the main source of uncertainty for the 2040–2069 period was the global climate model, while the main source of uncertainty for the 2070–2099 period was the climate scenario. Our results provide a novel, robust, and pragmatic framework to constrain uncertainties in order to accurately assess the impact of future climate change on crop yields. These results could be used to interpret future ensemble studies by accounting for uncertainty in crop and climate models, as well as to assess future emissions scenarios.

Winnipeg-based elementary school teachers’ perspectives on food allergy management: a qualitative analysis

BackgroundFood allergy affects 7-8% of children worldwide. Teachers supervise children in school, where most children spend their day. Yet, teachers have variable food allergy-related knowledge.ObjectiveWe aimed to identify how Winnipeg-based elementary school teachers manage food allergy and prevent food-triggered allergic reactions in their classrooms and schools.MethodsKindergarten-Grade 6 public and private school teachers, from Winnipeg, Canada, were interviewed virtually upon providing written informed consent. Interviews were recorded and transcribed verbatim. The study followed a pragmatic framework. Data were analysed via thematic analysis by multiple researchers.ResultsWe interviewed 16 teachers, who primarily identified as female (87.5%). Most teachers worked in public schools (87.5%) and, on average, had 5.8 years of teaching experience. We identified four themes within the data. Most teachers (68.9%) had direct or indirect experience with food allergy. Theme 1 described the minimal standardization and inconsistent enforcement of food allergy policies between and within schools. Teachers also had varied food allergy knowledge. Theme 2 reflected teachers’ variable confidence/perceived knowledge towards food allergy management, including feeling of stress and anxiety. Theme 3 captured the lack of standardized food allergy education for teachers, and concerns about the adequacy of the current provincial program. Theme 4 described how teachers spoke of relying on other school staff, families and students to have effective communication.ConclusionTeachers’ food allergy management was informed by their knowledge and lived experience, guided by their school policies and individualized students’ needs. Teachers identified gaps in knowledge and communication, and desired more training and resources.

Making sense of sensing homes: exploring ‘regimes of engagement’ in a smart urban energy context

ABSTRACT Visionary imaginaries of desirable ‘smart’ urban energy futures entice city governments into innovation and collaboration aimed at large-scale urbanism. As part of attending to actualizations and materializations of ‘smart’ urban imaginaries, this paper contributes to moving beyond idealized framings of smart urban publics, towards more embedded reflexive accounts of how ‘real people’ in urban contexts make sense of and reason about smart urban developments. Through a living lab intervention in Bergen, Norway, we open up a space for critical deliberation, to explore situated imaginations and geographies of smart urban futures. We analyse how people reason about their experiences with smart technological devices, expanding on existing practice-oriented urban studies by applying the pragmatic framework of ‘regimes of engagement’. We analyse shifts people make between different regimes of argumentation and justification, showing how participants pragmatically handle their (simultaneous) status as energy consumers, urban citizens, and responsible users in an urban energy grid.

Short-course antibiotic therapy of 5 days in community-acquired pneumonia (CAP5): study protocol for a randomised controlled trial

IntroductionThe optimal duration of antibiotic therapy for community-acquired pneumonia (CAP) is unsettled. Short-course therapy has proved successful in clinical trials but is not yet implemented in everyday clinical practice. Validation...

Report on Sino–Indian Border Disputes: International Law and International Relations Perspectives

Abstract This article is based on remarks and presentations made at two symposiums—namely, the International Online Symposium on Sino–Indian Border Disputes: A Dialogue between International Law and International Relations, and the Second International Online Symposium on The Peaceful Settlement of the Sino–Indian Boundary Dispute: A Pragmatic Multidisciplinary Framework (中國法與比較法研究中心第二次國際在線研討會—[和平解決中印邊界爭端：務實的多學科框架]). These were hosted by the City University of Hong Kong’s School of Law: Centre for Chinese and Comparative Law, in collaboration with the Public Law and Human Rights Forum, on 4 March 2021 and 9 December 2021 respectively. The article reflects on the nature of the Sino–Indian Border Dispute (SIBD) and provides transitory remarks on concepts that promote either its settlement or the mitigation/maintenance of its status quo. Based on the range of issues and variables raised by discussants regarding challenges and opportunities of the SIBD, articulated from the perspectives of international law and international relations, history, political science, geography, and more, this article emphasizes a multidisciplinary approach to SIBD settlement with a context-specific assessment of each sector.

Utilising the Implementation of Integrated Care to Develop a Pragmatic Framework for the Sustained Uptake of Service Innovations (SUSI).

The provision of integrated care (IC) across alcohol and other drug (AOD) and mental health (MH) services represents the best practice, yet the consistent delivery of IC in routine practice rarely occurs. Our hypothesis is that there is no practical or feasible systems-change approach to guide staff, researchers, or consumers through the complex transition that is required for the sustained uptake of IC across diverse clinical settings. To address this gap, we combined clinical and consumer expertise with the best available research evidence to develop a framework to drive the uptake of IC. The goal was to develop a process that is both standardised by the best available evidence and can be tailored to the specific characteristics of different health services. The result is the framework for Sustained Uptake of Service Innovation (SUSI), which comprises six core components that are applied in a specified sequence and a range of flexible activities that staff can use to deliver the core components according to their circumstances and preferences. The SUSI is evidence-based and practical, and further testing is currently underway to ensure it is feasible to implement in different AOD and MH services.

Prediction of Intensive Care Unit Length of Stay in the MIMIC-IV Dataset

Accurately estimating the length of stay (LOS) of patients admitted to the intensive care unit (ICU) in relation to their health status helps healthcare management allocate appropriate resources and better plan for the future. This paper presents predictive models for the LOS of ICU patients from the MIMIC-IV database based on typical demographic and administrative data, as well as early vital signs and laboratory measurements collected on the first day of ICU stay. The goal of this study was to demonstrate a practical, stepwise approach to predicting patient’s LOS in the ICU using machine learning and early available typical clinical data. The results show that this approach significantly improves the performance of models for predicting actual LOS in a pragmatic framework that includes only data with short stays predetermined by a prior classification.

Opportunities and challenges of trilateral South‒South cooperation for transforming development assistance for health: evidence from a DRC–UNICEF–China maternal, newborn, and child health project

BackgroundTrilateral South‒South cooperation is envisioned as an equal and empowering partnership model but still faces certain challenges. This study addresses whether and how trilateral South‒South cooperation can transform traditional development assistance for health (DAH) and explores the opportunities and challenges of trilateral South‒South cooperation for transforming future DAH, in the theme of “the emerging development partner’s DAH transformation facilitated by a multilateral organization”.MethodsWe evaluate a maternal, newborn, and child health (MNCH) project involving the Democratic Republic of Congo (DRC), the United Nations Children’s Fund (UNICEF), and China (hereinafter referred to as the “DRC–UNICEF–China project”). We analyze data from project documents and seventeen semi-structured interviews using a pragmatic analytical framework based on the DAH program logic model and the OECD’s trilateral cooperation framework.ResultsEvidence from the DRC–UNICEF–China MNCH project suggests that trilateral South‒South cooperation facilitated by a multilateral organization can provide transformative opportunities for emerging development partners’ DAH to generate and deliver context-based, demand-oriented solutions, harmonize rules and procedures, institutionalize mutual learning and knowledge sharing, and increase the visibility of emerging development partners as sources for South‒South development experience transfer. However, the project revealed some challenges, including the neglect of key stakeholders in the complex governance structure, the high transaction costs needed to ensure transparency, and the harm local absence of the emerging development partner poses to long-term DAH engagement.ConclusionsThis study echoes some of the findings in trilateral SSC literature that claim power structures and philanthropic, normative justification for health equity are often juxtaposed in trilateral SSC partnerships. The opportunities offered by the DRC–UNICEF–China project align with China’s cognitive learning process for strengthening international engagement and global image building. However, challenges may arise as a result of complex governance structures and the entrustment of facilitating partners, which can threaten the effectiveness of trilateral cooperation. We call for strengthening the beneficiary partner’s ownership at all levels, engaging the emerging development partner to better understand the beneficiary partner’s local context(s) and needs, and ensuring available resources to support programmatic activities and long-term partnerships for the health and well-being of the beneficiaries.