Holistic Framework Research Articles

Vaccine literacy and cultural competence training of Professional FOR health to improve the vaccination offer

Abstract Background It is essential that healthcare institutions have a high level of organizational vaccine literacy so that they can support Newly Arrived Migrants (NAM) to navigate, understand and make informed decisions on vaccinations in an effort to make uptake equitable. Developing training material for Professional-FOR-health (PfH) working with NAM, i.e. health and non-health workers, can improve the vaccination offer for NAM. Objectives A holistic training framework for PfH was designed to increase capacity building skills and cultural sensitivity of the healthcare system in promoting active immunization of NAMs. The blended training should cover four topics: “Vaccine Literacy”, “Cultural awareness/migrant sensitivity”, “Health promotion tools with community-based approach” and “Entitlement to vaccination for NAMs/NAMs profile”. As learners cannot be seen as mere recipients of notions, their needs, motivations, and experiences should be put right at the center of the training process. Therefore, a training guide and materials were shared to Consortium Countries to be adapted and implemented in their context. Training sessions were conducted in the summer of 2023. Results A total of 180 participants showed an average increase of 8.2% in correct answers from pre- to post-raining. Notably, 112 participants experienced more than a 10% increase in correct answers. Significant increases were observed across all topics, particularly in Vaccine Literacy (A1) and NAM Profile (A4), with increases of 52% and 74%. The training was evaluated positively with an overall index of 4.2 out of 5. All items analyzed from the satisfaction questionnaire yielded positive evaluations, with an average rating of 4 out of 5. Conclusions The evaluation underscores the effectiveness of training in meeting educational needs of participants. This type of training can be the groundwork for the changes needed to make the NAMs vaccination process more guaranteed and inclusive.

Conceptual scaffolding for the philosophy of medicine.

This paper consists of two parts. In the first part, I will introduce a philosophical toolbox that I call 'conceptual scaffolding,' which helps to reflect holistically on phenomena and concepts. I situate this framework within the landscape of conceptual analysis and conceptual engineering, exemplified by the debate about the concept of disease. Within the framework of conceptual scaffolding, I develop the main idea of the paper, which is 'the binocular model of plural medicine', a holistic framework for analyzing medical concepts and phenomena. In the second part, I demonstrate the use and value of the binocular model by analyzing, through the lenses of the model, the phenomenon of health wearable devices and their effects on the concept of diagnosis.

Integrating Machine Learning and Genetic Algorithms to Optimize Building Energy and Thermal Efficiency Under Historical and Future Climate Scenarios

As the global energy demand rises and climate change creates more challenges, optimizing the performance of non-residential buildings becomes essential. Traditional simulation-based optimization methods often fall short due to computational inefficiency and their time-consuming nature, limiting their practical application. This study introduces a new optimization framework that integrates Bayesian optimization, XGBoost algorithms, and multi-objective genetic algorithms (GA) to enhance building performance metrics—total energy (TE), indoor overheating degree (IOD), and predicted percentage dissatisfied (PPD)—for historical (2020), mid-future (2050), and future (2080) scenarios. The framework employs IOD as a key performance indicator (KPI) to optimize building design and operation. While traditional indices such as the predicted mean vote (PMV) and the thermal sensation vote (TSV) are widely used, they often fail to capture individual comfort variations and the dynamic nature of thermal conditions. IOD addresses these gaps by providing a comprehensive and objective measure of thermal discomfort, quantifying both the frequency and severity of overheating events. Alongside IOD, the energy use intensity (EUI) index is used to assess energy consumption per unit area, providing critical insights into energy efficiency. The integration of IOD with EUI and PPD enhances the overall assessment of building performance, creating a more precise and holistic framework. This combination ensures that energy efficiency, thermal comfort, and occupant well-being are optimized in tandem. By addressing a significant gap in existing methodologies, the current approach combines advanced optimization techniques with modern simulation tools such as EnergyPlus, resulting in a more efficient and accurate model to optimize building performance. This framework reduces computational time and enhances practical application. Utilizing SHAP (SHapley Additive Explanations) analysis, this research identified key design factors that influence performance metrics. Specifically, the window-to-wall ratio (WWR) impacts TE by increasing energy consumption through higher heat gain and cooling demand. Outdoor temperature (Tout) has a complex effect on TE depending on seasonal conditions, while indoor temperature (Tin) has a minor impact on TE. For PPD, Tout is a major negative factor, indicating that improved natural ventilation can reduce thermal discomfort, whereas higher Tin and larger open areas exacerbate it. Regarding IOD, both WWR and Tin significantly affect internal heat gains, with larger windows and higher indoor temperatures contributing to increased heat and reduced thermal comfort. Tout also has a positive impact on IOD, with its effect varying over time. This study demonstrates that as climate conditions evolve, the effects of WWR and open areas on TE become more pronounced, highlighting the need for effective management of building envelopes and HVAC systems.

Overcoming Challenges and Promoting Positive Education in Inclusive Schools: A Multi-Country Study

Inclusive education faces significant challenges requiring deep understanding and comprehensive solutions. This study aims to establish a holistic framework for understanding the challenges in inclusive education, the core mission of inclusive schools, and the essential qualities of teachers. The methodology employed was qualitative, using the grounded theory method. A total of 59 experts from 13 countries participated in this study. Semi-structured asynchronous virtual interviews were conducted and analyzed using ATLAS.ti software (version 8). The results identified eight persistent challenges to inclusive education. In addition, positive education was highlighted as the fundamental core of inclusive schools, with emphasis on the development of learning, well-being, engagement, resilience, motivation, mental health, affective and social outcomes, creativity, and happiness. Finally, the integral profile of the inclusive teacher was defined based on a four-dimensional model. This groundbreaking study introduces a novel comprehensive framework that revolutionizes our understanding of the enduring challenges in inclusive education. Elucidating the core mission of inclusive schools and defining the essential qualities of inclusive teachers offers transformative insights. This study’s implications, future perspectives, and limitations provide a wealth of valuable information for policymakers, educators, and researchers, paving the way for innovative approaches and enhanced inclusive educational practices.

Academic development for tomorrow? Claiming a clearer role for university pedagogy through a holistic framework

ABSTRACT The aim of this theoretically oriented article is to promote the educational role and purpose of academic development in higher education by suggesting a holistic framework and theoretical articulation for university pedagogy. By discussing links between university pedagogy, academic development, and broader views of university education, our framework clarifies the concept of university pedagogy in the Nordic countries. The framework encompasses four themes: (1) the relationship between educational theory and pedagogical practice; (2) the interplay between knowledge and the curriculum; (3) the university as an organization and social institution; and (4) the agency in and of academic communities. We argue that university pedagogy operating within this framework has the potential to strengthen the scholarly foundations of the development of university education. The framework can enhance critical public discourse on the purpose of university education.

On the need to better integrate the social environment in research on climate change and health: recommendations and thinking tools

Social inequality impacts health, is aggravated by the consequences of climate change, and may be influenced by inappropriate policy responses. These interdependent effects create a self-perpetuating loop exacerbating the impact of climate dysregulation on health in an uncontrolled and poorly understood way. Holistic approaches to public health such as One Health, EcoHealth or Planetary Health are well suited to tackling the considerable and complex environmental and social issues underlying climate dysregulation. However, the extent to which research using such frameworks investigates social determinants of health is not clear. In this paper we discuss the ways in which the social environment has so far been considered in the literature to problematize and analyze the relationship between climate dysregulation and health within holistic frameworks and provide tools and recommendations to facilitate their apprehension. Social factors are investigated empirically only in a minor fraction of studies addressing the relation between climate and health in holistic frameworks, and not systematically. Barriers to such approaches are discussed. This work also provides two analytical tools (a process diagram and a knowledge framework) and a set of recommendations to help include the social environment more meaningfully in such frameworks. They are meant to facilitate our understanding of the current status of this type of research and to encourage trans-disciplinary and trans-sectorial endeavors towards directions which need to be taken to ensure societal factors and inequalities are placed at the center of research on climate and health and the ensuing policy response.

The influence of green human resource management on environmental performance: Exploring the differential effects of green work engagement and moral reflection

This study investigates the impact of the implementation of Green Human Resource Management (GHRM) on the environmental performance of higher education institutions from the perspective of the Ability-Motivation-Opportunity (AMO) theory. A purposive sampling approach was employed to collect 670 questionnaires from the academic and administrative staff of higher education institutions in Thailand. The findings of the research demonstrate that GHRM enhances the environmental performance of higher education institutions. Moreover, GHRM contributes to this enhancement by positively influencing employees’ green work engagement, thereby improving the environmental performance of the institutions. Additionally, employees’ moral reflection positively moderates the relationship between GHRM and green work engagement. This study aspires to construct a holistic research framework, offering new practical and theoretical insights into GHRM, which, in turn, provides meaningful guidance for the sustainable development of global higher education institutions.

Enabling Social Robots to Perceive and Join Socially Interacting Groups Using F-formation: A Comprehensive Overview

Social robots in our daily surroundings, like personal guides, waiter robots, home helpers, assistive robots, and telepresence/teleoperation robots, are increasing day by day. Their usability and acceptability largely depend on their explicit and implicit interaction capability with fellow human beings. As a result, social behavior is one of the most sought-after qualities that a robot can possess. However, there is no specific aspect and/or feature that defines socially acceptable behavior, and it largely depends on the situation, application, and society. In this article, we investigate one such social behavior for collocated robots. Imagine a group of people is interacting with each other, and we want to join the group. We as human beings do it in a socially acceptable manner, i.e., within the group, we do position ourselves in such a way that we can participate in the group activity without disturbing/obstructing anybody. To possess such a quality, first, a robot needs to determine the formation of the group and then determine a position for itself, which we humans do implicitly. There are many theories which study group formations and proxemics; one such theory is f-formation which could be utilized for this purpose. As the types of formations can be very diverse, detecting the social groups is not a trivial task. In this article, we provide a comprehensive survey of the existing work on social interaction and group detection using f-formation for robotics and other applications. We also put forward a novel holistic survey framework combining some of the possibly more important concerns and modules relevant to this problem. We define taxonomies based on methods, camera views, datasets, detection capabilities and scale, evaluation approaches, and application areas. We discuss certain open challenges and limitations in the current literature along with possible future research directions based on this framework. In particular, we discuss the existing methods/techniques and their relative merits and demerits, applications, and provide a set of unsolved but relevant problems in this domain. The official website for this work is available at: https://github.com/HrishavBakulBarua/Social-Robots-F-formation

Mixed-variable graphical modeling framework towards risk prediction of hospital-acquired pressure injury in spinal cord injury individuals

Developing machine learning (ML) methods for healthcare predictive modeling requires absolute explainability and transparency to build trust and accountability. Graphical models (GM) are key tools for this but face challenges like small sample sizes, mixed variables, and latent confounders. This paper presents a novel learning framework addressing these challenges by integrating latent variables using fast causal inference (FCI), accommodating mixed variables with predictive permutation conditional independence tests (PPCIT), and employing a systematic graphical embedding approach leveraging expert knowledge. This method ensures a transparent model structure and an explainable feature selection and modeling approach, achieving competitive prediction performance. For real-world validation, data of hospital-acquired pressure injuries (HAPI) among individuals with spinal cord injury (SCI) were used, where the approach achieved a balanced accuracy of 0.941 and an AUC of 0.983, outperforming most benchmarks. The PPCIT method also demonstrated superior accuracy and scalability over other benchmarks in causal discovery validation on synthetic datasets that closely resemble our real dataset. This holistic framework effectively addresses the challenges of mixed variables and explainable predictive modeling for disease onset, which is crucial for enabling transparency and interpretability in ML-based healthcare.

A comprehensive framework for evaluating and predicting investment risks in renewable energy projects: a case study of Maynak hydropower station

ABSTRACT This study introduces a holistic analysis framework designed to evaluate and predict the investment risks associated with foreign renewable energy initiatives. This framework aims to reduce the uncertainties inherent in renewable energy projects. To achieve this, we utilize the variable weight matter-element extension model to establish the project’s fundamental reliability function. We then refine this model by incorporating evidence theory to assess the project’s risk level and derive precise risk index measurements. We utilize the GM model to forecast potential future risks associated with the project. In addition, a case study is presented on the risk assessment and prediction for the Maynak Hydropower Station. Our findings reveals that the project encountered significant investment risks in 2008, 2014, 2020, and 2022. Key risk indicators include political turmoil，policy change，imperfect legislation，cultural risk，exchange rate changes，technical risks and management risks. Furthermore, the investment risk level declined from 2023 to 2027, with our risk measurement outcomes closely aligning with actual conditions, thereby validating the effectiveness and applicability of our model.

A Holistic Framework for Evaluating Food Loss and Waste Due to Marketing Standards across the Entire Food Supply Chain.

This paper addresses the critical and urgent need to reduce food losses and waste (FLW) resulting from stringent marketing standards. It proposes a comprehensive and actionable framework grounded in the three pillars of sustainability-environmental, economic, and social-to effectively evaluate FLW across the entire food supply chain. The paper involves a thorough review of existing marketing standards, including research on FLW due to marketing standards, and proposes the implementation of targeted key actions within four key food sectors: fruits, vegetables, dairy, and cereals. The study provides a detailed analysis of the significant impact marketing standards have on FLW at various stages of the supply chain, including primary production, processing, retail, and consumption. By focusing on these critical points, the research underscores the necessity of addressing marketing standards to achieve meaningful reductions in FLW. The proposed framework aims to foster improved business practices and drive the development of innovative, sector-specific solutions that balance sustainability goals with economic viability. The holistic approach followed for this research lays the foundation for ensuring that the proposed framework is adaptable and practical, leading to measurable improvements in reducing FLW and promoting sustainability across the food industry.

Concept of Dementia and its Management in Unani System of Medicine: A Review

Dementia, derived from Latin meaning “without mind,” is a significant global health concern and the seventh leading cause of death, characterized by the progressive deterioration of cognitive functions, including memory, thinking, and behaviour. As the global population ages, dementia's prevalence is anticipated to rise dramatically, with an estimated 50 million cases currently worldwide, projected to reach 152 million by 2050. The two primary causes are Alzheimer's disease and vascular disorders. In the Unani system of medicine, dementia, referred to as Nisyān, is attributed to the dysfunction of three internal faculties: imagination (Qüwwate Khayal), thought (Qüwwate Fikr), and memory (Qirwwate Zikr), influenced by factors such as abnormal temperament (Sü' Mizāj) and disruptions in structural integrity. Clinical features vary, with early signs including short-term memory loss and disorientation. The condition can be classified into primary (degenerative) and secondary (acquired) dementias. Risk factors include age, family history, and lifestyle choices. Treatment principles in Unani medicine focus on addressing the underlying causes, correcting brain temperament, evacuating morbid matter, and employing dietary, regimental, and pharmacotherapeutic approaches. This holistic framework underscores the importance of traditional medical systems in understanding and managing dementia, advocating for a comprehensive approach to treatment that encompasses both modern and traditional practices. Keywords: unani system of medicine, Dementia, cognitive decline, Dietotherapy, su’Mizaj

How to Realize the Collaborative Supply of Cultural Resource Big Data with Government Participation: Experiences from China

To foster the sustainable development of culture, particularly focusing on the preservation of cultural heritage, encompassing relics, intangible cultural heritage, and historical sites, China has launched a strategy for the digitalization of culture, with the goal of establishing a holistic national big data framework for cultural resources. To improve the efficiency of collaborative supply of cultural resource big data among various parties and to further advance the sustainable development of culture, this research has created a cooperative model that includes cultural institutions, a cultural resource big data service platform, and government participation. Our research findings, based on prospect theory and evolutionary game theory combined with Chinese practice, are presented below. (1) Various factors, including the coefficient of digital infrastructure empowerment, access charges for digital infrastructure, government penalties, and the probability of data leakage, have varying effects on the system in different states. (2) Once the industry has developed, the government can increase the impact of digital infrastructure empowerment to create stronger incentives, rather than relying solely on rewards or penalties. (3) When the value level of cultural resource big data is high, the benefit distribution coefficient does not affect the system evolution results. Finally, we offer practical insights for the government, cultural organizations, and cultural resource big data service platforms based on our research results. Our research offers Chinese insights for global cultural sustainable development.

The Impact of Key Performance Indicators on Faculty Research in Higher Education

This study investigates the effectiveness of key performance indicators (KPIs) in evaluating the research contributions of academic staff in Uzbekistan, aiming to provide a nuanced understanding of faculty performance assessment. Employing a mixed-methods approach, the research integrates quantitative bibliometric analysis of publication data from 500 faculty members with qualitative interviews from 30 academics. The quantitative analysis focuses on metrics such as total publications, citation counts, and h-index scores, while the qualitative component explores faculty perceptions regarding the influence of KPIs on their research activities and career development. The analysis reveals significant variability in research productivity, with faculty averaging 12.4 publications and 110.2 citations. Econometric modeling indicates a strong positive correlation between publication metrics and citation impact, suggesting that higher publication output enhances academic visibility. Qualitative insights highlight the pressures of a "publish-or-perish" culture, which adversely affects research quality and faculty morale, particularly in contexts with limited institutional support. This research contributes to the discourse on academic performance evaluation by emphasizing the limitations of traditional metrics and advocating for a more holistic assessment framework. It highlights the need for higher education institutions to consider both quantitative and qualitative measures to better reflect the complexities of academic contributions in Uzbekistan.

Investigating the Antecedents of Corporate Governance Influencing the Investment Efficiency of Firms: A Synthesis of Literature and Future Research Agenda

This review study investigates the critical antecedents of corporate governance affecting firms’ investment efficiency. It proposes a comprehensive framework encompassing corporate governance’s multifaceted aspects for all stakeholders’ benefit. A thorough literature evaluation has been conducted using the SCOPUS database, encompassing all publications published between 2010 and June 2023. The existing body of literature has also been examined through the theoretical frameworks, journals, authors, articles and research construct questions. After synthesising 154 articles through bibliometric analysis, four key antecedents (financial reporting quality, auditing and accounting quality, environmental, social and governance (ESG), institutional ownership and board structure) of corporate governance were identified as primary influencers of investment efficiency. New corporate governance perspectives, such as ESG and carbon taxation in the context of investment efficiency, have been identified and can be explored in depth by future researchers. The review provides a holistic framework for corporate governance, which defines the association with investment efficiency. The study presents potential future research areas where scholars can extend the scope of corporate governance from the perspective of investment efficiency.

The Art of State-Societal Reconfiguration in a Time of Pandemic Crisis: A Health System Resilience Typology and Comparative Analysis Between Transcending Nations (the US, UK, and India) and Coping Nations (South Korea and Taiwan)

This paper examines and reviews three years of the preventive measures taken by different countries, which led us to frame the most effective mitigation and coping mechanisms that were deployed to cushion the impact of Covid-19 outbreaks on respective health systems. Measures taken by five countries (the United States, United Kingdom, India, South Korea, and Taiwan) are used as case studies. We delineate the resilience measures within the scope of “coping” and “transcending.” The elucidation of these measures is demarcated into three control phases: feedforward control, concurrent control, and feedback control. Our review reveals that the US, UK, and India struggled as a result of chaotic coordination by their public health systems to cope with high admission rates of Covid-19-infected patients; however, they possessed the ability to learn swiftly and to identify and produce vaccine candidates to transcend the crisis. Meanwhile, South Korea and Taiwan were found to have the ability to cope with the upheavals they encountered during the pandemic crisis. The holistic framework of resilience measures we derive may be instrumental to policy makers, public health specialists, and researchers, setting out as it does the coping and transcending abilities within the context of a learning society.

The need for a risk management framework for data science projects: a systematic literature review

Many data science endeavors encounter failure, surfacing at any project phase. Even after successful deployments, data science projects grapple with ethical dilemmas, such as bias and discrimination. Current project management methodologies prioritize efficiency and cost savings over risk management. The methodologies largely overlook the diverse risks of sociotechnical systems and risk articulation inherent in data science lifecycles. Conversely, while the established risk management framework (RMF) by NIST and McKinsey aims to manage AI risks, there is a heavy reliance on normative definitions of risk, neglecting the multifaceted subjectivities of data science project failures. This paper reports on a systematic literature review that identifies three main themes: Big Data Execution Issues, Demand for a Risk Management Framework tailored for Large-Scale Data Science Projects, and the need for a General Risk Management Framework for all Data Science Endeavors. Another overarching focus is on how risk is articulated by the institution and the practitioners. The paper discusses a novel and adaptive data science risk management framework – “DS EthiCo RMF” – which merges project management, ethics, and risk management for diverse data science projects into one holistic framework. This agile risk management framework DS EthiCo RMF can bridge the current divide between normative risk standards and the multitude of data science requirements, offering a human-centric method to navigate the intertwined sociotechnical risks of failure in data science projects.

The Cyberbullying Pada Aplikasi Tiktok Ditinjau Dari Hukum Pidana dan Fiqh Empat Madzhab

The growth of information technology has introduced challenges like cyberbullying, especially on platforms like TikTok. The real-time nature of TikTok and insufficient moderation exacerbate the psychological harm caused to victims. In Indonesia, cyberbullying is a criminal offense under Law Number 19 of 2016 (ITE Law) as it violates human rights. From an Islamic perspective, it is seen as a serious sin, contradicting Islamic moral values. The four major Islamic schools of thought—Hanafi, Maliki, Shafi'i, and Hanbali—guide punishing offenders, ranging from fixed (hudud) to discretionary (ta'zir) penalties depending on the severity of the offense. This study uses a doctrinal legal approach and library research to examine cyberbullying on TikTok from the perspectives of both criminal law and Islamic jurisprudence. The findings highlight that integrating the principles of positive law with Islamic jurisprudence could create a more holistic and effective framework for addressing cyberbullying. A combined approach can strengthen anti-cyberbullying policies, fostering a safer digital environment. Additionally, promoting education that emphasizes Islamic values such as respect can help prevent cyberbullying. The study recommends increasing public awareness, integrating Islamic and positive legal principles into policies, and improving law enforcement’s capacity to address cyberbullying more effectively.

Integrating Learning and Serious Game Design: The Development and Application of the Learning and Game Integration (LGI) Framework using the ‘Blackout’ Serious Game

Serious games are increasingly recognised as effective educational tools capable of simulating complex scenarios that traditional methods cannot replicate. This paper introduces the Learning and Game Integration (LGI) Framework, designed to seamlessly integrate educational content with interactive game design. Utilising the “Blackout” serious game, which simulates real world complex problem, this study demonstrates how the LGI Framework can be utilised as learning intervention to enhance learning by teaching Design Thinking to university students. The framework consists of four stages: Educational Content Integration, Theoretical Underpinning, Case Study Selection, and Game Design. The “Blackout” game enables students to engage with various stakeholder perspectives, deeply analyse problems, and develop innovative solutions under crisis conditions. Preliminary feedback from its implementation in an undergraduate business course (N=753) indicates increased student engagement and confidence in applying Design Thinking concepts. This paper contributes to the field of business education by presenting an innovative approach to teaching innovative problem-solving skills through serious games, emphasising the need for holistic educational frameworks that bridge theoretical learning with real-world application.

Empathy at the heart of customer experience: A holistic framework for understanding and enhancing consumer empathy through the lens of customer experience

AbstractServing as a social glue in interactions, consumer empathy takes center stage in shaping a pleasant customer experience. Our holistic framework of an empathic customer experience, rooted in the perception–action model of empathy and established customer experience conceptualizations, unveils the close interrelationship between consumer empathy and customer experiences. Grounded in a systematic literature review and a conceptual synthesis, our study contributes to customer experience research by conceptualizing consumer empathy as a cognitive and affective customer experience response, potentially accompanied by supplementary customer experience responses, which we refer to as an empathic customer experience. This study advances empathy literature by offering a systematic overview of an empathic customer experience, covering stimuli at touchpoints that induce an empathic customer experience during consumer interactions, potential contextual factors, and evaluative outcomes of an empathic customer experience. From our results, we derive an agenda with several research directions for the joint investigation of consumer empathy and customer experience to contribute to both research fields. In addition, our framework provides insights for managers, including recommendations for designing stimuli to evoke an empathic customer experience.