Resilience Framework Research Articles

Mathematical Resilience Framework (MRF): A new approach to overcoming math anxiety

Math anxiety is a significant barrier to student success in mathematics, often resulting in poor performance and disengagement from the subject. This paper introduces the Mathematical Resilience Framework (MRF), a novel approach that integrates cognitive-behavioral techniques with self-efficacy models to help students overcome math anxiety. The MRF emphasizes emotional regulation, mindset transformation, and confidence-building as key components in fostering resilience. This paper explores the theoretical foundation of mathematical resilience, the structure of the MRF, and its potential benefits when applied in educational settings. By comparing MRF to other interventions, it highlights how the framework addresses both the emotional and cognitive aspects of math anxiety. The paper concludes with recommendations for educators, policymakers, and researchers on integrating the MRF into educational systems to improve learning outcomes and support student success in mathematics.

Effect of Father-Love Absence on Subjective Well-Being: The Mediating Role of Hope

Father love is recognized as an important factor in personal development. While previous research has extensively examined the adverse effects of father-love absence on subjective well-being, it is important to note that these studies often treated subjective well-being as a singular, overarching construct, potentially limiting validity and comprehensiveness compared to a bi-factor model. Consequently, this study aimed to establish a bi-factor model of subjective well-being and investigate its association with father-love absence, considering the mediating role of hope within the theoretical framework of resilience. The study employed a weekly diary method to explore the dynamic adverse effects of father-love absence on weekly subjective well-being, highlighting hope’s role in mitigating these negative impacts. Utilizing a weekly survey method with 470 participants over seven consecutive weeks, multilevel regression modeling revealed that father-love absence significantly and negatively impacts subjective well-being. Further, multilevel mediation modeling demonstrated the mediating role of hope within the resilience framework. This research has significant theoretical and practical implications for enhancing adolescent well-being through increased father involvement in parenting.

Bridging technostress and continuous learning in knowledge-intensive organizations: A socio-technical systems approach for the future of healthy working life

We present an interdisciplinary exploration of technostress in knowledge-intensive organizations, including both business and healthcare settings, and its impact on a healthy working life. Technostress, a contemporary form of stress induced by information and communication technology, is associated with reduced job satisfaction, diminished organizational commitment, and adverse patient care outcomes. This article aims to construct an innovative framework, called The Integrated Technostress Resilience Framework, designed to mitigate technostress and promote continuous learning within dynamic organizational contexts. In this perspective article we incorporate a socio-technical systems approach to emphasize the complex interplay between technological and social factors in organizational settings. The proposed framework is expected to provide valuable insights into the role of transparency in digital technology utilization, with the aim of mitigating technostress. Furthermore, it seeks to extend information systems theory, particularly the Technology Acceptance Model, by offering a more nuanced understanding of technology adoption and use. Our conclusion includes considerations for the design and implementation of information systems aimed at fostering resilience and adaptability in organizations undergoing rapid technological change.

Exploring the Role of Creativity in Psychological Resilience

This paper investigates the intersection between creativity and psychological resilience, examining how creative processes and expressions contribute to the development and strengthening of resilience in individuals facing adversity. Psychological resilience, often defined as the capacity to recover from stress or trauma, and creativity, regarded as the ability to generate novel ideas and solutions, are analyzed through theoretical models, empirical research, and practical interventions. The paper reviews biopsychosocial, ecological, and developmental frameworks of resilience, highlighting the critical role creativity plays in fostering adaptive coping mechanisms and enhancing mental well-being. It further explores the empirical evidence linking creative behaviors to resilience-building, particularly in response to trauma and stress. Finally, practical implications and interventions for leveraging creativity to enhance resilience across diverse populations are discussed, suggesting tailored approaches for educators, mental health professionals, and community leaders. Keywords: Psychological Resilience, Creativity, Coping Mechanisms, Stress and Trauma, Creative Expression.

Navigating Acculturation: Overcoming Challenges and Creating Pathways to Well-Being for Central Asian Immigrants in the United States

This study explores the adaptations of recent immigrants from Central Asia (CA) to the United States. Using qualitative grounded theory analysis of narratives from 42 immigrants, gathered through semi-structured interviews and focus groups, acculturation, life course development, resilience, and intersectionality frameworks were applied to the analysis. Participants included 21 women and 21 men aged 22 to 45. Three major themes emerged. The first theme highlights acculturative challenges and stress, including shifts in gender roles, professional status, and family values. The second theme addresses barriers to seeking help, stemming from ideological and practical constraints. The third theme emphasizes opportunities and positive outlooks on life in the United States for immigrants and their children. The study underscores implications for practice and policy, along with avenues for future research.

Chaos Testing: A Proactive Framework for System Resilience in Distributed Architectures

Chaos Testing: A Proactive Framework for System Resilience in Distributed Architectures

Machine Learning Meets Cybersecurity

In an era where digital transformation is accelerating, the integration of machine learning (ML) into cybersecurity is becoming increasingly crucial. This article delves into the significant role that ML plays in enhancing cybersecurity measures. ML's ability to process and analyze vast amounts of data at unprecedented speeds allows for more efficient threat detection, anomaly identification, and predictive analytics. These capabilities are essential in pre-empting and mitigating cyber threats in real-time. However, the same technologies that bolster defences are also being leveraged by cybercriminals to develop more sophisticated attacks, posing unique challenges. This article explores the dual-edged nature of ML in cybersecurity, highlighting both its benefits and the potential risks. It discusses the challenges of bias in ML algorithms, the vulnerabilities exposed through adversarial attacks, and the ethical and privacy considerations that come with deploying ML solutions. Furthermore, it provides insights into the future trends and developments in ML-driven cybersecurity and underscores the importance of synergizing human expertise with machine intelligence to build more resilient cybersecurity frameworks. Through this exploration, the article aims to provide a comprehensive understanding of the transformative impact of ML on cybersecurity and the path forward in addressing the accompanying challenges.

SMART DENGUE CONTROL

This research presents a novel approach to combating dengue by integrating Biological Control methods with Artificial Intelligence (AI). The objective of the study is to reduce the Aedes aegypti mosquito population and decrease dengue transmission through sustainable strategies. A comprehensive research methodology was used, involving extensive literature review, case studies, and data analysis to identify the main factors driving the high incidence of dengue in Brazil. The research applied AI tools to analyze epidemiological, meteorological, and environmental data, allowing for early outbreak predictions and targeted interventions. AI-enhanced surveillance systems were also employed to monitor mosquito populations and identify breeding sites more accurately. These strategies were combined with biological control methods, such as using natural predators and genetically modified mosquitoes, to manage mosquito populations effectively. The study demonstrate that the integration of AI and biological control can significantly improve the efficiency, accuracy, and sustainability of dengue control measures. The study concludes that this data-driven approach, when adapted to local contexts, can reduce reliance on chemical pesticides and offer a more resilient framework for long-term dengue management.

Exploitative and exploratory search: Dynamic capabilities enhancing SME adaptation, new product development, and environmental performance

ABSTRACT This study delves into how small and medium-sized enterprises (SMEs) adapt to market changes and enhance environmental performance through exploitative and exploratory search strategies within emerging economies. Operationalizing these strategies as dynamic capabilities, we investigate their impact on new product development amid environmental dynamism. Utilizing a two-wave survey of 437 manufacturing SMEs, with lagged primary environmental performance data, we applied partial least squares—structural equational modeling (PLS-SEM) to test our hypotheses. Our findings contribute invaluable insights to entrepreneurship literature, emphasizing the crucial role of intentional search in SMEs’ continuous adaptation and innovation. We shed light on the distinctive contributions of exploitative and exploratory search in shaping SMEs’ resource base and specific outputs, such as environmental performance. By discerning between possessing a capability and achieving successful outcomes, our study offers a resilient framework for SMEs, boosting both new product development and environmental performance in emerging economies.

Pathways to queer thriving in an LGBTQ+ intergenerational community.

LGBTQ+ people and communities continue to survive and thrive within the context of complex and unrelenting personal, structural, and collective trauma. Psychological research has examined this adaptive capacity through frameworks of resilience and posttraumatic growth. Through multidisciplinary engagement, we have identified limitations of these frameworks when they are applied to LGBTQ+ communities. In the first half of this article, we reconceptualize resilience and posttraumatic growth as queer thriving and offer the Möbius strip as a metaphor to challenge and expand normative ideas around direction, trajectory, timeline, and outcomes of positive change through adversity. In the second half of this article, we explore pathways to queer thriving within an LGBTQ+ intergenerational community project-an ethnographic experiment-that we have cofacilitated since 2019. We view generational divisions in LGBTQ+ communities as both a reflection and a form of trauma. In our ethnographic experiment, LGBTQ+ younger and older adults have the rare opportunity to heal this division by coming together for storytelling, dialogue, and artmaking around themes and issues important to their lives. In this article, we present three ethnographic vignettes that powerfully illustrate the potential for queer thriving through intergenerational social connection. We conclude by emphasizing the importance of mixed-disciplinary, community-engaged, and descriptive approaches to examining resilience and posttraumatic growth within marginalized communities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A stigma-conscious framework for resilience and posttraumatic change.

Members of stigmatized groups face severe, chronic adversities that produce qualitatively unique and often challenging experiences. Further, access to resources relevant to overcoming adversity (e.g., time, money, energy, support) is depleted and blocked by stigmatization. However, current approaches to resilience and posttraumatic growth do not account for stigma, hindering our understanding of both constructs. Thus, drawing from the conservation of resources theory (Hobfoll, 1989), we develop a stigma-conscious framework on resilience and posttraumatic change (PTC) that extends existing work by enhancing realism and generalizability for stigmatized groups. We present a multilevel framework that explains how and why stigmatization directly (as an input) and indirectly (as an influencer of resource-related mechanisms) shapes resilience and PTC processes and outcomes. This framework advances interpretations of past work on resilience and posttraumatic growth, their respective conceptualizations and operationalizations, future model development, and interventions. We encourage and guide scholars to integrate stigma into resilience and PTC research and applications. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Navigating urban risks for sustainability: A comprehensive evaluation of urban vulnerability based on a pressure–sensitivity–resilience framework

Cities are important symbols of civilization in human society. The vulnerability to cities caused by human activities and natural disasters has become increasingly evident. How to reduce the vulnerability of cities is an important topic in the research of urban public safety and sustainable development. In this study, a comprehensive evaluation of urban vulnerability is conducted on the basis of the pressure–sensitivity–resilience framework from a complex systems perspective, integrating three subsystems—the resource–environment, economic, and social subsystems. On the basis of data from 18 cities in Sichuan Province, China, from 2006 to 2021, this study analyzes vulnerability in terms of its scores, spatial and temporal evolution, and obstacles. The results reveal that the overall vulnerability of the Sichuan Basin has shown a fluctuating downward trend over the past sixteen years, and the spatial distribution has evolved into a large “low-vulnerability” agglomeration. The obstacles affecting urban vulnerability are also changing dynamically and include factors such as the harmless treatment rate of household waste and industrial smoke dust emissions. Drawing from these insights, this study enables the identification and diagnosis of urban vulnerability and, further, provides city managers with tailored recommendations for crafting policies that aim to mitigate risks and promote sustainable development.

COVID-19 pandemic and food security: Strategic agricultural budget allocation in Indonesia

The COVID-19 pandemic has exposed significant vulnerabilities in Indonesia's food security, highlighting the need for more strategic agricultural budget allocation. This study addresses the issue of inadequate budgeting techniques that fail to effectively support food production and distribution during crises. The primary objective is to develop a tailored framework that optimises budget allocations to strengthen Indonesia's food security in the face of socio-economic and geographical challenges. Using a multi-dimensional research approach, the study involves key stakeholders from the Ministry of Agriculture, the Ministry of Finance, and the Ministry of National Development Planning, employing methods such as in-depth interviews, focus group discussions, and data collection from primary and secondary sources. The research utilises the Analytical Hierarchy Process (AHP) with the Expert Choice 2000 program to systematically evaluate decision-making options. Findings reveal the necessity of a resilient framework that balances short-term emergency responses with long-term strategies, focusing on increasing production capacity, improving seed quality, expanding land availability, and adopting advanced agricultural technologies. The study contributes to the policy landscape by offering a structured agricultural budgeting framework and policy recommendations aimed at mitigating disruptions, enhancing productivity, and supporting sustainable agricultural practices. It also emphasizes the importance of sensitivity analysis in budget planning to inform strategic decisions. The study recommended targeted investments in production capacity, a reevaluation of rice import regulations, and the adoption of innovative technologies to ensure a resilient and sustainable food system in Indonesia.

The social determinants of resilience: A conceptual framework to integrate psychological and policy research.

The psychological study of resilience has increasingly underscored the need for children and families to access material and psychological resources to positively adapt to significant stress. Redistributive policies-policies that downwardly reallocate society's social and economic resources-can offer economically disadvantaged families sustained access to these resources and mitigate the harmful impacts of adversity. This conceptual article builds upon and integrates insights from psychological and policy research to develop a unifying multilevel resilience framework, which we call the Social Determinants of Resilience. We examine four U.S. redistributive policies that have been extensively studied for their effects on child and family outcomes as case studies: (1) Medicaid expansion; (2) the Earned Income Tax Credit; (3) childcare subsidies; and (4) Temporary Assistance for Needy Families. Informed by a scoping review of each policy, we propose that redistributive policies promote children's resilience through three mechanisms by (1) increasing families' resource and service access; (2) reducing family stress; and (3) enhancing adaptive cognitions, emotions, behaviors, and interpersonal processes that protect against the development of psychopathology and promote positive mental health outcomes. Highlighting current evidence for these resilience mechanisms as well as gaps in knowledge, we conclude by setting a multidisciplinary research agenda that can leverage this conceptual framework to advance the science on how redistributive policies enable children and families to thrive. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Analysis of Challenges and Opportunities for Improving the Health System in Afghanistan: Innovative Approaches and Sustainable Solutions

This research explores the challenges and opportunities for improving the health system in Afghanistan. The main objective is to identify the major issues within the healthcare system and propose sustainable solutions to enhance the quality of health services. Using a mixed-method approach (qualitative and quantitative), data were collected through semi-structured interviews with experts and a review of credible scientific sources. The findings indicate that a lack of healthcare infrastructure, a shortage of specialized human resources, and management issues are among the primary challenges facing Afghanistan's healthcare system. Additionally, opportunities such as international support and utilizing modern technologies in healthcare have been identified. The study concludes that investment in infrastructure, human resource training, and strengthening international collaborations are essential to improve the healthcare situation in Afghanistan. The study's recommendations emphasize the importance of investments in infrastructure, comprehensive training for health workers, and international partnerships to strengthen service delivery. This analysis provides practical insights for policymakers and international organizations, which could ultimately help build a more resilient health framework in Afghanistan.

A 3D index for measuring economic resilience with application to modern financial crises

AbstractThis paper proposes a vector index R composed of monotonous functions capturing three theoretical aspects (3D) of economic resilience (engineering, ecological, evolutionary) and performs an analysis of GDP data of 200 countries worldwide for the period 1960–2020 and 15 economic crises (shocks). The empirical analysis, first, reveals that economic resilience appears positively related to gross value added (GVA), employment, education, sectorial structure and diversification, agricultural production, tax revenue and natural resources, whereas it is negatively associated with urbanization degree, primary sector specialization and trade activity. Also, it shows that the global economy shifted to a less resilient performance through time, and it reveals the pros and cons of the continents' performance in economic resilience, highlighting a relative sensitivity of European countries against the available shocks and relatively higher resilience of Asian and African countries. Finally, the analysis of transition probabilities reveals the 2008 economic crisis as the only shock with significant transitions among different states of resilience, providing insights into the insignificant geographical scale of previous shocks in the global economy. Overall, in the complex conceptualization and measurement framework of economic resilience, the proposed 3D index contributes to a multilevel consideration of diverse theoretical aspects of this concept, provides empirical insights into the global economy's resilience and facilitates better management of economic resilience‘s computational complexity.

Enhancing financial fraud detection using adaptive machine learning models and business analytics

Financial fraud continues to be a critical threat to businesses and economies worldwide, necessitating advanced detection techniques. This paper reviews the role of adaptive machine learning (ML) models and business analytics in enhancing fraud detection systems. Traditional fraud detection methods often fall short in addressing the complexity and evolving nature of fraudulent activities, making adaptive ML models, such as decision trees and neural networks, more effective in identifying subtle patterns in large datasets. Organizations can refine ML models by integrating business analytics, ensuring real-time detection and continuous improvement of fraud detection systems. The paper also explores the challenges in deploying these technologies, including data privacy concerns and model accuracy, as well as the potential impact of emerging technologies such as blockchain and quantum computing. Future directions emphasize improving the interpretability of ML models and leveraging multi-modal data for a more holistic approach to fraud prevention. The synergy between adaptive machine learning and business analytics promises a more resilient and effective framework for combating financial fraud.

Strategic leadership and management within non-profit organizations: An in-depth review of practices contributing to sustainable impact

This study provides an in-depth review of strategic leadership and management practices within non-profit organizations (NPOs) and their contribution to sustainable impact. Employing a systematic literature review and content analysis, the research aims to explore the evolving landscape of strategic leadership, define the scope of leadership and management in achieving sustainable impact, and identify innovative management practices that enhance organizational sustainability. The methodology involved a comprehensive search across peer-reviewed journals, conference proceedings, and grey literature from 2013 to 2023, focusing on empirical evidence, theoretical frameworks, and case studies relevant to NPOs' strategic leadership and management. Key findings reveal that adaptive leadership, innovative management practices, stakeholder engagement, and technology integration are crucial for NPOs to navigate operational complexities, engage stakeholders effectively, and achieve mission-driven objectives. The study proposes strategic recommendations for NPOs to enhance their sustainable impact, including adopting adaptive leadership styles, fostering innovation, integrating technology, and building resilient organizational frameworks. The study underscores the importance of policy development to guide non-profit leaders towards best practices in strategic leadership and management. It also highlights future research directions, emphasizing the need to explore the impact of emerging technologies, globalization, and cross-cultural dynamics on NPOs. Conclusively, the research affirms that effective strategic leadership and management are indispensable for enhancing the sustainable impact of NPOs, advocating for continuous innovation and adaptability in the non-profit sector.

Optimization of autonomous vehicle control system reliability on a commercial scale through LIF dombi methodologies.

The resilient framework of Linguistic Intuitionistic Fuzzy Sets (LIFSs) allows for the representation and management of uncertainties related to intuitionistic judgments and linguistic expressions. Recent advances in passive and active safety systems have reduced highway fatalities. Autonomous vehicles can improve safety, efficiency, and mobility by navigating traffic without a driver. One of the primary benefits associated with this technology is that it reduces the number of traffic collisions that result in millions of fatalities and numerous injuries. In this research work, we devise two novel aggregation operators: the linguistic intuitionistic fuzzy Dombi ordered weighted averaging (LIFDOWA) operator and the linguistic intuitionistic fuzzy Dombi ordered weighted geometric (LIFDOWG) operator, and explore their fundamental structural properties. We provide innovative score and accuracy functions for multiple attribute decision-making (MADM) problems within the framework of LIF knowledge. Moreover, we use these techniques to develop a specialized algorithm for MADM issues that addresses the complexities arising from ambiguous data during the selection process. We also demonstrate the effectiveness of our proposed methods by applying them to solve the MADM scenario of selecting an optimal approach to improve the credibility of autonomous vehicle control systems on a commercial scale. In addition, we also compare and evaluate the authenticity and practicability of the newly designed techniques in comparison to existing methodologies.

Resilient Sustainability Assessment Framework from a Transdisciplinary System-of-Systems Perspective

The vital role of extensive information exchange among stakeholders across diverse sectors and the interconnection of various scientific fields with nonhomogeneous technology readiness levels has created a new form of a complex engineering problem in the climate change era. Comprehensive sustainability assessment to enable the realization of needs requires transdisciplinary thinking to achieve systematic solutions that bridge the gap between multiple collaborative systems in a portfolio. Although the principal aim of dedicated sustainability regulations is to force companies to move toward sustainability development, general and non-engineered metrics that have not defined clear thresholds for evaluation have encountered severe challenges regarding implementation and economic viability. Therefore, adopting a transdisciplinary systems engineering approach can address multifaceted challenges like sustainability by overcoming collaboration barriers, and traditional disciplinary limits. This paper systematically reviews sustainability-dictated regulations from a transdisciplinary perspective. Different standards are compared, raised opportunities and challenges are discussed, and future remarks are highlighted. The sustainability problem is analyzed from a transdisciplinary systems engineering lens. Finally, a two-level resilient system sustainability assessment framework is proposed to effectively handle and enhance the resilience of companies’ sustainability development roadmaps by enabling decision makers to find robust and highly reliable solutions regarding sustainable system design. The impact of this research is to create a new insight into addressing climate change which not only assesses the current situation but also considers uncertainty sources that affect decision making for the future.