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Generative AI for Healthcare Security: Addressing Privacy Challenges through Anomaly Detection in Healthcare Communications
Cybersecurity within the healthcare sector is paramount due to the sensitive nature of patient data and critical healthcare services. This chapter explores the role of Generative AI (GAI), particularly using BERT embeddings and the Isolation Forest algorithm, in enhancing cybersecurity measures. It begins by discussing the significance of cybersecurity in healthcare and the potential threats healthcare organizations face, emphasizing the need for robust security measures to protect patient data and ensure uninterrupted healthcare services. The chapter provides an overview of GAI and its applications in cybersecurity, focusing on its ability to detect anomalies in healthcare communications. A detailed case study demonstrates the practical implementation of GAI techniques for anomaly detection in healthcare emails, highlighting the effectiveness of BERT embeddings and Isolation Forest in identifying potential security breaches. Furthermore, the chapter discusses the broader implications of generative AI in healthcare cybersecurity, addressing privacy concerns and ethical considerations. The findings underscore the importance of integrating advanced AI technologies with robust privacy-preserving measures to safeguard patient data while promoting technological innovation in healthcare cybersecurity. 2025 selection and editorial matter, Anoop V.S., Suhasini Verma, Usharani Hareesh Govindarajan. -
Quantum leap in quick commerce: Harnessing quantum computing for sustainable and efficient logistics
This chapter explores how quantum computing can revolutionise the quick commerce industry, focusing on logistics and supply chain management to boost efficiency and sustainability. Quick commerce, an emerging trend in e-commerce, promises incredibly fast delivery speeds to satisfy ever-growing consumer expectations. But this rapid expansion isnt without its hurdles, particularly when it comes to maintaining smooth operations and being eco-friendly. Quantum computing steps in as a potential game-changer, bringing its powerful processing abilities to the table. Integrating quantum computing into quick commerce could transform logistics operations, from planning delivery routes to managing warehouse resources. Its not just about speeding things up; its about rethinking the entire supply chain, including how we handle inventory and the final leg of delivery. Quantum algorithms, which are built on the principles of quantum mechanics, can help companies predict demand more accurately, restock shelves faster, cut down on waste, and enhance overall efficiency. These algorithms are especially good at optimising routes in real time, considering various factors to ensure quicker, more dependable deliveries. This study aims to bridge the gap between the theory and practice of quantum computing in logistics. It examines how quantum computing can be used, its possible benefits, and the challenges it might face in the quick commerce sector. The chapter argues that quantum computing could usher in a new era of logistics management characterised by unprecedented efficiency in routing deliveries, controlling inventory, and allocating resources. Highlighting the use of quantum algorithms for dynamic routing and demand forecasting underscores the potential for creating a more agile and eco-friendly delivery system. Ultimately, this research shines a light on how we can turn the conceptual promise of quantum computing into real-world improvements in quick commerce logistics, advocating for a future where quantum computing leads to a sustainable and efficient quick commerce ecosystem. 2026 selection and editorial matter, Pushan Kumar Dutta, Pronaya Bhattacharya, Jai Prakash Verma, Ashok Chopra, Neel Kanth Kundu and Khursheed Aurangzeb; individual chapters, the contributors. -
Enhancing Log File Analysis in Digital Forensics and Incident Response through Machine Learning
Log file analysis is crucial for identifying and exploring digital security incidents by recording system and network traffic. The growing volume and complexity of log data do not allow traditional analytical methods to be used, which led to the need for the development of more advanced analytical tools. This chapter shows a new method to infer practical information from the log file analysis using machine learning algorithms combined with Python programming. The technique has the following structure: Data preprocessing, Feature extraction, and then using multiple machine learning models such as RandomForestClassifier, Gradient Boosting Classifier, SVM, XGBoostClassifier, and MLPClassifier. Adding Python greatly improves these advanced models' accuracy and efficiency in analyzing log files. The XGBoostClassifier achieved the highest accuracy, which was 0.9198 as precision, and it indicates good applicability to complicated log data compared to another model in our test. This section compares the machine learning models using the UNSWNb15 dataset, which provides a broad range of network traffic data. The chapter contains some visualizations of flagship results and a detailed discussion about the results, discussing the challenges and limitations of the proposed approach. It also suggests future research directions. The results also typify the specifics of how Python and machine learning can be disrupted to develop digital forensics incident response practicability, bringing forth such innovations that cater to solving the cyber world's rapidly transitioning threat landscapes and tooling up valued scientific knowledge in the domain. 2026 selection and editorial matter, Vinay Aseri, Sumit Kumar Choudhary, and Adarsh Kumar; individual chapters, the contributors. -
Genetic Diversity of Garcinia gummi-gutta and Sustainable Utilization
The chapter discusses the consequences of using Garcinia gummi-gutta, often known as Malabar Tamarind, sustainably while diving into the complex web of genetic variation inside the crop. Giving a thorough overview, the chapter starts by detailing the botanical and genetic traits of this enigmatic species, revealing the morphological quirks and genetic differences that make it distinct. Examining the range and preferred habitats helps to highlight the ecological niches that are essential to its existence. It delves intently into the complex web of phytochemicals found in various plant parts and explains their range of biological functions. A crucial component of this study is a thorough examination of the techniques used to gauge the genetic diversity of populations of G. gummi-gutta. The assessment of G. gummi-gutta's conservation status indicates that threats to the species genetic richness need to be taken seriously and quickly addressed. The difficulties in attaining sustainable use are examined in detail, offering a comprehensive grasp of the nuances related to overexploitation and conservation initiatives. This study of G. gummi-gutta offers evidence of the complex interplay in the field of botanical resources between genetic diversity, conservation, and sustainable use. 2025 Hosakatte Niranjana Murthy. -
Monitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection
Skip to main content Taylor & Francis Group Logo T&F eBooks ? Search for keywords, authors, titles, ISBN Advanced Search About Us Subjects Browse Products Request a trial Librarian Resources What's New!! HomeComputer ScienceArtificial IntelligenceApplying Metaverse Technologies to Human-Computer Interaction for HealthcareMonitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection Monitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection Chapter Monitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection ByMeera Mathew Book Applying Metaverse Technologies to Human-Computer Interaction for Healthcare Edition1st Edition First Published2025 ImprintAuerbach Publications Pages18 eBook ISBN9781003491668 Share Share ABSTRACT The virtual world will be altered significantly as a result of the incorporation of metaverses into digital communication. Immersive, cooperative, and resilient 3D cybernetic environments that surpass conventional web surfing define the metaverse. Modern technology and dynamic forces that fortify the metaverse are what propel this advancement, since they allow its hybrid virtual-physical nature to be effortlessly integrated. The development and fulfilment of virtual world technologies require core capabilities including blockchain, artificial intelligence (AI), cloud computing, and 5G and 6G connection. Web3, which uses blockchain technology and smart contracts to create a decentralized, user-centric Internet, is all about the practical and geographical visibility of metaverses. Nonetheless, these ideas are connected to the broader evolution and do not conflict with one another. Because of its multiple functions, the metaverse may be used for a wide range of tasks. The gaming and entertainment sectors employ the metaverse in some of its most well-known uses. Users may enjoy a vibrant and imaginative setting in the metaverse where they can play games, watch films, go to concerts, etc. Because it may offer instructors and students a virtual environment where it is feasible to conduct training and experiments that cannot be experienced in the actual world owing to potential hazards or expenses, the metaverse can have various applications and consequences in the field of education. The metaverse will also benefit corporate growth, employee cooperation and communication, the creation of more realistic simulation models for urban development, process optimization, and many other areas. However, there are drawbacks to the metaverse as well. These include addictiveness, impairment of the ability of the mind to discriminate between actual reality and augmented or virtual reality, privacy protection, safeguarding people's digital identities, information confidentiality, and the requirement for sophisticated hardware and software infrastructure in order to receive, send, simulate, and process information in real time. The Indian Information Technology Act of 2000 and its implementing rules created India's current data protection system, which places requirements on businesses managing sensitive and personal data. Businesses must create organizational safeguards to protect data and get consent before processing any data. As the metaverse integrates more deeply into our digital world, a single legal framework is critical for managing the convergence of artificial intelligence and citizen privacy. In the light of newly introduced Indian Digital Personal Data Protection Act (DPDP Act) of 2023, data fiduciaries, data holders, and data processors have to be cautious of data collection and dissemination, and for this reason, metaverse app developers, app retainers, and app disseminators need special attention. Companies that employ moral artificial intelligence strategies are more prepared to navigate moral and societal traps associated with conducting business in the metaverse. 2025 selection and editorial matter, B. Sundaravadivazhagan, Balasubramaniam S, Pethuru Raj, and K. Shantha Kumari. -
Future Perspectives of Microplastic towards Environmental Assessment
Microplastic (MP) pollution is an outcome of the widespread use of non-biodegradable plastic and improper disposal. This leads to contamination of environmental resources, such as landfills, and all kinds of water reservoirs including but not limited to sea, fresh water, drinking water, and even wastewater. Recent reports have highlighted the presence of MPs in the human body, including blood, lungs, placentas, and breast milk, indicating the severity of the issue. It is thus crucial to eliminate these hazardous contaminants from the environment. One of the effective methods to address the concern while reducing the adverse effects is to remove the MPs at their discharge points. Nanomaterials with exceptional properties like high surface area, ease of functionalization, and high affinity toward various pollutants act as excellent adsorbents. In this chapter, we present an overview of emerging nanomaterial-based adsorbents, such as photocatalysts, metal-organic frameworks, carbon-based nanomaterials, and nanocomposites, for effective removal of MPs from aqueous media via adsorption, photo-catalysis, and membrane filtration. However, considering that the research in the area of MP pollution is still in its infant stage, we aim to provide a brief account of the strengths, weaknesses, and future research dimensions of nanomaterial-based adsorbents for removing MPs from aqueous media. 2025 selection and editorial matter, Nirmala Kumari Jangid and Rekha Sharma; individual chapters, the contributors. -
Navigating Post-Pandemic Mental Health Challenges: Unleashing the Potential of Artificial Intelligence
In the wake of the COVID-19 pandemic, the landscape of healthcare, particularly in the realm of mental health, has undergone unprecedented shiftsThis chapter delves into the pivotal role of artificial intelligence (AI) in shaping post-pandemic mental healthcare deliveryThis chapter comprehensively explores AI-driven solutions, including predictive modeling, sentiment analysis, and virtual assistants; this chapter underscores how AI technologies can revolutionize mental health diagnosis, treatment, digitalized psychometric assessment and support care websites, and automated consultation or recommendation of specific mental issuesAdditionally, it discusses integrating AI-powered tools in remote monitoring, teletherapy, and digital interventions to address the increasing demand for mental health services and bridge existing gaps in accessibility and conversion of digital platforms to provide mental health services and appointments, case records, and easy accessibilityMoreover, ethical considerations, data privacy concerns, and the importance of maintaining human-centric approaches in AI-enabled mental healthcare are examined per the Information Act and Mental Healthcare ActBy shedding light on the transformative potential of AI, this chapter aims to empower healthcare stakeholders to leverage cutting-edge technologies in fostering resilience and recovery in the post-pandemic era. 2025 selection and editorial matter, Philip Eappen and Narasimha Rao Vajjhala; individual chapters, the contributors. -
Breast Cancer Classification Using Machine Learning A Study
Nowadays, breast cancer is the most common disease found in women. Although many researchers and experts have aimed to discover the solution to this widespread disease, they have not determined it. In this study, the techniques that are used to find the early signs of breast cancer with the use of machine learning (ML) are discussed. ML is an emerging technology in the field of computer science and information technology, especially in disclosing medical diagnoses. ML is also used, for example, in image recognition, speech recognition, traffic prediction, virtual personal assistants, and online fraud detection. There are plenty of algorithms and techniques that are used in ML. Some of the most popular techniques are discussed in this study. 2025 selection and editorial matter, A. Malini, Surbhi Bhatia Khan, S. Kayalvizhi, and Mohammed Saraee; individual chapters, the contributors. -
Precision agriculture takes flight: Drone technology in crop management
[No abstract available] -
Ethical AI in Humanitarian Contexts: Challenges, Transparency, and Safety
This chapter elaborates on how emerging technologies for artificial intelligence (AI) can help create social change and solve worldwide problems. The chapter brings to light the issue of ethical matters and responsible AI practices that should be considered to avoid technology usage by the vulnerable population to harden already present inequalities. This chapter also examines the role of AI in ensuring that quality education is accessible to all, in addressing poverty through innovative approaches, and in the amplification quest of human rights advocacy by marginalized groups. This chapter presents a complete picture of the impact of AI on humanitarianism, exemplifying the devices of new horizons and emphasizing the necessity of responsible and inclusive applications. This chapter provides findings and advice for researchers, practitioners, policymakers, and all interested parties who are involved in using the new technologies to make their world fairer and well-sustained. The chapter aims to comprehend the AI-humanitarianism nexus and simultaneously proclaim safety measures and transparency for the sake of social upheaval. 2025 selection and editorial matter, Adeyemi Abel Ajibesin and Narasimha Rao Vajjhala; individual chapters, the contributors. -
Stability and Effciency Enhancement of Perovskite Solar Cells
The greatest notable efficiency increases in recent years have been observed in perovskite solar cells (PSCs). With an ABX3 crystal structure, perovskite is an organic-inorganic hybrid chemical that generally has an arrangement similar to that of BaTiO3-. In this configuration, X stands for halogens, such as oxygen (O), iodide (I?), bromide (Br?), or chloride (Cl?), while A and B are variously sized cations that coordinate 12-fold and 6-fold, respectively, with X anions. Cations such as formamidine and methylammonium alter the lattice parameters, with the bandgap growing as the lattice parameters increase, but they have no direct effect on the valence band maxima. Comparable to the body-centered cubic lattice with extra anions on a unit cell's faces is the ideal perovskite structure. To achieve high power conversion efficiency (PCE), perovskite absorbers and PSC device topologies must have high charge. Consequently, increasing electron mobility, prolonging carrier life span, and lowering defect density all depend on improving the perovskite absorber's material quality. 2026 selection and editorial matter, T.D. Subash, J. Ajayan, and Leong Wai Yie; individual chapters, the contributors. -
Assessing the Efficacy of Artificial Intelligence (AI) Applications in Predictive Policing: A Systematic Review Method
Artificial intelligence (AI) has gained attention for its potential to improve law enforcement operations through proactive policing. Advancements in data science have shown the potential benefits of applying machine learning (ML) in the criminal justice sector. Therefore, research in improving methods to forecast the likelihood of criminal reoffending is quickly growing. Creating a cutting-edge model for using ML to predict recidivism is challenging. We picked 12 out of 79 studies from Scopus and PubMed online databases in a comprehensive review that ensures the models can be replicated across various datasets and are suitable for predicting recidivism. Using two specific measures, the 12 research compared different datasets and machine learning algorithms. This study demonstrates that each approach achieves strong performance, with an average accuracy score of 0.81 and an average area-under-the-curve score of 0.74. This systematic research emphasizes essential factors that could enable criminal justice professionals to consistently utilize forecasts of recidivism risk generated by machine learning approaches. The factors include performance indicators, transparent algorithms or explainable AI approaches, and high-quality input data. 2026 Sofia Khatun, K. Sivananda Kumar. All rights reserved. -
Tracing the Evolution of Digital Strategy with AI, Blockchain, Cloud, and Cryptocurrencies
This chapter explores the transformative role of key technologies - artificial intelligence (AI), blockchain, cloud computing, and cryptocurrencies - in shaping contemporary digital strategies. It traces the historical evolution of these technologies and highlights their individual and synergistic contributions to business, governance, and society. AI has progressed from theoretical concepts to practical applications across diverse industries, enhancing decision-making, automation, and operational efficiency. Initially conceived for cryptocurrencies, blockchain technology now plays a pivotal role in securing and streamlining finance, healthcare, and supply chain management transactions. Cloud computing has democratized access to advanced technologies, accelerating the integration and scalability of AI and blockchain. Cryptocurrencies, built on blockchain frameworks, are reshaping global financial systems through decentralization and security. The chapter also addresses the challenges and opportunities of technological convergence, including ethical considerations, regulatory challenges, and the strategic need for multidisciplinary collaboration. By analyzing these intersections, this article provides a comprehensive understanding of how AI, blockchain, cloud computing, and cryptocurrencies drive digital strategies' future. 2026 Manjari Sharma, Sharad Gupta. All rights reserved. -
Innovation and Governance in the Digital Era: Exploring the Complexities of the Digital Supply Chain
This chapter investigates multiple factors and dynamics related to the digital supply chain and the involvement of national institutions, government authorities, and various stakeholders. In the highly advanced era of technological innovations and globalization, the digital supply chain has become decisive for modern economies. An interdisciplinary focus addresses the implications of digitalization for female workers, industrialization tendencies, global supply chains, and the enforcement of corporate codes of conduct. Given that modern digital technologies alter traditionally accepted methods of production and supply, it is important to understand the social and economic effects on female workers and the changes in opportunities and conditions for them at the current point. The purpose of the current research is to identify gender gaps and access to working opportunities and investigate the role national institutional frameworks and government authorities play in supporting womens empowerment in the digital supply chain. Primarily, the chapter aims at assessing the implications of digitalization on industrialization in the developed and developing world. Additional focus will be made on the opportunities and obstacles associated with automation, data analytics, or artificial intelligence, and ways of applying them to ensure sustainable development. Case studies and empirical research are likely to offer a comprehensive picture of the strategies governments, international organizations, and stakeholders can use to address the challenges of digital industrialization and address issues of social equity and just exposure to the opportunities opened through innovative tools and techniques. The relatively new concept of globalization is also closely connected to digital tools and technologies that are believed to facilitate the flow of goods and services and improve the conditions for efficient and fast supplies. However, on the other hand, global chains of supply are associated with specific challenges, such as disruptions or surveillance. Digitalization is also likely to boost unethical behavior and human rights violations. Hence, an important achievement of the current chapter is to investigate the interaction between digitalization and global supply chains and provide suggestions for the collaborative governance strategies that would promote openness, transparency, and better interaction. An alternative idea for the research is the evaluation of the efficiency of corporate codes of conduct employed to address human, civil, or product rights violations and guarantee consistency with environmental standards or regulations. To accomplish the goal, the chapter will focus on the evidence available to investigate the enforcement strategies and monitoring programs or approaches that companies rely on. An analysis of these two options is likely to result in a comprehensive understanding of the roles government authorities, institutions or organizations, and stakeholders play in preserving just working conditions and ethical standards in digital supply management. A tendency to consider the critical effects of digitalization on different administrative levels and stakeholders can be observed. That is why it is important to concentrate on the contributions of such approaches and the development of joint policies to ensure a balance between receiving the benefits of digitalization and avoiding its detrimental effects. 2025 selection and editorial matter, Saurabh Tiwari and Richa Goel; individual chapters, the contributors. -
Internet of Medical Things-Based Smart System for the Mental Health Care Challenges in 21st Century: Trends and Progress
Depression is a major mental health challenge in the 21st century and the factors that contribute to depression are rising on a day-to-day basis. Rapid urbanization and modernization brought in drastic changes in the way of life, including family type, nature of relationships, eating habits, pattern of socialization, entertainment, and various other aspects. Sometimes, this often leads to isolation and alienation in a well-connected world. In addition to the above challenges, war and climate change also pose major threats to mental health and well-being of the world population. According to the WHO, around 3.8% of the world population experienced depression in 2023 and this includes 5% of the adult population globally. Depression is considered as a leading cause of suicide and a major mental health issue among individuals in the age range of 15-29 years. This chapter reviews the applications of Internet of Medical Things (IoMT)-based systems to effectively manage depression and the related mental health care challenges in the present world. The study gives an overview of the existing trends by exploring working systems and prototypes for their service features, ethical aspects, privacy, and confidentiality. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
Revolutionizing Mental Health Care: The Transformative Power of Internet of Medical Things (IoMT): A Comprehensive Overview and Case Studies
This study proposes the detection of humans in disaster-affected areas from the images obtained from unmanned aerial vehicle (UAV). Specialized rescue teams do such search and rescue operations to search a vast area for missing persons. The degrading effect of blur induced by camera movement during image capture is one of the primary difficulties in data processing of UAV photography. This can be caused by the UAVs natural flying movement, severe winds, turbulence, or unexpected operator inputs, all of which reduce accuracy. This blur disturbs the visual analysis and interpretation of the data, causes errors, and can degrade the accuracy. As a result, this approach proposes a method based on contrast-limited adaptive histogram equalization (CLAHE) and deblurring using Gaussian blur kernel as the solution. A variety of UAV datasets were used to verify the methods speed and reliability. This method proves to be fast and efficient, making the algorithm applicable for UAV dataset. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
Revolutionizing Mental Health Care: The Transformative Power of Internet of Medical Things (IoMT): A Comprehensive Overview and Case Studies
This study proposes the detection of humans in disaster-affected areas from the images obtained from unmanned aerial vehicle (UAV). Specialized rescue teams do such search and rescue operations to search a vast area for missing persons. The degrading effect of blur induced by camera movement during image capture is one of the primary difficulties in data processing of UAV photography. This can be caused by the UAVs natural flying movement, severe winds, turbulence, or unexpected operator inputs, all of which reduce accuracy. This blur disturbs the visual analysis and interpretation of the data, causes errors, and can degrade the accuracy. As a result, this approach proposes a method based on contrast-limited adaptive histogram equalization (CLAHE) and deblurring using Gaussian blur kernel as the solution. A variety of UAV datasets were used to verify the methods speed and reliability. This method proves to be fast and efficient, making the algorithm applicable for UAV dataset. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
AI-Driven Health Coach for Diabetes Management
Artificial intelligence (AI) is transforming diabetes care through innovative approaches that enhance monitoring, prediction, and treatment. AI-powered health coaches exemplify this progress by automating various aspects of patient care, such as creating personalized dietary plans and managing medication schedules, thereby optimizing resource utilization with minimal human intervention. In India, where diabetes affects over 77 million people and significantly elevates the risk of complications like heart disease and stroke, AI-driven tools offer immense potential. Food recognition and nutritional apps powered by AI can revolutionize diabetes management by tracking dietary intake and providing tailored recommendations. However, widespread adoption faces barriers, including challenges related to localization, cultural relevance, and integration with healthcare systems. This chapter examines the role of AI in diabetes management, evaluating the benefits and limitations of current applications. It also proposes a framework for an AI-driven health coach tailored to the Indian context. The proposed solution aims to bridge existing gaps by delivering accurate, culturally sensitive, and integrated diabetes management tools, ultimately improving long-term health outcomes for Indian patients. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
Tapestry of Promise and Peril: NLP, AI, and IoMT in Healthcare Transformation - A Review
This chapter investigates the intersection of NLP, AI, and IoMT in healthcare, as the former two will unlock the medical jargon to create accessible communication, while the latter enables real-time monitoring and decentralized clinical trials, thus providing predictive insights into personalized care plans. A systematic literature search was carried out using keywords in important academic databases that include PubMed, Scopus, and Google Scholar from 2022 to 2024. Shadows lurk amidst this optimism. Security and privacy concerns pertaining to IoMT data loom large. Decentralized trials are clouded by ethical concerns and regulatory hurdles. The specter of inequality threatens to increase the digital divide. To bridge this gap, a multipronged approach is crucial. Secure, privacy-preserving NLP and AI algorithms are the foundation. Robust IoMT infrastructure with blockchain-based security and interoperability standards is the framework. Clear, ethical frameworks for decentralized trials are the guiding threads. Ultimately, inclusivity is key. Bridging the digital divide and empowering patients and healthcare workers alike will ensure this future benefits all. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
Adverse Childhood Experiences, Psychological Well-wBeing, and Grit: A Comparative Study between LGBTQIA+ and Cis-Heterogeneous Sample of India
Adverse childhood experiences (ACEs) is a major concern that has been related to serious health consequences. Moreover, lesbian, gay, bisexual, transgender, intersex, asexual, and queer (LGBTQIA+) individuals are more likely to experience ACEs than cis-heterosexual individuals, especially in India. However, research in India has been scarce. This study compared these variables between Indian LGBTQIA+ individuals (n = 102) and cis-heterosexual individuals (n = 118) aged between 18 and 25. The findings of this comparative study reveal significant differences between LGBTQIA+ and cis-heterogeneous groups in terms of ACEs and grit levels. Notable differences were also discovered in three domains of psychological well-being: environmental mastery, positive interpersonal relationships, and self-acceptance. However, the vulnerability of LGBTQIA+ individuals in India reveals itself in descriptive statistics that report they are susceptible to negative outcomes in mental health. This study further emphasizes the importance of implementing focused interventions and support to increase psychological well-being and grit in the LGBTQIA+ community. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors.