Background: The world has witnessed increased adoption of large language models (LLMs) in the last year. Although the products developed using LLMs have the potential to solve accessibility and efficiency problems in health care, there is a lack of available guidelines for developing LLMs for health care, especially for medical education. Objective: The aim of this study was to identify and prioritize the enablers for developing successful LLMs for medical education. We further evaluated the relationships among these identified enablers. Methods: A narrative review of the extant literature was first performed to identify the key enablers for LLM development. We additionally gathered the opinions of LLM users to determine the relative importance of these enablers using an analytical hierarchy process (AHP), which is a multicriteria decision-making method. Further, total interpretive structural modeling (TISM) was used to analyze the perspectives of product developers and ascertain the relationships and hierarchy among these enablers. Finally, the cross-impact matrix-based multiplication applied to a classification (MICMAC) approach was used to determine the relative driving and dependence powers of these enablers. A nonprobabilistic purposive sampling approach was used for recruitment of focus groups. Results: The AHP demonstrated that the most important enabler for LLMs was credibility, with a priority weight of 0.37, followed by accountability (0.27642) and fairness (0.10572). In contrast, usability, with a priority weight of 0.04, showed negligible importance. The results of TISM concurred with the findings of the AHP. The only striking difference between expert perspectives and user preference evaluation was that the product developers indicated that cost has the least importance as a potential enabler. The MICMAC analysis suggested that cost has a strong influence on other enablers. The inputs of the focus group were found to be reliable, with a consistency ratio less than 0.1 (0.084). Conclusions: This study is the first to identify, prioritize, and analyze the relationships of enablers of effective LLMs for medical education. Based on the results of this study, we developed a comprehendible prescriptive framework, named CUC-FATE (Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability), for evaluating the enablers of LLMs in medical education. The study findings are useful for health care professionals, health technology experts, medical technology regulators, and policy makers.

This study aims to assess parameters like student perception and student satisfaction towards the interactive teaching-learning process (TLP), which may help teachers at different educational levels to teach more effectively. The teaching-learning process included general regulatory teaching, teacher preparation for learning, regulatory assessment, and student perception and planning for learning. A questionnaire was administered to a sample of classes 11th and 12th with various streams, including Mathematics, Biology, and Commerce as their majors in Central India. This study examined the impact of student perception on their satisfaction with the teaching-learning process (TLP). The results indicated that students’ perception of general regulatory teaching, preparation for learning & regulatory assessment significantly impact their satisfaction towards TLP, but preparation for learning and Regulatory assessment were not associated to satisfaction with teaching. However, it resulted in student learning positively. The findings further indicated that student satisfaction and learning are not different in-stream and class level.

Healthcare Waste Management (HCWM) is critical for public health and environmental sustainability. However, healthcare facilities face significant barriers to implementing sustainable HCWM practices, particularly in developing regions. Identifying and prioritizing these barriers is essential to developing practical solutions. This study aims to identify and rank barriers to sustainable HCWM using an integrated methodology. It seeks to provide actionable insights for policymakers and healthcare administrators to improve HCWM practices. The study employed a multi-method approach, combining a comprehensive literature review, expert consultations, and Grey Relational Analysis (GRA). The literature review identified 17 potential barriers across economic, social, technical, and regulatory dimensions. Eight experts from diverse sectors evaluated these barriers based on ten criteria. GRA was used to rank the barriers, and sensitivity analysis assessed the robustness of the rankings under varying parameters. The findings revealed that the most critical barriers include the lack of standardized guidelines and protocols, ineffective waste segregation, awareness and knowledge gaps, and inadequate training. Financial constraints and disposal infrastructure also ranked highly, highlighting systemic challenges in HCWM. Sensitivity analysis demonstrated that these rankings remained stable across varying conditions, affirming the robustness of the results. Addressing the prioritized barriers—mainly through policy standardization, enhanced training programs, and improved resource allocation—can significantly improve HCWM practices. This study underscores the need for a holistic approach integrating technical, social, and regulatory interventions to enhance sustainability in healthcare waste management.

Corporate sustainability has garnered increasing attention within the business community as corporations communicate to influence their stakeholders to build sustainable relationships. There has been a surge in research exploring its connection to firm performance, but existing studies lack a cohesive and concentrated approach. The aim of this study is to explore the trends of growth of publications; gauge the annual growth rate, annual ratio of growth, relative growth rate, doubling time, and scientific production index; predict future production levels; and look at the relationship between corporate sustainability and firm performance by analysing the literature as well as identifying clusters and links with the Sustainable Development Goals (SDGs). The top countries contributing to the research were China, India, and the United States, accounting for over 45% of the global publications. The study analysed a focused corpus of 65 documents from the Scopus database on specific subfields of corporate sustainability and firm performance, identifying five main thematic clusters related to environmental performance, financial performance, corporate sustainability reporting, corporate social performance, and green supply chain management, with significant citations related to 17 SDGs. The annual growth rate (AGR) of publications was found to be −2.88%, with an average of 4.06 publications per year. The relative growth rate (RGR) decreased from 0.69 in 2010 to 0.36 in 2023, and the doubling time (Dt.) increased from 1.00 in 2010 to 1.93 in 2023. Employing structured methods and the PRISMA protocol, this scientifically rigorous study points towards identification of research themes linking sustainability practices to firm performance. Exponential smoothing (Holt’s linear trend model) is employed to project future research output within the field. The significant trends include an increase in publication frequency since 2017, indicating a growth phase in the research field. The findings highlight the need for greater investigation from developing countries and the importance of integrating sustainability considerations into business strategies.