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The present study examines the fluctuations in Socioeconomic and demographic (SED) factors and the prevalence of Non-Communicable Diseases (NCDs) across clusters of states in India. Further, it attempts to analyze the extent to which the SED determinants can serve as predictive indicators for the prevalence of NCDs.

The study uses three rounds of unit-level National Sample Survey self-reported morbidity data for the analysis. A machine learning model was constructed to predict the prevalence of NCDs based on SED characteristics. In addition, probit regression was adopted to identify the relevant SED variables across the cluster of states that significantly impact disease prevalence.

Overall, the study finds that the disease prevalence can be reasonably predicted with a given set of SED characteristics. Also, it highlights age as the most important factor across a cluster of states in understanding the distribution of disease prevalence, followed by income, education, and marital status. Understanding these variations is essential for policymakers and public health officials to develop targeted strategies that address each state’s unique challenges and opportunities.

The study complements the existing literature on the interplay of SEDs with the prevalence of NCDs across diverse state-level dynamics. Its predictive analysis of NCD distribution through SED factors adds valuable depth to our understanding, making a notable contribution to the field.

The article aims to provide a bibliometric and content analysis of the business application of blockchain technology.

Bibliometric analysis and content analysis were undertaken to accomplish the stated objectives of the study.

The results revealed publication and country collaboration trends, declining, emerging, and niche research areas, the topmost influential articles, authors, and most relevant journals.

As researchers have been myopic towards some mainstream research agendas studying the specific contexts of blockchain applications, this research believes a holistic approach to understanding blockchain technology's versatility to disrupt different business processes across a myriad of industries is lacking. In addition, to strengthen the research's conclusions, a content analysis of the most significant articles is conducted as part of the study.

To understand how Indian first-time mothers in STEM (Science, Technology, Engineering and Math) organisations returning to work cope with the perceived ideological psychological contract breaches from a work–home resources perspective.

This paper utilises interpretative phenomenological analysis (IPA) within the work–home resources (W-HR) model to analyse returning first-time mothers' lived experiences.

This study shows that significant life/work events such as childbirth/lack of career growth can trigger resource depletion at work and home and materialise in first-time mothers perceiving ideological psychological contract breaches at work. It has also been observed that key resource usage and macro support structures aid employees in attenuating work–home conflict by balancing contextual demands and personal resources. This study's participant accounts reveal that the recovery of volatile resources was possible by psychologically detaching and being silent.

The study offers a distinctive perspective by investigating the ideological PC breach experienced by first-time Indian mothers upon their organisational re-entry from a work–home resource model lens. Situated in a unique socio-cultural space and bringing forth the rich lived experiences of women working in the Indian STEM field, this paper explores how key resources shape the coping responses of first-time mothers in this context.