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A Systematic Review of Multimodal Frameworks for Assessing Health Vulnerability in Academicians Across Ergonomic,
Pooja Oza1, Shraddha Phansalkar1, Aayush Shrivastava2
1MIT School of Computing, MIT Art, Design and Technology University, Pune 412201, India.
Abstract:
Background: Lifestyle challenges such as prolonged sitting, irregular dietary habits, high stress levels, and lack of physical activity have become increasingly common among working professionals. All these factors contribute to the risk of chronic diseases such as diabetes, heart disease, obesity, and high blood pressure, which in turn result in reduced work performance and quality of life and may further affect health services access through increase healthcare needs. The teaching environment, like many other work environments, is mentally, emotionally, and practically demanding, and it puts extra pressure on those who work in it. Academicians, who devote themselves to guiding young minds, often make unhealthy daily choices and face significant work-related stress, which can lead to serious long-term health problems. This review highlights that health and well-being are shaped not by a single factor such as diet, work patterns, or habits, but by their combined effect. Methods: A study of around 113 studies has highlighted that academicians usually feel drained and physically exhausted. Result: The factors like prolonged fasts, insufficient water intake, long-standing hours, long and continuous talking, and extended periods in the sitting position have added to their stress levels at the workplace. The most critical finding is that these factors do not affect in isolation but impact as a combined interaction. These issues influence each other, thus increasing the vulnerability to lifestyle disorders. Conclusions: This critical problem can be addressed with a Multimodal Assessment Framework that integrates teachers' data on dietary habits, workplace ergonomics, sleep quality, and levels of physical activity. The presented work also proposes a statistical technique with an Artificial Intelligence (AI) model, and generates Vulnerability Quotient (VQ) that show lifestyle disease-related exposure of the teachers, which may be further used to provide remedial interventions. These insights can further guide institutions and policymakers to design healthier, supportive, and sustainable teaching environments.
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