Browsing by Author "Jha, JP"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Publication Assessment of Cardiopulmonary Fitness and Physical Activity in Health Science Students(Kathmandu University, 2024) Pun, DB; Jha, JP; Magar, BP; Thapa, BABSTRACT Background Insufficient physical activity and poor cardiopulmonary fitness increases the risk of chronic diseases and premature mortality. Sedentary lifestyle is observed among young health science students. Objective To assess cardiopulmonary fitness and physical activity levels among health science students at Jumla. Method A cross-sectional study was conducted on health science students at Karnali Academy, Jumla. Cardiopulmonary fitness was assessed using the Queen’s College Step Test to calculate VO2max. International Physical Activity Questionnaire was applied to measure physical activity in terms of Metabolic Equivalent of Task (MET) value. Data analysis utilized GNU-PSPP software with descriptive and inferential statistics. Result Total 107 students participated (56 females), aged 18-37 years. Their median VO2max was 40.05 ml/kg/min, significantly higher in males [51.69 (IQR 45.81 – 57.57)] than females [36.37 (IQR 34.90 – 38.58)] (p<0.001). Median weekly physical activity was 1030 MET-minutes/week, with males reporting higher levels [1436 (962 - 2670)] than females [678 (414 – 1103)] (p<0.001). VO2max had a positive correlation with total MET value per week (r = 0.504, p<0.001), and negative correlation with body adiposity (p<0.02). Multiple linear regression revealed physical activity level, sex, and BMI as significant predictors of VO2max (p<0.01). Conclusion Health science students at Karnali Academy have average levels of cardiopulmonary fitness and physical activity, lower in females. Targeted interventions can improve their fitness, benefiting the wider population in future. Further research should explore barriers to physical activity and factors influencing healthy lifestyle adoption among health science students in this region. KEY WORDS Exercise, Health occupations, Physical fitness, StudentsPublication Neurophysiology of Mindfulness Meditation: A Narrative Review Based on Buddhist Perspective(Kathmandu University, 2025) Joshi, B; Jha, JP; Karn, A; Shrestha, LABSTRACT Meditation, an inward journey to explore profound levels of consciousness rooted in Buddhism, has significant physical and psychological benefits, including enhanced well-being, improved concentration, emotional stability, and positive cognitive shifts. This narrative review consolidates past two decades of research on the neurophysiological effects of Buddhist mindfulness meditation based on neuroimaging findings, and aims to examine the Buddhist view of mindfulness meditation in relation to the structural and functional changes in the brain areas in health and diseases. Meditation practices, such as Vipassana in Buddhism, emphasize mindfulness and non-judgmental awareness of oneself and surrounding. Neuroimaging studies have revealed its significant impact on brain regions including structural changes involving anterior cingulate cortex (ACC), temporal lobe, insula, hippocampus, amygdala, thalamus and other areas. Four fundamental mechanisms summarize the mindfulness meditation: attention regulation, body awareness, emotion regulation, and a transformed self- perspective. The scientific explanation of effects of meditation is challenging, and we are only beginning to understand in neurophysiological terms. Previous research on mindfulness meditation has employed diverse methodological approaches, including self-reported measures, behavioral tasks and neuroimaging techniques; but there lacks a standardization, making it difficult to compare the findings. However, the cognitive processes are thought to underlie the potential benefits of mindfulness meditation in promoting mental well-being on an individual and societal level. This review highlights the mechanisms of mindfulness meditation to improve cognitive flexibility and promote mental well-being, in relation to Buddhist philosophy, with implications for individual and societal benefits. KEY WORDS Buddhism, Cognition, Consciousness, Meditation, Mindfulness, NeurophysiologyPublication Use of Artificial Intelligence in Medical Research: A SWOT Analysis(Kathmandu University, 2024) Jha, JP; Amgain, K; Joshi, LRABSTRACT As artificial intelligence (AI) tools are shaping our work, this article discusses a nuanced SWOT analysis, focusing on the applications of artificial intelligence in the area of medical research. It aims to evaluate the applications of artificial intelligence tools in medical research, discussing their implications for researchers, journals and the scientific community, addressing the growing concerns of using artificial intelligence tools in research and publication, evaluating its potential risks while harnessing the transformative potential. The analysis is complemented by a qualitative review of online resources, articles, blogs, interviews and podcasts, elucidating the prevailing themes in artificial intelligence-related considerations. The strengths highlight artificial intelligence’s capacity to accelerate research processes, particularly in diagnostics, drug production and data analysis. On the other hand, the weaknesses underscore concerns related to interpretability, biases, and ethical considerations, urging caution in artificial intelligence reliance. Opportunities arise in the form of explainable artificial intelligence, inclusive data practices, and enhanced model validation, while threats include issues of bias, privacy, overreliance and human exploitation. Such issues can be mitigated by collaboration from multiple experts and policymakers. The current state of artificial intelligence raises concerns about data quality, bias, transparency and ethical issues in its development and deployment. There is a need for collaborative efforts to establish ethical frameworks, regulations, and sustainability practices. A balanced approach, positioning AI as a collaborator that enhances human insights and creativity is recommended. KEY WORDS Artificial intelligence, Bias, Ethics, Medical research