Rezki Amelia Aminuddin A.p., Hari Purnomo, Hartomo Soewardi,
Volume 0, Issue 0 (10-2025)
Abstract
The rapid digitalization of higher education in Indonesia has transformed teaching practices but also presents serious obstacles to the physical and emotional well-being of lecturers. This study examines the impact of ergonomic policies on lecturer well-being through the integration of macroergonomics and social engineering perspectives and formulates policies for improving lecturer emotional well-being. To collect information, the study used different methods, including a survey of 100 lecturers with established tools like the Positive and Negative Affect Schedule (PANAS), Perceived Stress Scale (PSS), and ergonomic condition assessment, as well as personal insights from interviews with 10 chosen lecturers. The digital training program and the unergonomic work environment significantly contributed to increased levels of stress and emotional exhaustion. Specifically, 60% of lecturers reported back pain, 55% experienced eye strain, and 50% reported high levels of negative affect. Interview results corroborated these issues and revealed a widespread lack of institutional support. The strategy designed was an integrated ergonomic intervention, including furniture adjustments, enhanced digital skills development, and comprehensive mental health support, to improve lecturer productivity and emotional well-being.
Mehrdad Jalali Sepehr, Abdorrahman Haeri, Rouzbeh Ghousi,
Volume 30, Issue 4 (12-2019)
Abstract
Abstract
Background: In this paper healthcare condition of 31 countries that are the members of Organization for Economic and Co-operative Development (OECD) is measured by considering 14 indicators that are relevant to three main pillars of sustainable development.
Method: To estimate the efficiency scores, Principle Component Analysis-Data Envelopment Analysis PCA-DEA additive model in both forms of envelopment and multiplier is used to determine efficiency scores and also to define benchmarks and improvement plan for the inefficient countries. Then Decision Tree Analysis is also used to realize that which factors were the most influential ones to make a county an efficient Decision Making Unit (DMU).
Results: According to the PCA-DEA additive model, among 31 OECD countries, 16 countries have become inefficient, that USA have taken the lowest efficiency score, and among efficient countries Iceland could be considered as a paragon which has the highest frequency between the countries that are defined as the benchmarks. Decision tree analysis also show that exposure to PM2.5 is an influential factor on the efficiency status of countries.
Conclusion: This research gives an insight about the sustainable development and healthcare system and show the impressive effect of environmental and social factors like: exposure to PM2.5 and water quality, population insurance coverage, and AIDS on the healthcare efficiency of OECD countries
