Preferred and actual retirement age of oral and maxillofacial surgeons aged 55 and older in the Netherlands: a longitudinal study from 2003 to 2016

Analysis of Balance of Income and Expenditure and Optimal Retirement Age of Pension Insurance Co-Ordination Account Based on Improved Machine Learning Algorithm

Since the turn of the twenty-first century, the issue of aging has gained international attention. Both developed and developing nations are currently dealing with this issue. To ensure the sustained and healthy growth of the economy and society in the face of an aging society, it is especially important to establish a scientific old-age insurance system and a reasonable retirement system. We are all aware that the key indicators for the state to control the old-age insurance system in the old-age insurance system are the income and expenditure balance of the old-age insurance pooling account and the analysis of the ideal retirement age. In this paper, a better machine algorithm is used. By independently learning the rules present in a large amount of data and gaining new experience and knowledge, machine learning (ML) can increase computer intelligence and give computers decision-making abilities comparable to those of humans. In general, a machine learning algorithm uses the laws it derives from data to predict unknown data after automatically analysing the data. This study's findings suggest that the ideal retirement age and life expectancy are positively correlated, with the ideal retirement age's growth rate 12.57 percent higher than that of life expectancy.

A Nationwide Survey on Working Hours and Working Environment among Hospital Dentists in Japan

Sustainable human resource is one of the main issues in healthcare delivery and the way hospital dentists work has a significant impact on oral and dental healthcare services. This study is the first large-scale nationwide survey aiming to investigate the working hours including the working environment among hospital dentists in Japan. A total of 2914 hospital dentists responded to self-administered questionnaires from general hospitals (GHs) and medical educational institutions (MEIs) across the country. Among full-time dentists, the younger generation (i.e., those in their 20s and 30s) of both male and female dentists working in GHs engage in over 40 h of in-hospital clinical practice per week, apart from their self-learning hours. In contrast, the middle-aged dentists (i.e., those in their 40s and 50s) at MEIs work for more than 50 h on average due to the added teaching and research responsibilities. In a multiple logistic regression model using "more than 60 h of work per week" as the dependent variable, higher ORs (Odds Ratios) were found in males (OR = 1.83, 95%CI 1.50-2.22), MEIs (OR = 1.92, 1.52-2.42), and individuals specializing in dental and oral surgery (OR = 1.85, 1.47-2.32). Task-shifting was requested by 22.6% of the respondents for preventive care and dental guidance. Only a few male dentists experienced taking a parental leave and the peak distribution of working hours was shorter for females working in GHs. The support for child-rearing in the work environment is still insufficient and a consensus on the involvement of male dentists in childcare is needed.