The acquisition and consolidation of motor skills are essential in our lives. Neural plasticity of the primary motor cortex (M1) is strongly involved in the consolidation of motor skills. Recent studies have shown that the M1 plasticity can be altered by prior neural activity, termed ‘Metaplasticity’. Consequently, if we can demonstrate effective interventions that enhance M1 plasticity, we might propose new methodologies to promote the consolidation of motor skills. Although a variety of interventions have been reported, our research group has focused on a unique intervention: water immersion (WI). Our research has shown several possibilities that WI can be a neuromodulation of increasing M1 plasticity by altering the activity of sensory-motor-related areas. Herein, we briefly summarised previous research on the consolidation of motor skills through motor learning and M1 plasticity and introduced unique neuromodulation using WI, which temporarily increased M1 plasticity, including previous and present studies in our research group.

Julia is a new programming language that was released in 2012. Similar to Python, in the future, Julia has the potential for use in numerical analysis applications. In this study, we developed a free software named J-Assist that automatically executes statistical analysis operations in Julia version 1.4, which could introduce and popularize Julia among researchers and clinicians in the field of health and medical welfare. J-Assist provides a simple graphical user interface and is easy to install. Through this study, we demonstrate that it is possible to configure a system that automatically executes calculations and scripts in Julia. We compare J-Assist with EZR and Jupyter Notebook. J-Assist can be considered a simpler version of EZR. However, the execution languages used in J-Assist and EZR are different. J-Assist is intended for users who are new to Julia and programming and want to use Julia for quick statistical analysis; by contrast, Jupyter Notebook is suitable for users who want to develop complex programs and perform other complex analyses in Julia. This study also discusses the limitations of the current J-Assist software and functions that might be added to it in the future to expand its applicability for statistical analysis.

This study examined the factors associated with nursing professionals' attitudes toward second-trimester abortion care. A cross-sectional survey of nursing professionals working in hospitals providing birthing services in Japan was conducted. The Japanese short version of the Utrecht Work Engagement Scale, the Professional Quality of Life Scale-Japanese version-V, and a measurement of nurses' job satisfaction with their work situation were employed. Overall, 266 nursing professionals responded (response rate 26.6%), of whom 236 (90.4%) who had experience of assistance in second-trimester abortions were included in the analysis. A logistic regression analysis identified the following factors to be associated with attitude towards the second-trimester abortion care: nursing occupational category, work position, years of experience, job satisfaction subscales including “Pay,” “Compassion Fatigue/Secondary Trauma” on the professional quality of life, and age. As compared to the nursing professionals with reluctant attitudes, those with active ones toward their role had higher work engagement, greater satisfaction with second-trimester abortion care, and lower compassion fatigue. Increasing the level of job satisfaction may prevent burnout among the nursing professionals. Furthermore, the development of well-designed training and support systems might augment active attitudes toward abortion care.

The characteristics of non-permanent employment are likely to have a negative impact on workers' physical and mental health. A growing number of studies worldwide have focused on the health effects of non-permanent employment. However, few studies assessed the association between non-permanent employment and mental health at the beginning of the COVID-19 pandemic in Japan. The present study aimed to clarify any differences in mental health, health- related quality of life (HRQOL), and socioeconomic factors between permanent and non-permanent workers in the early stage of the COVID-19 pandemic in Japan. This study was conducted from March to April 2020. Data for Japanese workers were collected using an anonymous, self-administered, web-based questionnaire. We used the Center for Epidemiological Studies Depression Scale (CES-D) to measure depressive symptoms, the Sense of Coherence (SOC) scale to assess stress-coping ability, and the EQ-5D-5L to assess HRQOL. The overall prevalence of depressive symptoms (CES-D scores ≥16) was 51.5%. Non-permanent workers had higher CES-D scores (permanent vs. nonpermanent workers: 15 [11-25] vs. 17 [12-26], p = 0.012), lower SOC scores (permanent vs. nonpermanent workers: 56 [50–61] vs. 51 [46–57], p < 0.001), and lower HRQOL scores (permanent vs. nonpermanent workers: 1.000 [0.823–1.000] vs. 0.895 [0.823–1.000], p < 0.001). Trend analysis showed an increase in the prevalence of depression symptoms from high-SOC to low-SOC groups, in both permanent and non-permanent whole workers. In low-SOC group of whole workers, median of CES-D score was higher, and HRQOL score was lower significantly. We observed significant negative correlation between SOC and CES-D scores, and significant positive correlation between SOC and HRQOL scores in all SOC groups. The straight-line regression slopes of CES-D and HRQOL versus SOC scores were significantly higher in low-SOC group. Our findings suggest that both mental health and HRQOL could be promoted in Japanese non-permanent workers by strengthening their SOC.