Embracing resilience in multiple sclerosis: a new perspective from COVID-19 pandemic.

Coronavirus disease 2019 (COVID-19) resulted in several psychological consequences. Past epidemiological experiences already showed the deep albeit heterogeneous psychological repercussions of pandemics. Nevertheless, little is known about COVID-19 outbreak and the possible strategies for boosting resilience in patients with chronic diseases such as Multiple Sclerosis (MS). Therefore, we designed a study aiming to assess the changes in mental distress during COVID-19 outbreak in patients with MS and to identifyfactors contributing to resilience's development.We enrolled 106 patients (69 relapsing-remitting, 20 secondary-progressive, and 17 primary-progressive) whose neuropsychological assessment before the COVID-19 pandemic (1 January 2019-1 March 2020) was available. It consisted of Brief International Cognitive Assessment for MS (BICAMS), Hospital Anxiety and Depression Scale (HADS) and patient-reported MS Neuropsychological Screening Questionnaire (MSNQ-P). All patients were re-tested during Italian lockdown through an online survey, comprehensive of sociodemographic information, HADS self-rating Scale, MSNQ-P Questionnaire and finally Connor-Davidson Resilience self-rating Scale (CD-RISC 25), in order to evaluate resilience.No significant changes in HADS and MSNQ-P scores were detected during COVID-19 pandemic in our population. Though, pre-existing lower HADS and MSNQ-P scores but not demographic, disease- and treatment-related elements were found significantly (p < 0.0001) and independently associated with a better resilience attitude.

Transnational Research Networks in Chinese Scientific Production. An Investigation on Health-Industry Related Sectors.

Transnational research networks (TRN) are becoming increasingly complex. Such complexity may have both positive and negative effects on the quality of research. Our work studies the evolution over time of Chinese TRN and the role of complexity on the quality of Chinese research, given the leading role this country has recently acquired in international science. We focus on the fields of geriatrics and gerontology. We build an original dataset of all scientific publications of China in these areas in 2009, 2012 and 2015, starting from the ISI Web of Knowledge (ISI WoK) database. Using Social Network Analysis (SNA), we analyze the change in scientific network structure across time. Second, we design indices to control for the different aspects of networks complexity (number of authors, country heterogeneity and institutional heterogeneity) and we perform negative binomial regressions to identify the main determinants of research quality. Our analysis shows that research networks in the field of geriatrics and gerontology have gradually become wider in terms of countries and have become more balanced. Furthermore, our results identify that different forms of complexity have different impacts on quality, including a reciprocal moderating effect. In particular, according to our analysis, research quality benefits from complex research networks both in terms of countries and of types of institutions involved, but that such networks should be "compact" in terms of number of authors. Eventually, we suggest that complexity should be carefully taken into account when designing policies aimed at enhancing the quality of research.