Engagement in volunteering activities by persons with multiple sclerosis in Switzerland.

BACKGROUND: Informal and formal volunteering engagement is a proxy for social integration and may have beneficial effects for physical and mental well-being in persons with multiple sclerosis (pwMS). As literature on the topic among the pwMS is lacking, this study aimed to determine frequency and type of volunteering performed by pwMS and to identify factors associated with volunteering. METHODS: Cross-sectional, self-reported data of 615 pwMS participating in the Swiss Multiple Sclerosis Registry were analyzed using descriptive statistics to determine frequency and type of volunteering engagement. Univariable and multivariable generalized linear models with binomial distribution and log link function were used to identify factors associated with volunteering. Age, sex, employment status and gait disability were added to the multivariable model as fixed confounders. Sociodemographic, health-, work- and daily activity-related factors were included in the analysis. RESULTS: About one third (29.4%) of participants reported engagement in volunteering activities, most often through charities (16.02%) and cultural organizations (14.36%). In the multivariable model, participants who had a university degree were more likely to volunteer than those with lower level of education (RR = 1.48 95% CI [1.14; 1.91]). The ability to pursue daily activities (as measured by the EQ-5D subscale) was strongly associated with participation in volunteering among pwMS. Compared with pwMS who had no or only slight limitations in daily activities, those with severe problems were markedly less likely to engage in volunteering (RR = 0.41, 95% CI [0.21; 0.80]) . Finally, pwMS who reported caring for and supporting their family (i.e., being a homemaker) were more likely to engage in volunteering activities than those who did not (RR = 1.52, 95% CI [1.15; 2.01]). CONCLUSION: Nearly one in three pwMS engaged in diverse volunteering activities. Having a university degree, being less limited in daily activities and being a homemaker increased the probability of pursuing volunteering activities. Contingent on individual-level motivations, resources or physical abilities, pwMS who experience challenges in performing daily activities or social barriers should be made aware of barrier-free offers of socially inclusive and volunteering activities, often provided by the national MS societies and health leagues.

Real-world disease-modifying therapy usage in persons with relapsing-remitting multiple sclerosis: Cross-sectional data from the Swiss Multiple Sclerosis Registry.

INTRODUCTION: Several disease-modifying therapies (DMTs), covering a broad spectrum of mechanisms of action, have been approved by regulatory agencies for the treatment of relapsing-remitting multiple sclerosis (RRMS). However, only little is known about the current real-world treatment situation in Switzerland. Based on data from a diverse population of 668 persons with RRMS from the Swiss Multiple Sclerosis Registry (SMSR), the present study aims to fill this gap with a descriptive, cross-sectional approach. METHODS: Data originated from the SMSR baseline questionnaire and follow-up surveys. Data on current health status and life situation in the last 6 months were extracted from the survey distributed throughout 2020 and 2021, while data on disease-modifying therapy (DMT) histories were included from preceding surveys. Initially, data was stratified into three DMT groups according to the current DMT status (NO (No DMT), CONTINUED (DMT started more than 6 months ago), and NEW (DMT started less than 6 months ago)). In a subsequent analysis, the sample was stratified into groups corresponding to the five most frequently prescribed DMTs. Self-reported outcomes including therapy discontinuation or interruption, relapses and side-effects in the last 6 months were analyzed per group. Life and health situation parameters were also determined and analyzed. RESULTS: The study population consisted of 445 (66.6%) individuals belonging to the CONTINUED, 84 (12.6%) to the NEW, and 139 (20.8%) to the NO group. Within the NO group, 24 (17.3%) reported relapses. Furthermore, self-reported relapses (28 (33.3%)), side-effects (39 (46.4%)), and treatment discontinuations or interruptions (30 (35.7%)) occurred more frequently in the NEW compared to the CONTINUED group (37 (8.3%), 125 (28.1%), 8 (1.8%), respectively). The three groups also differed with respect to age, time since diagnosis, number of symptoms, DMT history, and health-related quality of life. The five most frequently prescribed DMTs included fingolimod (33.4%), dimethyl fumarate (25.0%), ocrelizumab (23.6%), natalizumab (10.6%) and teriflunomide (7.5%). The frequency of self-reported relapses ranged from 9.7% to 13.6%. Notable differences were found in the number of self-reported side-effects, ranging from 9.1% with natalizumab to 56.7% with dimethyl fumarate. DISCUSSION: This cross-sectional analysis suggested that the majority of individuals with RRMS in Switzerland continuously receive tolerable DMT. However, groups not receiving DMT or struggling with side-effects or continued disease worsening while on DMT still persist. It is conceivable that the number of self-reported symptoms indicates the need for more detailed clarification of the DMT characteristics and expectations of treatment outcomes. Injectable DMTs no longer play a major role in the treatment of RRMS in Switzerland and a trend toward an early use of potent drugs is emerging.

The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing.

BACKGROUND: The increasing availability of "real-world" data in the form of written text holds promise for deepening our understanding of societal and health-related challenges. Textual data constitute a rich source of information, allowing the capture of lived experiences through a broad range of different sources of information (eg, content and emotional tone). Interviews are the "gold standard" for gaining qualitative insights into individual experiences and perspectives. However, conducting interviews on a large scale is not always feasible, and standardized quantitative assessment suitable for large-scale application may miss important information. Surveys that include open-text assessments can combine the advantages of both methods and are well suited for the application of natural language processing (NLP) methods. While innovations in NLP have made large-scale text analysis more accessible, the analysis of real-world textual data is still complex and requires several consecutive steps. OBJECTIVE: We developed and subsequently examined the utility and scientific value of an NLP pipeline for extracting real-world experiences from textual data to provide guidance for applied researchers. METHODS: We applied the NLP pipeline to large-scale textual data collected by the Swiss Multiple Sclerosis (MS) registry. Such textual data constitute an ideal use case for the study of real-world text data. Specifically, we examined 639 text reports on the experienced impact of the first COVID-19 lockdown from the perspectives of persons with MS. The pipeline has been implemented in Python and complemented by analyses of the "Linguistic Inquiry and Word Count" software. It consists of the following 5 interconnected analysis steps: (1) text preprocessing; (2) sentiment analysis; (3) descriptive text analysis; (4) unsupervised learning-topic modeling; and (5) results interpretation and validation. RESULTS: A topic modeling analysis identified the following 4 distinct groups based on the topics participants were mainly concerned with: "contacts/communication;" "social environment;" "work;" and "errands/daily routines." Notably, the sentiment analysis revealed that the "contacts/communication" group was characterized by a pronounced negative emotional tone underlying the text reports. This observed heterogeneity in emotional tonality underlying the reported experiences of the first COVID-19-related lockdown is likely to reflect differences in emotional burden, individual circumstances, and ways of coping with the pandemic, which is in line with previous research on this matter. CONCLUSIONS: This study illustrates the timely and efficient applicability of an NLP pipeline and thereby serves as a precedent for applied researchers. Our study thereby contributes to both the dissemination of NLP techniques in applied health sciences and the identification of previously unknown experiences and burdens of persons with MS during the pandemic, which may be relevant for future treatment.