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Background: The increased use of digital data in health research demands interdisciplinary collaborations to address its methodological complexities and challenges. This often entails merging the linear deductive approach of health research with the explorative iterative approach of data science. However, there is a lack of structured teaching courses and guidance on how to effectively and constructively bridge different disciplines and research approaches., Objective: This study aimed to provide a set of tools and recommendations designed to facilitate interdisciplinary education and collaboration. Target groups are lecturers who can use these tools to design interdisciplinary courses, supervisors who guide PhD and master's students in their interdisciplinary projects, and principal investigators who design and organize workshops to initiate and guide interdisciplinary projects., Methods: Our study was conducted in 3 steps: (1) developing a common terminology, (2) identifying established workflows for research question formulation, and (3) examining adaptations of existing study workflows combining methods from health research and data science. We also formulated recommendations for a pragmatic implementation of our findings. We conducted a literature search and organized 3 interdisciplinary expert workshops with researchers at the University of Zurich. For the workshops and the subsequent manuscript writing process, we adopted a consensus study methodology., Results: We developed a set of tools to facilitate interdisciplinary education and collaboration. These tools focused on 2 key dimensions- content and curriculum and methods and teaching style-and can be applied in various educational and research settings. We developed a glossary to establish a shared understanding of common terminologies and concepts. We delineated the established study workflow for research question formulation, emphasizing the "what" and the "how," while summarizing the necessary tools to facilitate the process. We propose 3 clusters of contextual and methodological adaptations to this workflow to better integrate data science practices: (1) acknowledging real-life constraints and limitations in research scope; (2) allowing more iterative, data-driven approaches to research question formulation; and (3) strengthening research quality through reproducibility principles and adherence to the findable, accessible, interoperable, and reusable (FAIR) data principles., Conclusions: Research question formulation remains a relevant and useful research step in projects using digital data. We recommend initiating new interdisciplinary collaborations by establishing terminologies as well as using the concepts of research tasks to foster a shared understanding. Our tools and recommendations can support academic educators in training health professionals and researchers for interdisciplinary digital health projects., (©Jana Sedlakova, Mina Stanikić, Felix Gille, Jürgen Bernard, Andrea B Horn, Markus Wolf, Christina Haag, Joel Floris, Gabriela Morgenshtern, Gerold Schneider, Aleksandra Zumbrunn Wojczyńska, Corine Mouton Dorey, Dominik Alois Ettlin, Daniel Gero, Thomas Friemel, Ziyuan Lu, Kimon Papadopoulos, Sonja Schläpfer, Ning Wang, Viktor von Wyl. Originally published in JMIR Medical Education (https://mededu.jmir.org), 23.01.2025.)

Introduction: Understanding the prevalence of multiple sclerosis (MS) provides information for healthcare planning and helps identify trends and patterns of disease occurrence. For Switzerland, the number of persons with MS (pwMS) was last estimated at approximately 15,000 in 2016. The study's objectives were to update estimates of MS prevalence and characterise the change in MS prevalence in Switzerland between 2016 and 2021, the last year with complete administrative data., Methods: The Swiss MS Registry (SMSR) is an ongoing, longitudinal study in Switzerland. It has previously established a methodology to assess the epidemiology of MS in Switzerland by integrating SMSR data with administrative data on reimbursement approvals for disease-modifying therapies (DMTs). Subsequently, the benchmark-multiplier method is applied to the combined data. Using the same methodology, we calculated overall and sex- and age-specific prevalence rates for 2021. Furthermore, we descriptively analysed changes since 2016 by comparing the prevalence figures and demographic and clinical characteristics of pwMS in both years., Results: We estimated the population of pwMS in Switzerland at 18,140 (95% simulation interval: 17,550-18,750), corresponding to a period prevalence of 200.8-214.5/100,000 inhabitants. Peak prevalence was observed in the 50- to 55-year age group. Compared to 2016, the 2021 estimate corresponds to a 20% increase (n = 3,000). Extrapolating from Swiss population growth, we estimated that one-fifth of the observed prevalence increase may be attributed to a rising population. The proportion of pwMS in the age range from 50 to 64 (32.5% vs. 35.9%) and above 65 (8.0% vs. 11.1%) years increased. Consequently, the median (interquartile range) age increased from 47 (37-55) to 49 (38-57) years. The median age at diagnosis (36 [28-45] years) and the female-to-male ratio (2.7:1) remained stable since 2016. The proportion of pwMS treated with DMTs increased from 62.1% to 69.0%, with the largest change observed in infusion therapies (15.7% vs. 23.3%)., Conclusion: The estimated MS prevalence in Switzerland has increased since the previous estimate in 2016, with a shift in peak prevalence towards older ages. Population growth explained around one-fifth of this increase, thus leaving room for contributions by additional factors, which require further investigation. The rising MS prevalence has several implications for healthcare, research, and society., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

Background: Although healthcare practitioners (HCPs) are a valuable source of social support, research on support provided by neurologists to older persons with multiple sclerosis (pwMS) remains limited., Objectives: To explore expectations of pwMS aged 55 years or older regarding MS care and to identify support types, met and unmet needs within their relationship with neurologists., Methods: Utilizing a mixed-methods approach, we analyzed survey data from Swiss Multiple Sclerosis Registry participants. Quantitative data included Likert scales gauging the importance of various aspects of MS care for pwMS both in and out of neurological care. Qualitative data were derived from three open-ended questions, focusing on neurologist-provided support for pwMS in neurological care. Data underwent descriptive and deductive thematic analysis, using Cutrona and Suhr framework for coding social support., Results: Among the 286 participants (median age 61.0 years, interquartile range (IQR) 57.0-66.0; median disease duration 23.5 years, IQR 15.0-31.0), 84.6% ( N  = 244) were under neurological care. Quantitative findings highlighted the significance of HCP expertise and consultation time. Qualitative analysis identified all social support domains in the neurologist-pwMS relationship, with informational support being most prevalent, followed by emotional support. Neurologists' expertise, availability, comprehensive advising, listening, and validation emerged as key themes. Unmet needs were relatively infrequent and concerned insufficient information on complementary medicine, empathy, and understanding of symptoms like fatigue., Conclusions: Older pwMS see neurologists as adequate providers of comprehensive support and particularly value neurologists' sufficient availability, informational and emotional support. Areas for improvement include attention to complementary medicine and empathy., (© The Author(s), 2024.)

Background: While potential risk factors for multiple sclerosis (MS) have been extensively researched, it remains unclear how persons with MS theorize about their MS. Such theories may affect mental health and treatment adherence. Using natural language processing techniques, we investigated large-scale text data about theories that persons with MS have about the causes of their disease. We examined the topics into which their theories could be grouped and the prevalence of each theory topic., Methods: A total of 486 participants of the Swiss MS Registry longitudinal citizen science project provided text data on their theories about the etiology of MS. We used the transformer-based BERTopic Python library for topic modeling to identify underlying topics. We then conducted an in-depth characterization of the topics and assessed their prevalence., Results: The topic modeling analysis identifies 19 distinct topics that participants theorize as causal for their MS. The topics most frequently cited are Mental Distress (31.5%), Stress (Exhaustion, Work) (29.8%), Heredity/Familial Aggregation (27.4%), and Diet, Obesity (16.0%). The 19 theory topics can be grouped into four high-level categories: physical health (mentioned by 56.2% of all participants), mental health (mentioned by 53.7%), risk factors established in the scientific literature (genetics, Epstein-Barr virus, smoking, vitamin D deficiency/low sunlight exposure; mentioned by 47.7%), and fate/coincidence (mentioned by 3.1%). Our study highlights the importance of mental health issues for theories participants have about the causes of their MS., Conclusions: Our findings emphasize the importance of communication between healthcare professionals and persons with MS about the pathogenesis of MS, the scientific evidence base and mental health., (© 2024. The Author(s).)

Qualitative research and mixed methods are core competencies for epidemiologists. In response to the shortage of guidance on graduate course development, we wrote a course development guide aimed at faculty and students designing similar courses in epidemiology curricula. The guide combines established educational theory with faculty and student experiences from a recent introductory course for epidemiology and biostatistics doctoral students at the University of Zurich and Swiss Federal Institute of Technology, Zurich. We propose a student-centred course with inverse classroom teaching and practice exercises with faculty input. Integration of student input during the course development process helps align the course syllabus with student needs. The proposed course comprises six sessions that cover learning outcomes in comprehension, knowledge, application, analysis, synthesis and evaluation. Following an introductory session, the students engage in face-to-face interviews, focus group interviews, observational methods, analysis and how qualitative and quantitative methods are integrated in mixed methods. Furthermore, the course covers interviewer safety, research ethics, quality in qualitative research and a practice session focused on the use of interview hardware, including video and audio recorders. The student-led teaching characteristic of the course allows for an immersive and reflective teaching-learning environment. After implementation of the course and learning from faculty and student perspectives, we propose these additional foci: a student project to apply learned knowledge to a case study; integration in mixed-methods; and providing faculty a larger space to cover theory and field anecdotes., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Introduction: Self-reports are a valuable and cost-effective method of data collection, though they can be influenced by bias. Limited evidence exists on the quality of self-reports by persons with multiple sclerosis (pwMS), particularly since more potent disease-modifying therapies (DMTs) have been introduced. This study aimed to assess the reliability and validity of self-reported DMT use and multiple sclerosis (MS) type in the Swiss Multiple Sclerosis Registry (SMSR) by comparing self-reports with reimbursement approval requests from the Swiss Association for Joint Tasks of Health Insurers., Methods: The self-reported and reimbursement approval data were linked using privacy-preserving methods based on information available in both databases, i.e., date of birth, canton of residence, sex, and year of MS diagnosis. The SMSR baseline questionnaire data was utilized for the main analysis, while the SMSR follow-up survey data was utilized for the sensitivity analysis. For both analyses, we compared self-reported data with reimbursement approval data that corresponded to the respective periods of the SMSR data collection. Thus, the main analysis included the entirety of the data over the six-year period, while the sensitivity analysis captured a more recent snapshot of the data. To assess reliability, we estimated agreement using Cohen's kappa, and for validity, we estimated accuracy parameters using reimbursement approvals as the reference standard. Univariable and multivariable logistic regression models were employed to investigate factors associated with discordance between self-reports and reimbursement approvals in the main analysis., Results: The main analysis included 446 participants, and the sensitivity analysis included 193 participants. The agreement between self-reported and reimbursement approval data for medication use was near-perfect in both analyses (κ = 0.87, 95% confidence interval (CI) 0.85, 0.90 and κ = 0.82, 95% CI 0.76, 0.88). However, the agreement between self-reported and reimbursement approval-documented MS types ranged from fair to moderate (κ = 0.37, 95% CI 0.25, 0.48 to κ = 0.61, 95% CI 0.46, 0.77). The accuracy estimates for self-reported DMT use were generally high (≥ 0.80) with narrow CIs, except for less frequently reported drugs. While the sensitivity and specificity for RRMS were high, there was a notable possibility of false-negative self-reports for RRMS (NPV = 0.33, 95% CI 0.22, 0.45), and false-positive reports for SPMS (PPV = 0.36, 95% CI 0.21, 0.54). Multivariable logistic regression models showed that age (OR = 1.07, 95% CI 1.04, 1.10 per year) and education level (OR = 0.27, 95% CI 0.11, 0.65) were associated with discordance in reported and documented MS types, whereas possession of Swiss citizenship (OR = 0.32, 95% CI 0.14, 0.72) was associated with discordance in DMT use., Conclusion: Self-reported DMT use in pwMS is a reliable and valid information source, with near-perfect agreement and high accuracy. Self-reported MS types showed fair to moderate agreement and varying accuracy, likely reflecting the complexity of diagnosing progressive forms of MS and access to DMTs. In population-based MS research, self-reports of MS types, and particularly DMT use, can serve as a suitable surrogate for healthcare provider data., Competing Interests: Declaration of Competing Interest Mina Stanikić, Julia Braun, Vladeta Ajdacic-Gross, Zina-Mary Manyali, Benjamin Victor Ineichen, Stefania Iaquinto, and Viktor von Wyl declare no competing interests. Özgür Yaldizli received grants from ECTRIMS/MAGNIMS, University of Basel, Pro-Patient Stiftung University Hospital Basel, Free Academy Basel, Swiss National Science Foundation, Swiss Multiple Sclerosis Society and advisory board/lecture and consultancy fees from Roche, Sanofi Genzyme, Allmirall, Biogen and Novartis. Christian P Kamm has received honoraria for lectures as well as research support from Biogen, Novartis, Almirall, Teva, Merck, Sanofi Genzyme, Roche, Janssen, Eli Lilly, Celgene and the Swiss MS Society. Ente Ospedaliero Cantonale (employer) received compensation for Chiara Zecca's speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Chiara Zecca is recipient of a grant for senior researchers provided by AFRI (Area Formazione accademica, Ricerca e Innovazione), EOC. Ente Ospedaliero Cantonale (employer) received compensation for Claudio Gobbi's speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Pasquale Calabrese has received honoraria for speaking at scientific meetings, serving at scientific advisory boards and consulting activities from Abbvie, Actelion, Almirall, Bayer-Schering, Biogen, EISAI, Lundbeck, Merck Serono, Novartis, Sanofi-Aventis and Teva. He also receives research grants from the Swiss Multiple Sclerosis Society, and the Swiss National Research Foundation., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Despite strong recommendations for coronavirus disease 2019 (Covid-19) vaccination by multiple sclerosis (MS) organizations, some persons with MS (pwMS) remain vaccine hesitant. The Swiss MS Registry conducted a survey to explore Covid-19 vaccine hesitancy, self-reported side effects and changes in MS symptoms following vaccination in adult pwMS., Methods: Self-reported data were analyzed cross-sectionally. Multivariable logistic regression was used to explore participant characteristics associated with Covid-19 vaccine hesitancy., Results: Of 849 respondents, 73 (8.6%) were unvaccinated. Hesitation to vaccinate was most often a personal preference (N = 42, 57.53%). Factors negatively associated with vaccine hesitancy included older age (OR = 0.97 per year, 95% CI [0.94, 0.99]) and regularly seeing healthcare professionals (OR = 0.25, 95% CI [0.07, 0.85]). A history of confirmed Covid-19 infection (OR = 3.38, 95% CI [1.69, 6.77]) and being underweight (OR = 4.50, 95% CI [1.52, 13.36]) were positively associated with vaccine hesitancy. Of 768 participants who provided information, 320 (41.2%) and 351 (45.2%) reported vaccination side effects after the first and second vaccinations, respectively. Changes in MS symptoms were reported by 49 (6.3%) participants after the first and 67 (9.0%) participants after the second vaccination, and were most often described as increased or new-onset fatigue (N = 17/49 (34.7%) after the first and N = 21/67 (31.3%) after the second dose)., Conclusions: Covid-19 vaccine hesitancy was low among surveyed pwMS. The risk of vaccine hesitancy was higher among younger pwMS, those with a history of Covid-19 infection, and those without regular contact with healthcare professionals., Competing Interests: Declaration of Competing Interest Mina Stanikić reports employment by Roche branch in Serbia, Roche d.o.o., from February 2019 to February 2020. Christian P Kamm has received honoraria for lectures as well as research support from Biogen, Novartis, Almirall, Teva, Merck, Sanofi Genzyme, Roche, Janssen, Eli Lilly, Celgene and the Swiss MS Society. Ente Ospedaliero Cantonale (employer) received compensation for Chiara Zecca's speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Chiara Zecca is recipient of a grant for senior researchers provided by AFRI (Area Formazione accademica, Ricerca e Innovazione), EOC. Ente Ospedaliero Cantonale (employer) received compensation for Claudio Gobbi's speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Anke Salmen has received speaker honoraria and/or travel compensation for activities with Bristol Myers Squibb, Novartis, Roche and research support of Baasch Medicus Foundation and the Swiss MS society, not related to this work. Andrew Chan has served on advisory boards for, and received funding for travel or speaker honoraria from Actelion-Janssen, Almirall, Bayer, Biogen, Celgene, Sanofi-Genzyme, Merck, Novartis, Roche and Teva, all for hospital research funds; and research support from Biogen, Genzyme and UCB. Eric Twomey, Milo A. Puhan, Vladeta Ajdacic-Gross and Viktor von Wyl declare no competing interests., (Copyright © 2023. Published by Elsevier B.V.)

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., Competing Interests: Declaration of Competing Interest Mina Stanikić reports employment by Roche branch in Serbia, Roche d.o.o., from February 2019 to February 2020. The employer of Chiara Zecca receives support for advisor activities, speaking or grants from Celgene, Genzyme, Lilly, Merck, Novartis, Roche, and grants from Abbvie, Almirall, Biogen Idec, Celgene, Genzyme, Lilly, Merck, Novartis, Roche, Teva Pharma. Pasquale Calabrese has received honoraria for speaking at scientific meetings, serving at scientific advisory boards and consulting activities from Abbvie, Actelion, Almirall, Bayer-Schering, Biogen, EISAI, Lundbeck, Merck Serono, Novartis, Sanofi-Aventis and Teva. He also receives research grants from the Swiss Multiple Sclerosis Society (SMSG), and the Swiss National Research Foundation. Mathias Mettler, Urban Schwegler, Chloé Sieber, Vladeta Ajdacic-Gross, Stephanie Rodgers, Christina Haag, Susanne Kägi, Irene Rapold and Viktor von Wyl declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Multiple sclerosis (MS) impacts education, future career pathways and working capability and therefore may negatively impact the financial situation of persons with MS (pwMS) in Switzerland. We therefore investigated the financial situation and its influencing sociodemographic and disease-specific factors of pwMS compared to the general Swiss population with focus on material deprivation (MD)., Methods: Data on the financial situation of pwMS were collected via a specific questionnaire added to the regular, semi-annual follow-up assessments of the Swiss Multiple Sclerosis Registry. Questions were taken in an unmodified format from the standardized "Statistics on Income and Living Conditions" (SILC) questionnaire 2019 of the Federal Statistical Office of Switzerland which evaluates the financial situation of the general Swiss population, enabling a direct comparison of pwMS with the general Swiss population., Results: PwMS were 1.5 times more frequently affected by MD than the general Swiss population (6.3% of pwMS versus 4.2% of the general Swiss population) which was confirmed in a multivariable logistic regression analysis of pooled SILC and Swiss Multiple Sclerosis Registry (SMSR) data. High symptom burden, having only mandatory schooling, well as having a pending disability insurance application (as opposed to no application or receiving benefits) were associated with a higher odds of MD whereas higher education, older age, having a Swiss citizenship, living with a spouse or a partner or being currently employed were independently associated with a lower odds of MD., Conclusion: MS has a negative impact on the financial situation and is associated with MD. PwMS with a high symptom burden at the transition from work force to receiving disability benefits appeared to be vulnerable for MD. Higher education, older age, having a Swiss citizenship, living with a spouse or a partner or being currently employed were independently associated with a lower odds of MD., Competing Interests: Declaration of Competing Interest Kamm CP has received honoraria for lectures as well as research support from Biogen, Novartis, Almirall, Teva, Merck, Sanofi Genzyme, Roche, Janssen, Eli Lilly, Celgene and the Swiss MS Society (SMSG). Sanak L has no disclosures to report. Von Wyl V has no disclosures to report. Chan A has received speakers’/board honoraria from Actelion (Janssen/J&J), Almirall, Bayer, Biogen, Celgene (BMS), Genzyme, Merck KGaA (Darmstadt, Germany), Novartis, Roche, and Teva, all for hospital research funds. He received research support from Biogen, Genzyme, and UCB, the European Union, and the Swiss National Foundation. He serves as associate editor of the European Journal of Neurology, on the editorial board for Clinical and Translational Neuroscience and as topic editor for the Journal of International Medical Research. Stanikic M reports employment by Roche branch in Serbia, Roche d.o.o. from February 2019 to February 2020. Zina-Mary Manjaly has no disclosures to report. Zecca C is recipient of a grant for senior reseachers provided by AFRI (Area Formazione accademica, Ricerca e Innovazione), EOC. Ente Ospedaliero Cantonale (employer) received compensation for C.Z.’s speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Calabrese P. has received speakers’/board honoraria from Almirall, Biogen, Celgene (BMS), Genzyme, Novartis, Roche, Schwabe and Teva., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

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., (©Deborah Chiavi, Christina Haag, Andrew Chan, Christian Philipp Kamm, Chloé Sieber, Mina Stanikić, Stephanie Rodgers, Caroline Pot, Jürg Kesselring, Anke Salmen, Irene Rapold, Pasquale Calabrese, Zina-Mary Manjaly, Claudio Gobbi, Chiara Zecca, Sebastian Walther, Katharina Stegmayer, Robert Hoepner, Milo Puhan, Viktor von Wyl. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 10.11.2022.)

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., (Copyright © 2022. Published by Elsevier B.V.)