Natural language processing analysis of the theories of people with multiple sclerosis about causes of their disease

Christina Haag; Nina Steinemann; Vladeta Ajdacic-Gross; Jonas Tom Thaddäus Schlomberg; Benjamin Victor Ineichen; Mina Stanikić; Holger Dressel; Paola Daniore; Patrick Roth; Sabin Ammann; Pasquale Calabrese; Christian Philipp Kamm; Jürg Kesselring; Jens Kuhle; Chiara Zecca; Milo Alan Puhan; Viktor von Wyl

doi:10.1038/s43856-024-00546-3

Natural language processing analysis of the theories of people with multiple sclerosis about causes of their disease

Commun Med (Lond). 2024 Jun 24;4(1):122. doi: 10.1038/s43856-024-00546-3.

Authors

Christina Haag^{1

2}, Nina Steinemann¹, Vladeta Ajdacic-Gross¹, Jonas Tom Thaddäus Schlomberg^{2

3}, Benjamin Victor Ineichen^{4

5}, Mina Stanikić^{1

2}, Holger Dressel^{1

6}, Paola Daniore^{2

7}, Patrick Roth⁸, Sabin Ammann¹, Pasquale Calabrese⁹, Christian Philipp Kamm^{10

11}, Jürg Kesselring¹², Jens Kuhle^{13

14}, Chiara Zecca^{15

16}, Milo Alan Puhan¹, Viktor von Wyl^{17

18

19}

Affiliations

¹ Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
² Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland.
³ Psychedelic Research & Therapy Development, Department of Adult Psychiatry and Psychotherapy, Psychiatric University Clinic Zurich, University of Zurich, Zurich, Switzerland.
⁴ Center for Reproducible Science, University of Zurich, Zurich, Switzerland.
⁵ Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland.
⁶ Division of Occupational and Environmental Medicine, University of Zurich and University Hospital Zurich, Zurich, Switzerland.
⁷ Digital Society Initiative, University of Zurich, Zurich, Switzerland.
⁸ Department of Neurology & Brain Tumor Center, University Hospital and University of Zurich, Zurich, Switzerland.
⁹ Division of Molecular and Cognitive Neuroscience, Neuropsychology and Behavioral Neurology Unit, University of Basel, Basel, Switzerland.
¹⁰ Neurocentre, Lucerne Cantonal Hospital, Lucerne, Switzerland.
¹¹ Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
¹² Department of Neurology and Neurorehabilitation, Rehabilitation Center Valens, Valens, Switzerland.
¹³ Department of Neurology, University Hospital Basel and University of Basel, Basel, Switzerland.
¹⁴ Multiple Sclerosis Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel, Departments of Biomedicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
¹⁵ Multiple Sclerosis Center, Neurocenter of Southern Switzerland, EOC, Lugano, Switzerland.
¹⁶ Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland.
¹⁷ Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland. viktor.vonwyl@uzh.ch.
¹⁸ Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland. viktor.vonwyl@uzh.ch.
¹⁹ Digital Society Initiative, University of Zurich, Zurich, Switzerland. viktor.vonwyl@uzh.ch.

Abstract

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.

Plain language summary

Multiple sclerosis (MS) is a disease that affects the brain and spinal cord, causing a wide range of symptoms. Our study investigated what people living with the disease think causes MS. We analyzed the replies given by 486 people who were questioned about their MS to look for patterns in the responses. We identified 19 distinct themes, notably mental and work-related stress, genetics, and dietary factors, which we grouped into 4 categories: physical health, mental health, established scientific risk factors, and chance. We found that mental health problems were viewed as a key factor for MS. Our work highlights the need for healthcare professionals to have transparent conversations with people with MS about what is known about the disease course and potential causes. In addition, it highlights the importance of fully informing and supporting people with MS regarding their mental health.