Predictors for early and long-term readmission in involuntarily admitted patients.

BACKGROUND: It is a common aim to reduce psychiatric readmissions. Although risk factors for readmissions were described, specific data in the group of patients with potentially aversively experienced involuntary admissions are lacking. To better understand underlying mechanisms, it is important to identify factors that are linked to readmissions in this specific patient group, which is the purpose of the current paper. METHODS: A four-year cohort of N = 3575 involuntary admissions (IA) was followed-up for subsequent re-hospitalization. Demographic, administrative and clinical factors associated with short- (within 30 days) or long-term (> 30 days) readmissions were examined using logistic regression modelling. RESULTS: Almost half of all IA cases were readmitted within the observation period, whereof every fifth readmission was within the first month after discharge from the involuntary index hospitalization. Adjusted regression modelling revealed problematic substance use at admission and assisted living or homelessness as risk factors for readmission, while high functioning at discharge, anxiety disorders, no subsequent treatment after discharge or IA due to danger to others were negatively associated with readmission. Factors specifically linked to short-term readmission were substance use and personality disorders, abscondence or discharge by initiation of the clinic, as well as being discharged to any place except the patient's home. There were no specific risk-factors for long-term readmission. CONCLUSIONS: To prevent readmissions after IA, especially for patients at risk, the aim of treatment strategies should be to focus on intensive discharge planning, enable continuous treatment in the outpatient setting, and provide social support.

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

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.

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.