Aggregating Bipolar Opinions through Bipolar Assumption-based Argumentation (preprint)

We introduce a novel method to aggregate Bipolar Argumentation Frameworks expressing opinions of different parties in debates. We use Bipolar Assumption-based Argumentation (ABA) as an all-encompassing formalism for Bipolar Argumentation under different semantics. By leveraging on recent results on judgement aggregation in Social Choice Theory, we prove several preservation results for relevant properties of Bipolar ABA using quota and oligarchic rules. Specifically, we prove (positive and negative) results about the preservation of conflict-free, closed, admissible, preferred, complete, set-stable, well-founded and ideal extensions in Bipolar ABA, as well as the preservation of acceptability, acyclicity and coherence for individual assumptions. Finally, we illustrate our methodology and results in the context of a case study on opinion aggregation for the treatment of long COVID patients.

Conceptualizing Suicidal Behavior: Utilizing Explanations of Predicted Outcomes to Analyze Longitudinal Social Media Data (preprint)

The COVID-19 pandemic has escalated mental health crises worldwide, with social isolation and economic instability contributing to a rise in suicidal behavior. Suicide can result from social factors such as shame, abuse, abandonment, and mental health conditions like depression, Post-Traumatic Stress Disorder (PTSD), Attention-Deficit/Hyperactivity Disorder (ADHD), anxiety disorders, and bipolar disorders. As these conditions develop, signs of suicidal ideation may manifest in social media interactions. Analyzing social media data using artificial intelligence (AI) techniques can help identify patterns of suicidal behavior, providing invaluable insights for suicide prevention agencies, professionals, and broader community awareness initiatives. Machine learning algorithms for this purpose require large volumes of accurately labeled data. Previous research has not fully explored the potential of incorporating explanations in analyzing and labeling longitudinal social media data. In this study, we employed a model explanation method, Layer Integrated Gradients, on top of a fine-tuned state-of-the-art language model, to assign each token from Reddit users' posts an attribution score for predicting suicidal ideation. By extracting and analyzing attributions of tokens from the data, we propose a methodology for preliminary screening of social media posts for suicidal ideation without using large language models during inference.

The impact of COVID-19 pandemic and lockdown on emergency psychiatry department admissions (preprint)

Background: This study aimed to explore the impact of coronavirus disease 2019 pandemic and lockdown period (LP) measures on patients’ visits to psychiatric emergency department (PED) of Istanbul University-Cerrahpaşa, Cerrahpaşa Medical School. Methods: We conducted a retrospective cohort study comparing the number and characteristics of patients during the initial lockdown with visits in the pre- and post-lockdown months. We also investigated the number of monthly PED visits and hospitalizations between March 11, 2020-2021 and compared it to the same period in 2019 and between March 2021-2022. Results: PED visits in the initial LP in Istanbul increased by 109% compared to the pre-lockdown months in the previous year. Anxiety and depressive disorders were responsible for most of this increase. The decline in PED visits was 3.1% and 42% during the first and second year of the pandemic, respectively; however, among the major diagnostic categories, we found that the rates of anxiety, depressive disorders, and OCD increased significantly in the first year, while psychotic disorders declined and bipolar disorders remained the same. In the second year, there was a trend toward pre-pandemic year ratios. Conclusion: The present findings highlight the immediate and long-term effects of the COVID-19 pandemic and lockdown measures on patients’ admission to the PED.

Evaluating the buffering role of perceived social support and coping resources against the adult mental health impacts of COVID-19 psychosocial stress: a cross-sectional study in South Africa (preprint)

Objectives: Growing evidence has highlighted the global mental health impacts of the COVID-19 pandemic and lockdown, particularly in societies with pre-existing socioeconomic adversities and public health concerns. Despite the sudden and prolonged nature of many psychosocial stressors during the pandemic, recent studies have shown that communities utilized several coping mechanisms to buffer the mental health consequences of COVID-related stress. This paper examines the extent to which coping resources and social support buffered against the mental health effects of COVID-19 psychosocial stress among adults in South Africa. Materials & Methods: Adult participants (n=117) completed an online survey during the second and third waves of the COVID-19 pandemic in South Africa (January-July 2021), which assessed experiences of stress, coping resources, social support, and four mental health outcomes: depression, anxiety, post-traumatic stress disorder, and bipolar disorder. Moderation analyses examined the potential buffering role of coping resources and social support against the mental health effects of COVID-19 stress. Results: Adults reported elevated rates of psychiatric symptoms. Coping resources buffered against the poor mental health effects of COVID-19 psychosocial stress, whereas perceived social support did not significantly moderate the association between COVID-19 stress and adult mental health. Discussion: These results suggest that adults in our sample utilized a variety of coping resources to protect their mental health against psychosocial stress experienced during the COVID-19 lockdown and pandemic in South Africa. Additionally, existing mental health conditions and strained social relationships may have attenuated the potential stress-buffering effect of perceived social support on adult mental health.

Disparities in COVID-19 infection, hospitalisation and death in people with schizophrenia, bipolar disorder, and major depressive disorder: a cohort study of the UK Biobank.

People with severe mental illness (SMI; including schizophrenia/psychosis, bipolar disorder (BD), major depressive disorder (MDD)) experience large disparities in physical health. Emerging evidence suggests this group experiences higher risks of infection and death from COVID-19, although the full extent of these disparities are not yet established. We investigated COVID-19 related infection, hospitalisation and mortality among people with SMI in the UK Biobank (UKB) cohort study. Overall, 447,296 participants from UKB (schizophrenia/psychosis = 1925, BD = 1483 and MDD = 41,448, non-SMI = 402,440) were linked with healthcare and death records. Multivariable logistic regression analysis was used to examine differences in COVID-19 outcomes by diagnosis, controlling for sociodemographic factors and comorbidities. In unadjusted analyses, higher odds of COVID-19 mortality were seen among people with schizophrenia/psychosis (odds ratio [OR] 4.84, 95% confidence interval [CI] 3.00-7.34), BD (OR 3.76, 95% CI 2.00-6.35), and MDD (OR 1.99, 95% CI 1.69-2.33) compared to people with no SMI. Higher odds of infection and hospitalisation were also seen across all SMI groups, particularly among people with schizophrenia/psychosis (OR 1.61, 95% CI 1.32-1.96; OR 3.47, 95% CI 2.47-4.72) and BD (OR 1.48, 95% CI 1.16-1.85; OR 3.31, 95% CI 2.22-4.73). In fully adjusted models, mortality and hospitalisation odds remained significantly higher among all SMI groups, though infection odds remained significantly higher only for MDD. People with schizophrenia/psychosis, BD and MDD have higher risks of COVID-19 infection, hospitalisation and mortality. Only a proportion of these disparities were accounted for by pre-existing demographic characteristics or comorbidities. Vaccination and preventive measures should be prioritised in these particularly vulnerable groups.

Psychiatric polygenic risk as a predictor of COVID-19 risk and severity: insight into the genetic overlap between schizophrenia and COVID-19.

Despite the high contagion and mortality rates that have accompanied the coronavirus disease-19 (COVID-19) pandemic, the clinical presentation of the syndrome varies greatly from one individual to another. Potential host factors that accompany greater risk from COVID-19 have been sought and schizophrenia (SCZ) patients seem to present more severe COVID-19 than control counterparts, with certain gene expression similarities between psychiatric and COVID-19 patients reported. We used summary statistics from the last SCZ, bipolar disorder (BD), and depression (DEP) meta-analyses available on the Psychiatric Genomics Consortium webpage to calculate polygenic risk scores (PRSs) for a target sample of 11,977 COVID-19 cases and 5943 subjects with unknown COVID-19 status. Linkage disequilibrium score (LDSC) regression analysis was performed when positive associations were obtained from the PRS analysis. The SCZ PRS was a significant predictor in the case/control, symptomatic/asymptomatic, and hospitalization/no hospitalization analyses in the total and female samples; and of symptomatic/asymptomatic status in men. No significant associations were found for the BD or DEP PRS or in the LDSC regression analysis. SNP-based genetic risk for SCZ, but not for BD or DEP, may be associated with higher risk of SARS-CoV-2 infection and COVID-19 severity, especially among women; however, predictive accuracy barely exceeded chance level. We believe that the inclusion of sexual loci and rare variations in the analysis of genomic overlap between SCZ and COVID-19 will help to elucidate the genetic commonalities between these conditions.

Physical Activity in Adults with Schizophrenia and Bipolar Disorder: A Large Cross-Sectional Survey Exploring Patterns, Preferences, Barriers, and Motivating Factors.

Adults with severe mental ill health may have specific attitudes toward physical activity. To inform intervention development, we conducted a survey to assess the physical activity patterns, preferences, barriers, and motivations of adults with severe mental ill health living in the community. Data were summarised using descriptive statistics, and logistic regressions were used to explore relationships between physical activity status and participant characteristics. Five-hundred and twenty-nine participants (58% male, mean age 49.3 years) completed the survey. Large numbers were insufficiently active and excessively sedentary. Self-reported levels of physical activity below that recommended in national guidelines were associated with professional inactivity, consumption of fewer than five portions of fruit and vegetables per day, older age, and poor mental health. Participants indicated a preference for low-intensity activities and physical activity that they can do on their own, at their own time and pace, and close to home. The most commonly endorsed source of support was social support from family and friends. Common motivations included improving mental health, physical fitness, and energy levels. However, poor mental and physical health and being too tired were also common barriers. These findings can inform the development of physical activity interventions for this group of people.

Psychotic Symptoms After SARS-CoV-2 Infection.

ABSTRACT: This case series reports three middle-aged male patients with no prior history of psychiatric disorders who developed psychotic symptoms with manic characteristics after COVID-19 infection. They presented mystic and paranoid delusions associated with euphoria, logorrheic, insomnia, and bizarre behaviors. Two of them required psychiatric hospitalization and one received corticosteroids. Treatment with antipsychotic medication improved their symptoms in a few weeks. This case series reports the new-onset psychosis probably due to COVID-19 infection. Pathogenetic speculation about the probable causes of COVID-19 psychosis, such as inflammatory reaction and corticosteroid use, was done. Moreover, other probable causes of manic psychosis, such as late-onset bipolar disorder, were also considered and ruled out. There is a need for more research to determine the causality between psychotic symptoms and COVID-19 infection.

The Effect of COVID-19 Public Health Measures On Mental Health in California (preprint)

California was the first state to implement statewide public health measures, including lockdowns and curfews, to mitigate the transmission of SARS-CoV-2. The implementation of these public health measures may have had unintended consequences related to mental health for persons in California. This study is a retrospective review of electronic health records of patients who sought care in the University of California Health System to examine changes in mental health status during the pandemic. Data were extracted prior to the pandemic (March-October 2019) and during the pandemic (March-October 2020). Weekly values of new mental health disorders were extracted and further classified based on age. Paired t-tests were performed to test for differences in the occurrence of each mental health disorder for each age group. A two-way ANOVA was performed to assess for between-group differences. When compared with pre-pandemic diagnoses, persons aged 26-35 had the greatest increase in mental health diagnoses overall during the pandemic, specifically for anxiety, bipolar disorder, depression, mood disturbance, and psychosis. The mental health of persons age 25-35 were more affected than any other age group.

Loneliness and mood disorders: consequence, cause and/or unholy alliance?

PURPOSE OF REVIEW: People with persistent depressive disorders and with bipolar disorder are more likely to feel lonely than people in the general population. This evidence update focused on studies in the last 2 years, characterized by the COVID-19 pandemic and consequent social distancing directives. RECENT FINDINGS: Longitudinal studies identified that people who feel lonely are more likely to become depressed or to experience relapse of mood disorders. There is emerging evidence that feelings of loneliness or mandatory social isolation can precede manic episodes. Hence the relationship between loneliness and mood disorders is complex and bidirectional. Interventions were developed to reduce loneliness in people with mental health problems, including depressive disorders, through cognitive modification and/or supported socialisation. No loneliness-focused interventions have been specifically tailored to people with bipolar disorder. SUMMARY: Studies carried out before and during the COVID-19 pandemic found that feelings of loneliness can be both consequences and precursors of persistent depression and bipolar disorder. Mood symptoms and loneliness have a cumulative negative effect on physical and mental health outcomes. Conceptual overlaps and relations between loneliness and mood symptoms should be clarified in qualitative studies. Theory-driven intervention models should be developed and tested in methodologically robust studies.

CHARACTERISTICS OF ACUTE PSYCHIATRIC DISORDERS IN PATIENTS WITH COVID-19 IN A THIRD-LEVEL HOSPITAL IN PERU (preprint)

Objective: To describe the sociodemographic and clinical characteristics of acute psychiatric disorders in COVID-19 patients in an emergency department at a national reference psychiatry and mental health hospital. Methods: A descriptive observational study was performed. Data were collected from medical records of patients admitted by emergency according to the International Classification of Diseases (ICD-11). The group of patients with a first acute psychiatric episode vs. patients with more than one acute psychiatric episode were compared. Results: 110 patients were included; 61.8% corresponded to the female sex and the mean age was 36 years. 49.1% corresponded to schizophrenia, followed by acute polymorphic psychotic disorder (13.6%), bipolar disorder (10%), and depressive episodes (7.3%). Psychotic disorders and depressive episodes occurred in a higher percentage in the group with a first episode, 42.4% (p< 0.001), and 15.2% (p< 0.001), respectively. The episodes of schizophrenia were higher in the group of patients with previous episodes (63.6%). Conclusions: A higher frequency of cases of acute psychotic disorder and depressive disorders was found as the first episode in patients with COVID-19 infection; however, within the group with previous episodes, greater predominance of patients with acute disorders due to schizophrenia was found.

Strategies and foundations for scientific discovery in longitudinal studies of bipolar disorder.

Bipolar disorder (BD) is a complex and dynamic condition with a typical onset in late adolescence or early adulthood followed by an episodic course with intervening periods of subthreshold symptoms or euthymia. It is complicated by the accumulation of comorbid medical and psychiatric disorders. The etiology of BD remains unknown and no reliable biological markers have yet been identified. This is likely due to lack of comprehensive ontological framework and, most importantly, the fact that most studies have been based on small nonrepresentative clinical samples with cross-sectional designs. We propose to establish large, global longitudinal cohorts of BD studied consistently in a multidimensional and multidisciplinary manner to determine etiology and help improve treatment. Herein we propose collection of a broad range of data that reflect the heterogenic phenotypic manifestations of BD that include dimensional and categorical measures of mood, neurocognitive, personality, behavior, sleep and circadian, life-story, and outcomes domains. In combination with genetic and biological information such an approach promotes the integrating and harmonizing of data within and across current ontology systems while supporting a paradigm shift that will facilitate discovery and become the basis for novel hypotheses.

Psychiatric presentations and admissions during the first wave of Covid-19 compared to 2019 in a psychiatric emergency department in Berlin, Germany: a retrospective chart review.

BACKGROUND: Most studies agree that the Covid-19 pandemic and the subsequent lockdown had a negative impact on mental health. On the other hand, international studies have shown that psychiatric emergency departments (pED) experienced a decrease in presentations and admissions. METHODS: Retrospective chart review of all pED presentations and admissions during the first wave of Covid-19 pandemic in Germany (Covid-19 period: 3/2/20 to 05/24/20) in a psychiatric hospital in Berlin compared to 1 year earlier (pre-Covid-19 period). Descriptive statistics and logistic regression were performed. RESULTS: We observed no statistical significant changes in overall pED presentations and overall hospital admissions during the Covid-19 period compared to the pre-Covid-19 period (813 vs. 894, - 9.1%, p = 0.064 and (363 vs. 437, - 16.9%, p = 0.080 respectively). In the subgroup analysis, less patients with depressive disorders (p = 0.035) and with personality disorders (p = 0.002) presented to the pED, a larger number of presentations with schizophrenia was observed (p = 0.020). In the Covid-19 period, less patients with substance use disorder and paranoid schizophrenia were admitted to the hospital via the pED than in the pre-Covid-19 period (p = 0.035 and p = 0.006, respectively). Bed capacity was reduced in the Covid-19 period by - 32.8% (p <  0.001). Presentations in police custody were 13.7% (p = 0.029) higher during the Covid-19 compared to pre-Covid-19 period, with higher rates in female presentations (p = 0.008) and suicide attempts (p = 0.012) and less hospital admissions (p = 0.048). Logistic regression analyses revealed that positive predictors for pED presentation during Covid-19 period were police custody (p <  0.001), being redirected from another hospital (p <  0.001), suicide attempt (p = 0.038), suicidal thoughts (p = 0.004), presentation with paranoid schizophrenia (p = 0.001) and bipolar and manic disorders (p = 0.004), negative predictors were hospital admission (p <  0.001), depressive disorders (p = 0.021) and personality disorders (p <  0.001). CONCLUSIONS: A larger number of presentations in police custody during the Covid-19 period may represent untreated medical needs. This was seen predominantly in female patients, suggesting this subgroup might have suffered particularly under lockdown measures. Patients with paranoid schizophrenia were the only subgroup, which increased in absolute numbers, also suggesting a particular lockdown effect. Reduced bed capacity due to infection curbing measures is suggestive to have played an important role in augmenting the threshold for hospital admissions.

COVID-19 and first manic episodes: a systematic review.

Sars-CoV-2 is a respiratory virus that can access the central nervous system, as indicated by the presence of the virus in patients' cerebrospinal fluid and the occurrence of several neurological syndromes during and after COVID-19. Growing evidence indicates that Sars-CoV-2 can also trigger the acute onset of mood disorders or psychotic symptoms. COVID-19-related first episodes of mania, in subjects with no known history of bipolar disorder, have never been systematically analyzed. Thus, the present study assesses a potential link between the two conditions. This systematic review analyzes cases of first appearance of manic episodes associated with COVID-19. Clinical features, pharmacological therapies, and relationships with pre-existing medical conditions are also appraised. Medical records of twenty-three patients fulfilling the current DSM-5 criteria for manic episode were included. Manic episodes started, on average, after 12.71±6.65 days from the infection onset. Psychotic symptoms were frequently reported. 82.61% of patients exhibited delusions, whereas 39.13% of patients presented hallucinations. A large discrepancy in the diagnostic workups was observed. Mania represents an underestimated clinical presentation of COVID-19. Further studies should focus on the pathophysiological substrates of COVID-19-related mania and pursue appropriate and specific diagnostic and therapeutic workups.

Psychological Capital and Alienation among patients with COVID-19 infection: The mediating role of Social Support (preprint)

Background COVID-19 infection continues all over the world, causing serious physical and psychological impacts to patients. Patients with COVID-19 infection suffer from various negative emotional experiences such as anxiety, depression, mania, and alienation, which seriously affect their normal life and is detrimental to the prognosis. Our study is aimed to investigate the effect of psychological capital on alienation among patients with COVID-19 and the mediating role of social support in this relationship.Methods The data were collected in China by the convenient sampling method. A sample of 259 COVID-19 patients completed the psychological capital, social support and social alienation scale and the structural equation model was adopted to verify the research hypotheses.Results Psychological capital was significantly and negatively related to the COVID-19 patients’ social alienation (p < .01). And social support partially mediated the association between psychological capital and patients’ social alienation (p < .01).Conclusion Psychological capital is critical to predicting COVID-19 patients’ social alienation. Social support plays an intermediary role and explains how psychological capital alleviates the sense of social alienation among patients with COVID-19 infection.

Effects of acupuncture combined with medication on patients with COVID-19 complicated with bipolar disorder: A protocol of systematic review and meta-analysis.

BACKGROUND: There is growing evidence that coronavirus disease 2019 (COVID-19) can trigger acute episodes of mood disorders or psychotic symptoms. Reports on the treatment of COVID-19-related bipolar disorder (BD) are limited. Our study aimed to investigate the potential for new or recurrent BD due to COVID-19. We qualitatively evaluate clinical treatments (acupuncture combined with medication) and any potential pathophysiological links between infection and BD. METHODS: We searched Embase, PubMed, Cochrane Library, Web of Science and MEDLINE (via Web of Science), Scopus, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure Database, and the Wanfang Database from December 1, 2019, to September 15, 2022, to identify all articles on acupuncture combined with drugs used to treat COVID-19 complicated with bipolar disorders. Two researchers will screen the articles and extract the relevant information. RESULTS: The results will provide a systematic overview of the current evidence on the use of acupuncture combined with drug therapy to treat COVID-19 complicated with bipolar disorder. CONCLUSION: The conclusions of this study will help clarify the effects of acupuncture combined with drug therapy on patients with COVID-19-related BD.

Revolving Door Phenomenon and Related Factors in Schizophrenia, Bipolar Affective Disorder and Other Psychotic Disorders.

BACKGROUND: Patients with chronic mental illness are frequently hospitalized and discharged from psychiatry wards. This situation is referred to as the "revolving door phenomenon" (RDP). In addition to factors related to the patient and the disease, limited number of beds leading to shortened hospital stay are among the reasons associated with frequent hospitalization. This study aims to compare patients with RDP and patients with single hospitalization in terms of clinical, sociodemographic, and treatment-oriented characteristics in order to evaluate the risk factors causing frequent hospitalization. SUBJECTS AND METHODS: In this study, patients who were admitted and hospitalized between May 1, 2011 - May 1, 2016 were retrospectively evaluated from patient records. The RDP group consisted of 74 patients and the single-hospitalization group consisted of 59 patients who met inclusion criteria. RESULTS: The RDP group had significantly higher rates of male gender, ECT history, past suicide attempts, multiple drug treatment, clozapine use, legal incidents, and noncompliance to follow up following discharge compared to the single-hospitalization group (p<0.05). CONCLUSION: This study demonstrates that Turkey also has RDP patients with characteristics and hospitalization patterns similar to patients in countries with different cultural, social, and economic conditions. It is important to identify and correct factors that cause frequent hospitalization as it will reduce the burden of the health system as well as provide benefit to the patient.