Background The COVID-19 pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multifaceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a “mental health tsunami”, the psychological effects of the COVID-19 crisis remain unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances. Objective Our study aims to provide insights regarding people’s psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support expressions in the pandemic context. Methods We obtained about 60 million Twitter streaming posts originating from the United States from March 24 to May 24, 2020, and compared these with about 40 million posts from a comparable period in 2019 to attribute the effect of COVID-19 on people’s social media self-disclosure. Using these data sets, we studied people’s self-disclosure on social media in terms of symptomatic mental health concerns and expressions of support. We employed transfer learning classifiers that identified the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examined the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 data sets. Results We found that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis—mental health symptomatic expressions have increased by about 14%, and support expressions have increased by about 5%, both thematically related to COVID-19. We also observed a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlighted that people express concerns that are specific to and contextually related to the COVID-19 crisis. Conclusions We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people’s mental health symptomatic and support expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their “new normal.” Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, health care and precautionary measures, and pandemic-related awareness. This study shows the potential to provide insights to mental health care and stakeholders and policy makers in planning and implementing measures to mitigate mental health risks amid the health crisis.

We describe two patients with Gilles de la Tourette's syndrome (TS) and disabling obsessive-compulsive and ritualistic behaviors who underwent bilateral radiofrequency anterior cingulotomy. Both achieved a limited but sustained improvement in behavioral symptoms and overall functional abilities. Our observations indicate involvement of limbic structures in this disorder. The procedure should be considered for patients with TS complicated by resistant obsessive-compulsive disorder.

National suicide prevention programmes that have been successful in reducing rates or keeping them low have been intentional, with collective alignment of local, regional and national priorities. Prevention efforts must begin well before individuals become suicidal, complementing readily available clinical services that address the needs of acutely distressed persons. These efforts, which focus on the antecedent risks and vulnerabilities of key populations, have the potential to diminish premature mortality from multiple causes, even as reducing suicide is the outcome of primary interest. In this commentary, I consider four key challenges that must be confronted in order to develop effective, broadly reaching systemic strategies that, at once, can be adapted locally while being implemented nationally – challenges that are framed in a social–ecological context. They involve defining the scope of the problem, meeting essential data needs, developing and modelling measurable implementation strategies and building prevention efforts based on shared culture and values.

Background: The novel coronavirus disease 2019 (COVID-19) pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multi-faceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a mental health tsunami, the psychological effects of the COVID-19 crisis remains unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances. Objective: Our work aims to provide insights regarding people's psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support-seeking expressions in the pandemic context. Methods: We obtain 60M Twitter streaming posts originating from the U.S. from March, 24 to May, 25, 2020, and compare these with 40M posts from a comparable period in 2019 to causally attribute the effect of COVID-19 on people's social media self-disclosure. Using these datasets, we study people's self-disclosure on social media in terms of symptomatic mental health concerns and expressions seeking support. We employ transfer learning classifiers that identify the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examine the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 datasets. Results: We find that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis, mental health symptomatic expressions have increased by ~14%, and support seeking expressions have increased by 5%, both thematically related to COVID-19. We also observe a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlight that people express concerns that are contextually related to the COVID-19 crisis. Conclusions: We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people's mental health symptomatic and support-seeking expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their new normal. Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, healthcare and precautionary measures, and pandemic-related awareness. This work shows the potential to provide insights to mental healthcare and stakeholders and policymakers in planning and implementing measures to mitigate mental health risks amidst the health crisis.

Thirty multiple sclerosis patients were assessed: 15 with predominantly cerebral involvement of their demyelinating disease and 15 with predominantly spinal cord and cerebellar involvement. The groups were matched with regard to age, duration of illness, and Kurtzke disability scores. Assessment included neuropsychological testing, the Beck Depression Inventory, and a psychiatric interview patterned after the Schedule for Affective Disorders and Schizophrenia. A group of normal volunteers served as controls for the neuropsychological testing. There were significantly more major depressive episodes in the cerebral group, as assessed by the patients' histories and by interview, and there was a trend toward more depressive symptoms in this group, as measured by the Beck inventory.