Project description:BackgroundTo date, very few nationwide studies addressing the way in which mental health services are addressing the current pandemics have been published. The present paper reports data obtained from a survey relating to the Italian mental health system conducted during the first phase of the Covid-19 epidemic.MethodsTwo online questionnaires regarding Community Mental Health Centres (CMHC) and General Hospital Psychiatric Wards (GHPW), respectively, were sent to the Heads of all Italian Mental Health Departments (MHDs). Statistical analysis was carried out by means of Chi Square test with Yates correction or the Fisher Exact test, as needed.ResultsSeventy-one (52.9%) of the 134 MHDs and 107 (32.6%) of the 318 GHPWs returned completed questionnaires. Less than 20% of CMHCs were closed and approx. 25% had introduced restricted access hours. A substantial change in the standard mode of operation in CMHCs was reported with only urgent psychiatric interventions, compulsory treatments and consultations for imprisoned people continuing unchanged. All other activities had been reduced to some extent. Remote contacts with users had been set up in about 75% of cases. Cases of COVID positivity were reported for both staff members (approx. 50% of CHMCs) and service users (52% of CHMCs). 20% of CMHCs reported cases of increased aggressiveness or violence among community patients, although only 8.6% relating to severe cases. Significant problems emerged with regard to the availability of personal protective equipment (PPE) for staff members. A reduced number of GHPWs (- 12%), beds (approx.-30%) and admissions were registered (87% of GHPWs). An increase in compulsory admissions and the rate of violence towards self or others among inpatients was reported by 8% of GHPWs. Patient swabs were carried out in 50% of GHPWs. 60% of GHPWs registered the admission to general COVID-19 Units of symptomatic COVID+ non-severe psychiatric patients whilst COVID+ severe psychiatric patients who were non-collaborative were admitted to specifically set up "COVID-19" GHPWs or to isolated areas of the wards purposely adapted for the scope.ConclusionsThe pandemic has led to a drastic reduction in levels of care, which may produce a severe impact on the mental health of the population in relation to the consequences of the expected economic crisis and of the second ongoing wave of the pandemic.

Project description:BackgroundThe post-disaster mental health crisis intervention (MHCI) system in China remains immature and unsystematic. We aim to report the perceptions of a large sample of MHCI workers and government administrators and provide recommendations for developing a national mental health disaster response management plan in China.MethodsAn in-depth qualitative study was conducted, collecting data from 20 focus-group discussions and 25 key stakeholder interviews. These recruited participants who had been involved in different types of disaster rescue across 7 provinces/cities where disasters have recently occurred. We used thematic analysis to analyze the data and relevant findings were extracted for policy recommendation.ResultsMental health workers' perspectives were examined in detailed according to four core themes: forms of organization, intervention pathway, intervention strategy and technique, and public health information. Post-disaster MHCI should be approached in teams that are integrated with emergency medicine systems, and be led by unified command management. All levels of local health and family planning commission should prepare post-disaster MHCI work plans and build response teams/emergency centres. Future training for MHCI workers should focus on: building a sense of trust within the team; clarifying each member's role; strengthening the screening, assessment and referrals training for psychological professionals; and providing psychological intervention training for Chinese psychiatrists. It is necessary to set up guiding principles for disaster research ethics, mental health rehabilitation and media interaction.ConclusionsThrough exploring and analyzing the perceptions of current disaster response mental health workers and government administrators, our findings provide essential recommendations for developing a national to county level post-disaster MHCI emergency management plan and can guide the formulation of relevant laws and regulation in China.

Project description:BackgroundThe overload of healthcare systems around the world and the danger of infection have limited the ability of researchers to obtain sufficient and reliable data on psychopathology in hospitalized patients with coronavirus disease 2019 (COVID-19). The relationship between severe acute respiratory syndrome with the coronavirus 2 (SARS-CoV-2) infection and specific mental disturbances remains poorly understood.AimTo reveal the possibility of identifying the typology and frequency of psychiatric syndromes associated with acute COVID-19 using cluster analysis of discrete psychopathological phenomena.Materials and methodsDescriptive data on the mental state of 55 inpatients with COVID-19 were obtained by young-career physicians. Classification of observed clinical phenomena was performed with k-means cluster analysis of variables coded from the main psychopathological symptoms. Dispersion analysis with p level 0.05 was used to reveal the clusters differences in demography, parameters of inflammation, and respiration function collected on the basis of the original medical records.ResultsThree resulting clusters of patients were identified: (1) persons with anxiety; disorders of fluency and tempo of thinking, mood, attention, and motor-volitional sphere; reduced insight; and pessimistic plans for the future (n = 11); (2) persons without psychopathology (n = 37); and (3) persons with disorientation; disorders of memory, attention, fluency, and tempo of thinking; and reduced insight (n = 7). The development of a certain type of impaired mental state was specifically associated with the following: age, lung lesions according to computed tomography, saturation, respiratory rate, C-reactive protein level, and platelet count.ConclusionAnxiety and/or mood disturbances with psychomotor retardation as well as symptoms of impaired consciousness, memory, and insight may be considered as neuropsychiatric manifestations of COVID-19 and should be used for clinical risk assessment.

Project description:Disasters have substantial consequences for population mental health. Social media data present an opportunity for mental health surveillance after disasters to help identify areas of mental health needs. We aimed to 1) identify specific basic emotions from Twitter for the greater New York City area during Hurricane Sandy, which made landfall on October 29, 2012, and to 2) detect and map spatial temporal clusters representing excess risk of these emotions.We applied an advanced sentiment analysis on 344,957 Twitter tweets in the study area over eleven days, from October 22 to November 1, 2012, to extract basic emotions, a space-time scan statistic (SaTScan) and a geographic information system (QGIS) to detect and map excess risk of these emotions.Sadness and disgust were among the most prominent emotions identified. Furthermore, we noted 24 spatial clusters of excess risk of basic emotions over time: Four for anger, one for confusion, three for disgust, five for fear, five for sadness, and six for surprise. Of these, anger, confusion, disgust and fear clusters appeared pre disaster, a cluster of surprise was found peri disaster, and a cluster of sadness emerged post disaster.We proposed a novel syndromic surveillance approach for mental health based on social media data that may support conventional approaches by providing useful additional information in the context of disaster. We showed that excess risk of multiple basic emotions could be mapped in space and time as a step towards anticipating acute stress in the population and identifying community mental health need rapidly and efficiently in the aftermath of disaster. More studies are needed to better control for bias, identify associations with reliable and valid instruments measuring mental health, and to explore computational methods for continued model-fitting, causal relationships, and ongoing evaluation. Our study may be a starting point also for more fully elaborated models that can either prospectively detect mental health risk using real-time social media data or detect excess risk of emotional reactions in areas that lack efficient infrastructure during and after disasters. As such, social media data may be used for mental health surveillance after large scale disasters to help identify areas of mental health needs and to guide us in our knowledge where we may most effectively intervene to reduce the mental health consequences of disasters.

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Disaster psychiatry and homelessness: creating a mental health COVID-19 response.

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Disaster psychiatry and homelessness: creating a mental health COVID-19 response.

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