Disaster management: Mental health perspective

Disaster mental health is based on the principles of ′preventive medicine′ This principle has necessitated a paradigm shift from relief centered post-disaster management to a holistic, multi-dimensional integrated community approach of health promotion, disaster prevention, preparedness and mitigation. This has ignited the paradigm shift from curative to preventive aspects of disaster management. This can be understood on the basis of six ′R′s such as Readiness (Preparedness), Response (Immediate action), Relief (Sustained rescue work), Rehabilitation (Long term remedial measures using community resources), Recovery (Returning to normalcy) and Resilience (Fostering). Prevalence of mental health problems in disaster affected population is found to be higher by two to three times than that of the general population. Along with the diagnosable mental disorders, affected community also harbours large number of sub-syndromal symptoms. Majority of the acute phase reactions and disorders are self-limiting, whereas long-term phase disorders require assistance from mental health professionals. Role of psychotropic medication is very limited in preventing mental health morbidity. The role of cognitive behaviour therapy (CBT) in mitigating the mental health morbidity appears to be promising. Role of Psychological First Aid (PFA) and debriefing is not well-established. Disaster management is a continuous and integrated cyclical process of planning, organising, coordinating and implementing measures to prevent and to manage disaster effectively. Thus, now it is time to integrate public health principles into disaster mental health

Two Years Beyond COVID-19: Unveiling the Persistence of Neuropsychiatric Symptoms and Risk Factors in a Cross-Sectional Study

Aims The neuropsychiatric morbidities associated with post-COVID status are important public health issues. The range and severity of morbidity varies with the type of clinical setting and time of assessment. There are limited studies on the long-term persistence of the post-COVID neuropsychiatric symptoms (PCNS). Hence, this study aims to determine the proportion of persistent PCNS after approximately 2 years of COVID and to find any risk factors for persistent PCNS. Methods This study was a cross-sectional study of randomly selected 2,281 individuals aged 18–60 years, currently living in the community, who were RT-PCR positive for COVID-19 from the National Institute of Mental Health and Neurosciences (NIMHANS) laboratory (at least 4 weeks before intake) from a period of 1 June 2020 to 31 March 2022. Among them, 927 individuals who met the study criteria were screened for PCNS through telephone interviews using a validated PCNS screening tool comprising sociodemographic details, life events inventory and 20 questions to assess for PCNS. 196 individuals who came positive for PCNS were further evaluated by in-person or web-based interviews with Structured Clinical Interviews for DSM–5-Research Version and World Health Organization-Post-COVID Case Report Form for persistent PCNS. Descriptive statistics, Chi2 test, Mann–Whitney U Test, and Binary logistic regression analysis were used for data analysis. The Institutional Ethics Committee approved this study. Results The median age of study participants was 34 years, and 51.3% were female. 68 out of 196 participants (34.7%) had persistent PCNS approximately 2 years (23.84 months) after COVID-19 infection. Chronic fatigue (10.2%), depression (6.1%), cognitive symptoms (4%), hyposmia (3.6%), hypogeusia (3.6%), anxiety (2.5%), panic disorder (2.5%) and insomnia (2%) are the main persistent symptoms. The median age of the participants with persisted PCNS (40 years) is higher compared with the median age of the participants without persisted PCNS (34 years) [Mann–Whitney U = 5,225.0, P = 0.021]. Even though significant associations were found between the development of PCNS after 4 weeks of COVID and female gender, symptomatic COVID-19, severity of COVID-19 (oxygen supplementation), hospital admission, total number of times of COVID-19, and presence of life events, this association were not found with persistence of PCNS at 2 years. Conclusion This study revealed that one-third of the individuals with PCNS had persistent symptoms after 2 years. Chronic fatigue is the most common persistent PCNS. Middle-aged and above age groups were found to be a risk factor for persistent PCNS

Legalization of recreational cannabis: Is India ready for it?

Cannabis is one of the oldest psychoactive substances in India and worldwide. Many developed countries like Canada, Netherlands and few states of the USA have legalized the use of recreational cannabis. However, In India, the recreational use of cannabis and its various forms such as ganja, charas, hashish, and its combination is legally prohibited. There have been several discussions and public interest litigations in India regarding the legalization of recreational cannabis use and its benefits. With this background, this article addresses the various implications of legalizing recreational use of cannabis, a multibillion dollar market and its impact on mental health, physical health, social, cultural, economic, and legal aspects with the lessons learnt from other countries that have already legalized recreational cannabis use. It also discusses whether India is prepared for the legalization of recreational cannabis, given the current criminal justice and healthcare systems. The authors conclude that, India is perhaps not enough prepared to legalize cannabis for recreational use. India's existing criminal justice and healthcare systems are overburdened, finding it challenging to control medicinal use, which is often the first contact point for cannabis-related concerns

Discovery biology of neuropsychiatric syndromes (DBNS): a center for integrating clinical medicine and basic science

Abstract Background There is emerging evidence that there are shared genetic, environmental and developmental risk factors in psychiatry, that cut across traditional diagnostic boundaries. With this background, the Discovery biology of neuropsychiatric syndromes (DBNS) proposes to recruit patients from five different syndromes (schizophrenia, bipolar disorder, obsessive compulsive disorder, Alzheimer’s dementia and substance use disorders), identify those with multiple affected relatives, and invite these families to participate in this study. The families will be assessed: 1) To compare neuro-endophenotype measures between patients, first degree relatives (FDR) and healthy controls., 2) To identify cellular phenotypes which differentiate the groups., 3) To examine the longitudinal course of neuro-endophenotype measures., 4) To identify measures which correlate with outcome, and 5) To create a unified digital database and biorepository. Methods The identification of the index participants will occur at well-established specialty clinics. The selected individuals will have a strong family history (with at least another affected FDR) of mental illness. We will also recruit healthy controls without family history of such illness. All recruited individuals (N = 4500) will undergo brief clinical assessments and a blood sample will be drawn for isolation of DNA and peripheral blood mononuclear cells (PBMCs). From among this set, a subset of 1500 individuals (300 families and 300 controls) will be assessed on several additional assessments [detailed clinical assessments, endophenotype measures (neuroimaging- structural and functional, neuropsychology, psychophysics-electroencephalography, functional near infrared spectroscopy, eye movement tracking)], with the intention of conducting repeated measurements every alternate year. PBMCs from this set will be used to generate lymphoblastoid cell lines, and a subset of these would be converted to induced pluripotent stem cell lines and also undergo whole exome sequencing. Discussion We hope to identify unique and overlapping brain endophenotypes for major psychiatric syndromes. In a proportion of subjects, we expect these neuro-endophenotypes to progress over time and to predict treatment outcome. Similarly, cellular assays could differentiate cell lines derived from such groups. The repository of biomaterials as well as digital datasets of clinical parameters, will serve as a valuable resource for the broader scientific community who wish to address research questions in the area

Sample size requirement for achieving multisite harmonization using structural brain MRI features

When data is pooled across multiple sites, the extracted features are confounded by site effects. Harmonization methods attempt to correct these site effects while preserving the biological variability within the features. However, little is known about the sample size requirement for effectively learning the harmonization parameters and their relationship with the increasing number of sites. In this study, we performed experiments to find the minimum sample size required to achieve multisite harmonization (using neuroHarmonize) using volumetric and surface features by leveraging the concept of learning curves. Our first two experiments show that site-effects are effectively removed in a univariate and multivariate manner; however, it is essential to regress the effect of covariates from the harmonized data additionally. Our following two experiments with actual and simulated data showed that the minimum sample size required for achieving harmonization grows with the increasing average Mahalanobis distances between the sites and their reference distribution. We conclude by positing a general framework to understand the site effects using the Mahalanobis distance. Further, we provide insights on the various factors in a cross-validation design to achieve optimal inter-site harmonization