Internet addiction in adolescents: Role of family, personality and comorbid psychopathology in school children in Eastern India.

Context: There is an increasing prevalence of internet addiction among adolescents during the COVID-19 pandemic, but very few Indian studies have assessed and taken into account various factors that can explain internet addiction in this vulnerable population. Aims: We examine the differences in family functioning, temperament, character and psychopathology in adolescents with and without internet addiction. Settings and Design: 1000 adolescents from urban middle-class families were included in this cross-sectional, two-randomized-group designed, comparative study. Clinical and control group population were selected from high schools. Those with severe internet addiction were compared to those with no addiction. Methods and Materials: Internet Addiction Test, Temperament and Character Inventory, Devereux Scale of Mental Disorders and McMaster Family Assessment Device were administered along with General Health and CRAFFT Questionnaire as screening tool. Statistical Analysis Used: Mann-Whitney U test was done along with Spearman's rank-difference coefficient of correlation. Result: Adolescents with internet addiction had high novelty seeking and low persistence. Internet addiction was also associated with conduct problems and depression. There was a significant positive association between depression and years of internet usage. Family of adolescents with internet addiction had increased difficulty in problem solving, communication, affective responsiveness, affective involvement and behavior control. Conclusion: Adolescents with internet addiction have temperament difficulties, more psychopathology and belong to dysfunctional families. Since the family plays a central role in an Indian context, family-focused strategies must also be included in the management of internet addiction.

Theory of mind deficit in women with breast cancer and depression: A comparative study.

Background: Studies have established that Theory of Mind (ToM) is impaired in patients with depression, but few studies have investigated the status of ToM in breast cancer patients who often suffer from depression. Our objective was to compare the ToM deficits in women with breast cancer with and without depression with a control group. Methods: The study was conducted at the Oncology department of a multi-speciality hospital in Kolkata. It was a cross sectional matched control study. We compared the ToM performance of women with breast cancer and depression (N=39), breast cancer without depression (N=63) and a healthy control group (N=34) using the widely used ToM task, Reading the Mind in the Eyes test (Eyes Test). Depression was diagnosed using Mini - International Neuropsychiatric Interview following International Classification of Diseases - 10th edition guidelines. Chi-square and one-way analysis of variances was done. Results: Both groups of patients had greater impairment in ToM compared to healthy controls (p<0.05). Among breast cancer patients, presence of depression predicted even greater impairment of ToM (p<0.05). Lower income, less education and not being in any occupation other than homemaking were associated with greater ToM impairment across all groups (p <0.05). Conclusion: Breast cancer patients suffering from depression may have an additional burden of impaired social cognition, which may reduce their ability to shore up social support when it is most required. This needs to be addressed urgently to ensure better quality of life.

COVID-19 prediction using AI analytics for South Korea.

The severe spread of the COVID-19 pandemic has created a situation of public health emergency and global awareness. In our research, we analyzed the demographical factors affecting the global pandemic spread along with the features that lead to death due to the infection. Modeling results stipulate that the mortality rate increase as the age increase and it is found that most of the death cases belong to the age group 60-80. Cluster-based analysis of age groups is also conducted to analyze the maximum targeted age-groups. An association between positive COVID-19 cases and deceased cases are also presented, with the impact on male and female death cases due to corona. Additionally, we have also presented an artificial intelligence-based statistical approach to predict the survival chances of corona infected people in South Korea with the analysis of the impact on the exploratory factors, including age-groups, gender, temporal evolution, etc. To analyze the coronavirus cases, we applied machine learning with hyperparameters tuning and deep learning models with an autoencoder-based approach for estimating the influence of the disparate features on the spread of the disease and predict the survival possibilities of the quarantined patients in isolation. The model calibrated in the study is based on positive corona infection cases and presents the analysis over different aspects that proven to be impactful to analyze the temporal trends in the current situation along with the exploration of deceased cases due to coronavirus. Analysis delineates key points in the outbreak spreading, indicating that the models driven by machine intelligence and deep learning can be effective in providing a quantitative view of the epidemical outbreak.

Towards Climate Resilient and Environmentally Sustainable Health Care Facilities.

The aim of building climate resilient and environmentally sustainable health care facilities is: (a) to enhance their capacity to protect and improve the health of their target communities in an unstable and changing climate; and (b) to empower them to optimize the use of resources and minimize the release of pollutants and waste into the environment. Such health care facilities contribute to high quality of care and accessibility of services and, by helping reduce facility costs, also ensure better affordability. They are an important component of universal health coverage. Action is needed in at least four areas which are fundamental requirements for providing safe and quality care: having adequate numbers of skilled human resources, with decent working conditions, empowered and informed to respond to these environmental challenges; sustainable and safe management of water, sanitation and health care waste; sustainable energy services; and appropriate infrastructure and technologies, including all the operations that allow for the efficient functioning of a health care facility. Importantly, this work contributes to promoting actions to ensure that health care facilities are constantly and increasingly strengthened and continue to be efficient and responsive to improve health and contribute to reducing inequities and vulnerability within their local settings. To this end, we propose a framework to respond to these challenges.