Mental Health Status, Coping Strategies During Covid-19 Pandemic Among Undergraduate Students of Healthcare Profession.

The present study aimed to assess the prevalence of psychological distress, associated lifestyle behaviors, and associated coping strategies among the students of healthcare profession. A total of 588 medical, dental, and nursing students studying in institutes of health sciences, KIIT University, Bhubaneswar, India participated in this cross-sectional online survey during September-October, 2020. A semi-structured questionnaire, DASS-21questionnaire, and Brief COPE were used to collect relevant information. The proportion of students experiencing symptoms of depression, anxiety, and stress was 26.2%, 27.7%, and 9.7%, respectively. Body mass index, presence of comorbidity, and soft drink consumption were significantly associated with psychological distress. Students experiencing psychological distress were applying emotion-focused coping behaviors (venting, acceptance, self-blame, substance use, religion) and avoidant coping behaviors (self-distraction, behavioral disengagement, denial). The prevalence of psychological distress among the students of health profession studying in KIIT University of Bhubaneswar during the period of Covid-19 pandemic is low and it can be further lowered by designing appropriate interventions incorporating healthy lifestyle behaviors and suitable coping strategies thereby ensuring sound mental health of these students.

Sleep quality and associated factors among undergraduate medical students during Covid-19 confinement.

Problem considered: Medical students are vulnerable to poor sleep quality which may lead to attention difficulties and poor academic performance. Good quality sleep is needed for optimal neurocognitive and psychomotor functions as well as physical and mental health. This study aimed to assess the prevalence of poor sleep quality among undergraduate medical students during home confinement at the time of Covid-19 pandemic and analyze the relationship between sleep quality and relevant socio-demographic and psychological variables. Methods: A cross-sectional study was conducted among 284 undergraduate medical students of a teaching hospital of Bhubaneswar from October-November 2020. Using a semi-structured questionnaire, relevant information was collected. Sleep quality of the students was assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire and mental health status of the students using Depression, Anxiety, and Stress Scale - 21 (DASS-21). Results: The prevalence of poor sleep quality among undergraduate medical students was 45%. Multivariate logistic regression revealed that students doing exercise for <3 days/week (AOR: 1.81, 95% CI: 1.01-3.23), spending ≥8 h screen time/day (AOR: 2.02, 95%: 1.12-3.66), having anxiety symptoms (AOR: 3.61, 95% CI: 1.72-7.57), and those who were not satisfied with own self (AOR: 2.69, 95% CI: 1.35-5.38) were more likely to report poor sleep quality. Conclusion: Poor sleep quality was prevalent among undergraduate medical students during their home confinement at the time of Covid-19 pandemic. Sleep educational programs, anxiety management, and lifestyle modifications can be recommended to improve sleep quality among medical students.

Impact of environmental temperature and relative humidity on spread of COVID-19 infection in India: a cross-sectional time-series analysis.

Purpose: Coronavirus disease 2019 (COVID-19) has become a serious public health problem worldwide. This study sought to examine the associations of daily average temperature (AT) and relative humidity (ARH) with the percent increase in COVID-19 cases. Methods: Daily confirmed cases and meteorological factors in 38 districts of India were collected between 1st April 2020 to 30th April 2020. Taking a 5-day time lag of average values of the variables and multiple days-samples, we ran multiple models and performed appropriate hypothesis tests to decide the single preferred model for each sample data. Suitable fixed effects (FE) and random effects (RE) models with cluster-robust standard errors were applied to quantify the district-specific associations of meteorological and other variables with COVID-19 cases. Results: All FE models revealed that every one-degree rise in AT led to a decrease in 3.909 points (on average) in percent increase in COVID-19 cases. All RE models showed that with one unit increase in the malaria annual parasite index, there was a significant increase in 10.835 points (on average) in percent increase in COVID-19 cases. In both FE and RE models, ARH was found to be negatively associated with a percent increase in COVID-19 cases, although in half of these models the association was statistically insignificant. Conclusion: Our results indicate that mean temperature, mean relative humidity, and malaria endemicity might have an essential role in the stability and transmissibility of the 2019 novel coronavirus.