Assessment of Sleep Quality among Medical Students During the Covid- 19 Pandemic

Objective: To assess the sleep quality among medical students, comparing their sleep cycles during physical and online studies along with other factors associated with sleep patterns. Study Design: Cross-sectional Questionnaire based survey Place and Duration of Study: Department of Community Medicine, HITEC Institute of Medical Sciences Taxila from 1st January 2020 to 31st March 2020 Methodology: One hundred and forty seven students were surveyed in a time period of 1 month. The questionnaire included PSQI Pittsburgh Sleep Quality Index and other clinically validated questions. Students with known sleeping disorders were excluded from this survey. Result(s): There were 81 (55.1%) females and 65 (44.2%) males with mean age 20+/-1.4 years. Out of these 94(63.9%) were classified as "Poor Sleepers" and only 53 (36.1%) were "Good Sleepers". Poor sleep quality was associated with female gender (p<0.05), day-scholar residence status (p<0.054), excessive time required to sleep (p<0.00), excessive screen time usage (p<0.007), increased hours of study (p<0.089), experiencing trouble while driving, eating and socializing (p<0.002), lack of enthusiasm (p<0.000), unsatisfactory daily activities (p<0.000) and poor daytime alertness levels (p<0.360). 104 (70.7%) were aware of the effects of melatonin on sleep, only 51 (34.7%) admitted to have used coffee to stay awake at night. 98 (66.7%) subjects were pre-exam workers, 95 (64.6%) admitted not being able to wake up easily in the morning. Conclusion(s): The students and hostelites that used less screen time slept better. Excessive daytime tiredness was also a result of poor sleeping habits. Students who studied for longer periods of time and had difficulty waking up in the morning slept poorly. Poor sleepers also find it difficult to interact and are often unambitious about performing their daily menial tasks, as well as displeased with their daily activities. As a matter of fact, we deduce that sleep quality has unanticipated consequences for medical students' social and mental health.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Collaborative Federated Learning for Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge

Despite significant improvements over the last few years, cloud-based healthcare applications continue to suffer from poor adoption due to their limitations in meeting stringent security, privacy, and quality of service requirements (such as low latency). The edge computing trend, along with techniques for distributed machine learning such as federated learning, has gained popularity as a viable solution in such settings. In this paper, we leverage the capabilities of edge computing in medicine by evaluating the potential of intelligent processing of clinical data at the edge. We utilized the emerging concept of clustered federated learning (CFL) for an automatic COVID-19 diagnosis. We evaluate the performance of the proposed framework under different experimental setups on two benchmark datasets. Promising results are obtained on both datasets resulting in comparable results against the central baseline where the specialized models (i.e., each on a specific image modality) are trained with central data, and improvements of 16% and 11% in overall F1-Scores have been achieved over the trained model trained (using multi-modal COVID-19 data) in the CFL setup on X-ray and Ultrasound datasets, respectively. We also discussed the associated challenges, technologies, and techniques available for deploying ML at the edge in such privacy and delay-sensitive applications.

Pulmonary Fibrosis on High resolution Computed Tomography (HRCT) in Post Covid Patients

Objective: To detect people who may develop lung fibrosis early, allowing for the early administration of anti-fibrotic medications, which will not only benefit the infected patients with timely effective disease management, but will also ensure appropriate use of medical resources for this purpose. Study Design: Descriptive case series study Place and Duration of Study: This study was conducted at the Department of Radiology, Sharif Medical City Hospital, Lahore for one year from September 2020 to August 2021. Materials and Methods: This study was conducted after the approval of the ethical review board. Cases of Covid-19 were included as per inclusion criteria using non-probability, consecutive sampling. Results: Among the patients included in the study, 171 (45.6%) were male and 204 (54.4%) were females. Majority of the patients were of age group more than 50 years. The frequency of pulmonary fibrosis in our study population was 27.5% (103) with degree of pulmonary involvement: mild in 21 (20%), moderate in 39 patients (37.9%) and severe involvement in 43 of 103 patients (41.7%). Data was stratified for various effect modifiers including age (p=0.19), gender (p=0.01), socioeconomic status (p=0.002), BMI (p=0.11), history of chronic illness (p<0.00001), degree of pulmonary involvement (p=0.01) and history of steroid use (p<0.00001). Conclusion: The aim of this study was to detect people who may develop lung fibrosis early, allowing for the early administration of anti-fibrotic medications. Along with determination of disease severity using HRCT severity scoring, which will not only benefit the infected patients with timely effective disease management, but will also ensure appropriate use of medical resources for this purpose. Side by side our study will guide the medical and government authorities to take suitable steps for the local population depending upon the lethality of disease in the second wave. This study will also able to identify the population at risk of developing fibrosis. © 2022 Medical Forum Monthly. All rights reserved.

Adoption of mobile food ordering apps for O2O food delivery services during the COVID-19 outbreak

Purpose The purpose of this paper is to develop a model to examine how different technological and cognitive cues related to mobile food ordering applications (MFOAs) impact diners' intentions to use MFOAs continuously. The moderating role of national household demographics was also assessed in the online-to-offline (O2O) food delivery services (FDS) context. Design/methodology/approach Drawing insights from the uses and gratification (U&G) theory, an online sample survey of 968 valid respondents who had ordered or purchased food through delivery apps during the COVID-19 outbreak in China was used for the analysis. The proposed model was empirically tested using structural equation modeling. Findings The results revealed that cues in MFOAs (i.e. ease of use, convenience, price saving orientation, the listing of various food choices, exploring restaurant patterns, and compatibility) directly influenced diners' e-satisfaction and that intention to use continuously is triggered by e-satisfaction during the COVID-19 crisis. Moreover, this study found that collectivist household diners emphasized ease of use, convenience, and compatibility. Comparatively, individualistic household diners placed more importance upon price saving orientation and listing of various food choices during the pandemic. Originality/value The authors offer a new insight into customers' dining choices by extending the scope of O2O services in the food industry. The findings contribute to understanding diners' purchase decision-making processes regarding MFOAs' O2O-FDS during the COVID-19 crisis. The multi-group comparison via national household demographics also provides a new perspective regarding different dining preferences toward O2O-FDS.

Applying the Islamic marketing ethics among small scale business Muslimpreneurs during Covid19 MCO: A comparison among types of social network system (SNS)

The outbreak of COVID-19 forced the Malaysian government to implement the Movement Control Order (MCO) in phases starting March 18, 2020. The implementation of the MCO has affected business continuity, especially among Muslimpreneurs involved in small-scale business. Restricting business hours and business movements to limited time periods and movements, entrepreneurs have turned to online and digital business methods specifically for marketing, supplying, and delivering goods. As a Muslim, Muslimpreneurs should not compromise with any unethical element in their entrepreneurial activities. Thus, business marketing and promotional activities conducted digitally and online should be in line with the Islamic law as well as the basic principles of ethics in Islamic business. This study used a content analysis approach to examine the implementation of Islamic marketing ethics in the sharing of business advertisements through Social Network System which is popular among Muslimpreneurs in Malaysia. For that purpose, a total of 45 samples of advertisements have been randomly studied from WhatsApp, Instagram and Facebook applications. This study found that over 90% of Muslimpreneurs have adhered to the basic principles of Islamic marketing ethics in their advertising material. At the same time, Muslimpreneurs are also found to prefer sharing quality ads and more on Facebook compared to WhatsApp and Telegram. © 2021 Author(s).

Forecasting Chinese Yuan/USD Via Combination Techniques During COVID-19

This study aims to forecast the exchange rate of the Chinese Yuan against the US Dollar by a combination of different models as proposed by Poon and Granger (2003) during the Covid-19 pandemic. For this purpose, we include three uni-variate time series models, i.e., ARIMA, Naive, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Chinese Yuan against the US dollar by two combination criteria i.e. var-cor and equal weightage. After finding out the individual accuracy, the models are then assessed through equal weightage and var-cor methods. Our results suggest that Naive outperforms all individual & combination of time series models. Similarly, the combination of NARDL and Naive model again outperformed all of the individual as well as combined models except the Naive model, with the lowest MAPE value of 0764. The results suggesting that the Chinese Yuan exchange rate against the US Dollar is dependent upon the recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting which commensurate with the literature.

COVID-19 Induced anxiety among health care professionals

Objective: To evaluate the stress level among doctors and nurses during COVID-19 crises. Study design: Descriptive correlational study Place and duration of study: Department of Medicine &Critical Care, Services Hospital Lahore and Bahria International Hospital, Lahore from 1st May 2020 to 31st July 2020 Methodology: Descriptive correlational study design to evaluate the stress level among doctors and nurses. A couple of other factors were also identified like lack of personal protective equipment's (PPEs) and family pressure to quite job along with COVID-19 stress. Two groups were substituted one with exposure of COVID-19 and other without its exposure. The internal review board and ethical committee of Bahria International Hospital, Lahore, approved the study. Questionnaire was collected after proper informed consent from health professionals working at COVID management units at Services Hospital Lahore and Bahria International Hospital Lahore. Chi-Square test and Odd ratios were calculated among the stated groups of doctors and nurses. Results: Statistical analysis among the groups of doctors and nurses exposed and not exposed shows significant higher levels of anxiety in doctors and nurses who were involved in management of COVID-19 patients directly as compared to those who were not. Similarly, the level of risks increased almost double in the exposed healthcare workers. Availability of personal protective equipment and pressure from the families to quit the job also plays significant role in elevating of anxiety levels. Conclusion: Study concludes that anxiety increases in the health care professionals due to lack of robust systems to cope up with the COVID-19 pandemic. Factors like stress from family, lack of proper protective equipment leads to fear of being infected and taking the infection to their loved ones. It is responsibility of management of health care set ups to ensure the availability of PPEs and making a robust system of infection control to help combat the pandemic. © 2020 Lahore Medical And Dental College. All rights reserved.