The role of ambient parameters on transmission rates of the COVID-19 outbreak: A machine learning model

Compliance with health protocols in the banking sector facing Covid-19

Background

The spread of the coronavirus has become one of the current challenges in the world. Implementing health protocols in the workplace along with informing people who face them, has become a vital issue.

Objective

The purpose of this study was to determine the level of compliance with health protocols and measure the level of awareness, attitude and performance of bank employees while facing Covid-19.

Materials and methods

The data collection tool included a checklist and two questionnaires (demographic information and the other on the awareness, attitude and performance of bank staff) regarding the coronavirus.

Results

A total of 199 bank employees from 25 bank branches participated in the study. The results showed that in 24% of the bank branches, the staff did not use face masks. And 100% of the studied bank branches lacked proper ventilation. The mean awareness scores of female employees (94.3) were significantly higher than those of male employees (87.7). Also, the performance of female employees (93.2) was significantly better than male employees (87.2).

Conclusion

The results showed that to achieve proper performance in controlling and reducing the covid-19 disease among bank employees and other workers, these items are noteworthy: (1) Providing and training the correct use of protective equipment including face masks. (2) Monitoring for strict implementation of health protocols. Therefore, it is necessary to keep training and information up-to-date due to the new phenomena of this disease.

Cognitive functions and anxiety among blue-collar workers in hospitals during COVID-19 pandemic

Background

The rapid spread of COVID-19 poses a major threat to public health worldwide. Hospital blue-collar workers, like other health care workers, may be under severe physical and psychological stress. This psychological distress is mainly described as symptoms of anxiety and depression, stress and cognitive function. This study aimed to investigate the effects of anxiety on cognitive function among laundry and sterilization center workers in 4 hospitals during COVID-19 pandemic.

Method

This study has a cross-sectional design and it was conducted among health service workers who were occupied in health facilities (laundry and sterilization center) in 4 hospitals. In the present study, two questionnaires and a test were used to collect the data included a general health questionnaire (GHQ-28), a health anxiety index questionnaire (HAI-18) and a cognitive function test. Descriptive statistics and Spearman correlation coefficient by SPSS version 19 were used.

Results

The results showed that the overall score of coronavirus anxiety in male and female workers was 38.72 ± 5.94 and 40.92 ± 4.11, respectively. The correlation between auditory attention and coronavirus anxiety is moderate and has a negative trend (P = 0.050, n = 50, and r = -0.315). Workers with higher anxiety expressed lower auditory attention. Also, correlation between visual attention and coronavirus anxiety was weak and negative (P = 0.032, n = 50, and r = -0.179).

Conclusion

This study revealed that cognitive and psychological aspects of mental health can be affected by COVID-19 exposure and its due anxiety in blue-collar workers in hospitals. These findings indicate that purposeful supportive interventions should be implemented to promote workers' health and cognitive function.

Utilization of Random Forest and Deep Learning Neural Network for Predicting Factors Affecting Perceived Usability of a COVID-19 Contact Tracing Mobile Application in Thailand "ThaiChana"

The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 contraction, different contact tracing applications have been utilized such as Thai Chana from Thailand. This study aimed to predict factors affecting the perceived usability of Thai Chana by integrating the Protection Motivation Theory and Technology Acceptance Theory considering the System Usability Scale, utilizing deep learning neural network and random forest classifier. A total of 800 respondents were collected through convenience sampling to measure different factors such as understanding COVID-19, perceived severity, perceived vulnerability, perceived ease of use, perceived usefulness, attitude towards using, intention to use, actual system use, and perceived usability. In total, 97.32% of the deep learning neural network showed that understanding COVID-19 presented the most significant factor affecting perceived usability. In addition, random forest classifier produced a 92% accuracy with a 0.00 standard deviation indicating that understanding COVID-19 and perceived vulnerability led to a very high perceived usability while perceived severity and perceived ease of use also led to a high perceived usability. The findings of this study could be considered by the government to promote the usage of contact tracing applications even in other countries. Finally, deep learning neural network and random forest classifier as machine learning algorithms may be utilized for predicting factors affecting human behavior in technology or system acceptance worldwide.

The university students’ viewpoints on e-learning system during COVID-19 pandemic: the case of Iran

The outbreak of COVID-19 closed educational institutions and universities. The aim of this study was to explain the strengths and weaknesses of the e-learning system in Iranian universities of medical sciences in the COVID-19 pandemic. This is a qualitative study that was conducted with students enrolled in Iranian medical universities. Data was collected through an open-ended electronic questionnaire based on the interview guide and was analyzed through content analysis.

122 students from 46 medical universities participated in this study. 122 questionnaires from 46 universities of medical sciences were completed. From a total of 54 codes extracted from the results, seven (strengths/positive experiences) and six (weaknesses/challenges) themes were extracted, each of which had several subsets. E-learning has both visible and hidden layers in terms of advantages and disadvantages. The e-learning system is an essential tool to continue education during the COVID-19 pandemic. Most students believe that e-learning was a great complement to prevent academic failure, but it cannot replicate the same efficiency of face-to-face training.