Working conditions and anxiety levels of employees who have to work during the COVID-19 pandemic

Anxiety's correlation with sleepiness and memory among security officers during the COVID-19 pandemic

BACKGROUND

In the working population especially among older adults, anxiety problems have grown dramatically. This element has a significant impact on employee absenteeism and problems with physical and mental health. It was widely known that security personnel had several physical and mental difficulties during their various work hours. It is important to investigate the effects of anxiety on them.

OBJECTIVE

The present study aims to provide insights into the prevalence of anxiety disorders and explore the correlations between anxiety symptoms, sleep, and memory during the COVID-19 pandemic.

METHODS

To conduct a cross-sectional study, 42 older adult participants between the ages of sixty to seventy years were chosen and the procedure was explained.Data were gathered by giving instructions on how to complete the self-reported Generalized Anxiety Disorder Assessment -7 (GAD-7), the Epworth Sleepiness Scale, and the revised Everyday Memory Questionnaire.

RESULTS

A total of 36 out of 42 participants (85.71%) experienced moderate to severe anxiety. Anxiety and sleep had a correlation of 0.8, while anxiety and memory had a correlation of 0.87 with a positive EMQ-R relationship. Moreover, there was a statistically significant association between sleep and memory, with a positive correlation of 0.73.

CONCLUSION

The study concludes that, there is a substantial prevalence of anxiety accompanied by notable insomnia and memory problems in elderly security officers. Our findings indicate a clear relationship between sleep disturbances, memory issues, and most prevalent anxiety symptoms. These results emphasize the importance of incorporating mental health assessments and addressing an effective treatment for anxiety.

Prevalence and associated risk factors for mental health problems among young adults in Fiji Island during COVID-19: a cross-sectional study

Introduction

The COVID-19 pandemic has had a significant impact on mental health globally. To understand the impact of the pandemic on mental health in Fiji, this study aimed to investigate the prevalence of anxiety disorder and depression among the young adults.

Method

An online survey was conducted to assess the prevalence of anxiety disorder and depression among the general population in Suva, Fiji during the COVID-19 pandemic. A total of 1,119 Fiji adults participated in the study. The study was conducted between May 20 to June 30, 2022, using a snowball sampling via social media platforms. The Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) scales were used to measure anxiety and depression, respectively. The COVID-19 related stressors was evaluated using the adapted SARS stressors assessment. Univariate and multivariate logistic regression analysis was performed to determine the factors influencing mental health among respondents.

Results

The result shows that a significant portion of individuals experienced each of the stressors, with the highest prevalence seen for hearing information about the severity of COVID-19. The prevalence of anxiety and depression was found to be 45% and 49%, respectively. Being female, having pre-existing illness and COVID-19 stressors were a risk factor to develop anxiety and depression. On the other hand, employed individuals and having high BMI was a protective factor against developing depression during COVID-19 lockdown.

Conclusion

These findings highlight the importance of addressing the mental health needs of the Fijian population during the COVID-19 pandemic and beyond.

Factors Affecting Preventive Behaviors for Safety and Health at Work during the COVID-19 Pandemic among Thai Construction Workers

Occupational health and safety risks are of major concerns in construction industry. The COVID-19 outbreak provides an additional risk that could drastically affect the safety risks and health of construction workers. Understanding the factors that affect the health and safety of construction workers is significant in reducing risky behaviors and enhancing worker preventive behaviors. Via integrating the Protection Motivation Theory (PMT) and the extended Theory of Planned Behavior (TPB), this study investigates the factors that affect preventive behaviors among construction workers during the COVID-19 pandemic in Bangkok, Thailand. A total of 610 Thai construction workers participated in an online questionnaire survey, which consisted of nine factors with 43 questions. Structure equation modeling (SEM) was adopted to analyze the causal relationships among the latent variable. The SEM results indicated that organizational support and knowledge about COVID-19 had significant (p < 0.0001) direct influences on perceived vulnerability and perceived severity. In addition, perceived vulnerability and perceived severity had significant direct influences on perceived behavioral control. Perceived severity had significant (p < 0.0001) direct influence on attitude towards behavior. Moreover, perceived behavioral control and attitude towards behavior had significant (p < 0.0001) direct influence on intention to follow the preventive measure. Furthermore, the intention to follow the preventive measure had significant (p < 0.0001) direct influences on the COVID-19 preventive behavior. Of note, organizational support and knowledge about COVID-19 had significant (p < 0.0001) indirect influence on COVID-19 preventive behavior. The findings of this study may assist project managers/supervisors and authorities in the construction industry in understanding the challenge during COVID-19 and possible similar epidemics in the future. In addition, conducting effective strategies would improve construction industry safety and promote preventive behaviors among construction workers.

Effects of a mobile health intervention on activities of stress self-management for workers

BACKGROUND

Mobile health interventions are being widely tried because of their attractive advantages. However, there is not enough evidence for its effectiveness.

OBJECTIVE

This study aimed to evaluate the effects of mobile app-based stress management intervention (mSMI) on highly stressed workers.

METHODS

A sample of 82 white-collar workers with elevated symptoms of perceived stress (Perceived Stress Scale-10≥22) were randomly assigned to the intervention or control group. The mSMI consisted of three modules: self-management including a work diary, counseling based on cognitive behavioral therapy and interventions focused on music, meditation, relaxation and image healings. Self-report data were collected at the baseline and post-intervention. Study outcomes analyzed perceived stress, anxiety, depression, and work engagement. Data were assessed using analysis of covariance with covariates.

RESULTS

There was significantly reduced perceived stress from baseline to 6 weeks in mSMI (t = 5.788, p < 0.001) and control group (t = 3.184, p = 0.003). After adjusting for covariates, the between-group difference in the perceived stress was significantly different (F = 4.051, p = 0.048); however, the effect size was small. There was no significant intervention effect on anxiety, depression, and work engagement. The process evaluation indicated that most participants (85.3%) were satisfied with the intervention and their mental health benefited.

CONCLUSION

This study found that mobile health intervention facilitated perceived stress management for highly stressed workers. Further studies should address job-related outcomes and mental health symptoms in workers by applying the latest information technology and addressing the limitations of mobile interventions.

Returning to work and the impact of post COVID-19 condition: A systematic review

BACKGROUND: The COVID-19 pandemic is still ongoing, with rapidly increasing cases all over the world, and the emerging issue of post COVID-19 (or Long COVID-19) condition is impacting the occupational world. OBJECTIVE: The aim of this systematic review was to evaluate the impact of lasting COVID-19 symptoms or disability on the working population upon their return to employment. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statements we performed a systematic review in December 2021, screening three databases (PubMed, ISI Web of Knowledge, Scopus), for articles investigating return to work in patients that were previously hospitalized due to COVID-19. A hand-searched was then performed through the references of the included systematic review. A quality assessment was performed on the included studies. RESULTS: Out of the 263 articles found through the initial search, 11 studies were included in this systematic review. The selected studies were divided based on follow-up time, in two months follow-up, follow-up between two and six months, and six months follow-up. All the studies highlighted an important impact of post COVID-19 condition in returning to work after being hospitalized, with differences based on follow-up time, home Country and mean/median age of the sample considered. CONCLUSIONS: This review highlighted post COVID-19 condition as a rising problem in occupational medicine, with consequences on workers’ quality of life and productivity. The role of occupational physicians could be essential in applying limitations to work duties or hours and facilitating the return to employment in workers with a post COVID-19 condition.

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.