Workplace Stress and Productivity: A Cross-Sectional Study

Levels of work stress among information technology professionals during COVID-19 pandemic in an Indian metropolis

Introduction

Amid the ongoing Non-Communicable Disease and COVID-19 pandemic, understanding prevalence and characteristics associated with work stress is vital from a health and economic perspective, more so among information technology (IT) professionals.

Objective

To estimate the prevalence and factors associated with work stress among IT professionals during the coronavirus disease 2019 (COVID-19) pandemic in Bengaluru, India.

Materials and Methods

A cross-sectional study was undertaken on a convenient sample of 356 IT professionals in Bengaluru, India, between September 2020 and March 2021 to assess work stress. The weblink to TAWS-16 (Tool to Assess and classify Work Stress) was provided for IT employees to self-report their experience of work-related stressors and coping abilities in the past 6 months. The prevalence and specific prevalence of work stress were calculated. Multi-variate logistic regression was conducted to identify factors associated with work stress. Ethical clearance was obtained from the Institutional Ethics committee, National Institute of Mental Health and Neurosciences, Bengaluru. Informed consent was obtained from study subjects.

Results and Conclusion

The prevalence of work stress among IT professionals was 17.7% during the COVID19 pandemic, with higher rates among employees aged 31 years and above, among female employees, and among employees with 4-7 years of work experience. More than 80% of the professionals experienced deadline pressures, long working hours, regular multi-tasking, and difficulty in maintaining work-life balance. Based on the results, it is recommended to integrate work-stress assessment in periodical medical examination of IT employees from a health promotion and productivity improvement perspective.

Machine learning-based classification analysis of knowledge worker mental stress

The aim of this study is to analyze the performance of classifying stress and non-stress by measuring biosignal data using a wearable watch without interfering with work activities at work. An experiment is designed where participants wear a Galaxy Watch3 to measure HR and photoplethysmography data while performing stress-inducing and relaxation tasks. The classification model was constructed using k-NN, SVM, DT, LR, RF, and MLP classifiers. The performance of each classifier was evaluated using LOSO-CV as a verification method. When the top 9 features, including the average and minimum value of HR, average of NNI, SDNN, vLF, HF, LF, LF/HF ratio, and total power, were used in the classification model, it showed the best performance with an accuracy of 0.817 and an F1 score of 0.801. This study also finds that it is necessary to measure physiological data for more than 2 or 3 min to accurately distinguish stress states.

Identification and assessment of stress and associated stressors among veterinary students in India using a cross-sectional questionnaire survey

Background

Veterinary education, is a rigorous professional training program, which exposes students to significant academic and non-academic pressures. The identification of stressors and stress levels among veterinary students mighty help the designing and implementation of coping strategies to protect the students' mental health.

Methods

A 44-item based cross-sectional questionnaire survey was prepared and disseminated among veterinary students in India to identify the stressors responsible, measure the amount of stress, and relate stress to characteristics like gender, degree year, and family income. A total of n = 611 veterinary students across 14 states including 27 colleges/universities participated in the study. The collected data was evaluated for sampling adequacy, construct validity, and reliability using a set of statistical tests.

Results

The analysis revealed high sampling adequacy with a KMO value of 0.957 and a highly significant anti-image correlation (p < 0.001). The principal component analysis generated six factors or subscales which effectively explained 51.98% of the variance in the data, depicting high construct validity. The Cronbach's alpha value of 0.957 revealed high internal consistency for the questionnaire. Analysis revealed more than 94% of pupils under stress, with levels ranging from moderate to severe. Academic-related stressor (95.58%) was the leading cause of overall stress in the present study followed by inter- and intrapersonal and career related-stressors (93.12%) and exams and evaluation-related stressor (90.99%). In comparison to male students, female students reported significantly higher levels of overall stress, academic stress, and intrapersonal and interpersonal stress (p < 0.001) using Chi-square. The students from lower-income families experienced significantly higher overall stress as well as stress due to family responsibilities (p < 0.001). The first-year undergraduate students reported significantly higher (p < 0.001) stress due to family responsibilities-related stressors whereas second-year students due to social activities-related stressors. The hierarchal regression model predicted that gender, family income, academic-related stressors, inter- and intrapersonal and career-related stressors, and social activities-related stressors can be employed to evaluate overall stress among students, as they ensured the maximum variance in the data (p < 0.001).

Conclusions

To the best of our knowledge, this is the first Indian study to identify stressors, quantify associated stress and predict major attributes to be targeted in future studies for veterinary students.

Effects of Sedentary Behavior Interventions on Mental Well-Being and Work Performance While Working from Home during the COVID-19 Pandemic: A Pilot Randomized Controlled Trial

Sedentary behavior negatively impacts mental health, which can decrease employee productivity. Employee mental well-being and work performance may improve with sedentary reduction interventions, especially strategies that include environmental workplace modifications and behavior-changing strategies. However, such interventions have not been examined among employees working remotely during the COVID-19 pandemic. As part of the Stand Up Kansas program, 95 sedentary university employees working from home were randomized into one of four intervention arms: height-adjustable desk provision (Desk Only), online sedentary behavior modification program (Program Only), Desk + Program, or Control. The outcomes were measured at a baseline (November 2020) and following the 12-week intervention (February 2021). Employees reported mood (positive and negative affect), stress, fatigue (duration, interference with activities and severity) and work performance (irritability, focus, work satisfaction, non-work satisfaction and productivity) were measured using established self-report instruments. The effect sizes, by comparing the Control arm to the Desk + Program arm, revealed large improvements in mood (positive affect, d = 1.106). Moderate improvements were also seen in fatigue (duration, d = −0.533, and interference with activities, d = −0.648) and several aspects of work performance (focus, d = 0.702, work satisfaction, d = 0.751, and productivity, d = 0.572). Moderate effect sizes were also seen for positive affect (d = 0.566) and fatigue severity (d = 0.577) among the Program Only arm, whereas no noteworthy effect sizes were observed among the Desk Only arm. Combining an online sedentary behavior modification program with height-adjustable desk provisions appeared to positively affect mental well-being and work performance among remote employees.