Keywords

COVID-19, IT Employees, Mental Health, Worker Well-being, Organizational Performance.

Introduction

Mental fitness consists of our emotional, psychological, and social well-being. Mental health wellness affects how we think, feel, and act. It additionally facilitates deciding how we take care of stress, relate to others, and make choices. Mental fitness is critical at each level of life, from early life and childhood thru adulthood. As the impact of the COVID-19 coronavirus is felt around the world and governments implement “Social distancing” and quarantine measures to help stem the spread of the disease, concerns about the long-term effects of the virus - on both physical and mental wellbeing - are being raised. Mental health is an inner useful resource that allows us to think, feel, connect, and function; it's far a lively manner that allows us to construct resilience, grow, and flourish (Avey et al., 2010; Carolan et al., 2017).

According to Census, India has a 474 million working population. Furthermore, the country's Sample Registration System's 2018 report shows that country's demographic dividend continues to grow. The share of the running-age populace is anticipated to grow from 61% in 2011 to 65% in 2036, including 12 million human beings in the running populace every year. Mental disorders are impacting millions of working populations in India. Although there are no population-based prevalence studies for working populations, there are estimates of mental disorders in India, implying the burden of mental disorders in the working population.

Literature Review

Bhardwaj & Srivastava (2008) have confirmed that the workers’ failure to adapt to the psychosocial work environment results in deterioration in mental health. Lack of job satisfaction, insecurity, poor human relationship, and emotional tension are some of the psychosocial factors, which adversely affect both the physical and mental health of the workers.

Jain (2012) has studied the depression and psychological well-being of doctors in the context of their gender, area, and types of practice. The study shows that the doctor in the different locations have a higher change in depression and further study shows that the sociability of the doctor in the difference has a high rate of psychological wellbeing score in both gender and marital status.

Shivakumar & Rangaraj (2020) have documented the levels of anxiety, stress, and depression that prevail among the employees who work from home, as a result of Covid-19-related lockdown. The study has clearly established the association between mental health factors and the new normal of Work from Home.

Prasad et al. (2020) have proposed that Communication, Organization climate, Organization Policies, Job Satisfaction, and psychological factors affect the psychological well-being of employees in the information technology sector during the survey period of the Covid-19 pandemic.

Phadnis et al. (2021) have confirmed that the radical change in the work environment in which there is an absence of all forms of physical interactions between colleagues led to a sense of isolation and disconnectedness from the real world for many participants.

Ranjitha (2021) confirm that the quality of work-life of the employees is improved by the time to plan a better work pattern inclusive of fitness routines, healthy diet schedules, and quality family time to switch between work and family routines. The study concluded that the pandemic has provided a chance for compatibility between the efforts of the organization and the efforts of the working professionals to synchronize with each other for better productivity.

Azhagan & Kumar (2022) have briefed that mental well-being in the IT sector has played a vital part takes place in the performance of an employee. The main motive of the research study is to investigate the IT employee’s mental well-being in the covid-19 pandemic and that the organizational productivity, performance, and working capability of the individual are influenced by the psychological, physical, and social factors in the personal and workplace environment Figures 1 & 2.

Figure 1 Research Model

Figure 2 Scree Plot

Objectives of the Study

1. To identify the factor that impacts the mental wellness of the IT employees.

2. To analyze the relationship of mental wellness of employees during the covid situation.

3. To identify the COVID pandemic’s impact on employee wellbeing by focusing on both personal and workplace environments.

4. To assess the effectiveness of the employee's psychological well-being and work effectiveness during the covid-19 pandemic.

Methodology

Data Collection

This research study is carried the based on primary data and secondary data. The primary data is gathered from the public by a 5-point Likert scale ranging from 1-strongly agree to 5-strongly disagree also dichotomous scales were used. Secondary data are selectively gathered from journals, articles, and websites. This primary data is arranged for the questionnaire method the subject of the study (Kazmi et al., 2020).

Sampling Method

A convenient sampling method is implemented to collect the primary data. The respondents for the motive of this observation are decided on systematically. Convenience sampling is a sort of Non-probability sampling, which doesn`t comprise a random choice of respondents (Kundi et al., 2020).

Correlation

Correlation refers to the Statistical relationship between two entities. This means the two variables moved either up or down in the same direction. The correlation coefficient is calculated with the aid of using first figuring out the covariance of the variables and dividing that quantity by the product of those variables’ standard deviations (Azhagan & Kumar, 2022).

Regression

Regression is a statistical approach utilized in finance, investing, and different disciplines that try to decide the strength and individual of the connection among one structured variable (normally denoted through Y) and a sequence of different variables (called independent variables).

Factor Analysis

Factor analysis is a way this is used to reduce a big variety of variables into fewer numbers factors. This approach extracts the most common variance from all variables and places them right into a common rating. As an index of all variables, we will use this rating for a similar evaluation. Factor evaluation is a technique of record reduction. It does this through searching for underlying unobservable (latent) variables that might be meditated withinside the discovered variables (manifest variables).

The factor analysis model is: X = μ + L F + e

Results and Discussion

Correlation

Hypothesis 1: Education Qualification and Anxiety.

H0: There is no significant relationship between education qualification and anxiety.

H1: There is a significant relationship between education qualification and anxiety.

Interpretation

From table 1, it is inferred that P-value is greater than 0. i.e., P<0.05 (0.042<0.05) is lesser than the critical value 0.05, hence H₀ is rejected and H₁ is accepted. Therefore, there is a positive relationship exists between education qualification and anxiety.

Regression

Hypothesis 1: Martial Status * Depression

H0: There is no relationship exist among Marital Status and Depression.

H1: There is a relationship exist among Marital Status and Depression.

Interpretation

From Tables 2 & 3 it is inferred that P-value is greater than 0. i.e., P<0.05 (0.042<0.05) is lesser than the critical value 0.05, hence H₀ is rejected and H₁ is accepted. Therefore, there is a positive relationship exist among Martial Status and Depression.

Factor Analysis

Factor analysis of all the variables from the questionnaire.

Interpretation

From Table 4 it is inferred that the Kaiser-Meyer-Olkin test value is 0.610 which is more than 0.5 and can be considered acceptable and valid to conduct data reduction techniques. Bartlett’s test of sphericity significant to a level of significance is <0.001 which shows that there is a high level of correlation between variables, which makes it adequate to apply factor analysis.

From Table 5 it is inferred that the extraction value is ranging from 0.688 to 0.754 which shows that the minimum variance share of items after extraction is 68.8% and the maximum variance share of the item is 75.4%.

From Table 6 it is inferred that the total variance contributed by the first component is 33.850%, by the second component is 18.903%, the third component is 12.753%, and the fourth component is 10.342%. The Eigenvalue for the first factor is 4.062, the second factor is 2.268, the third factor is 1.530, and the fourth factor is 1.241.

From Table 7 it is inferred that Factor 1 has a very high significant loading on the variable depression (0.816), Factor 2 has a very high significant loading on the variable anxiety (0.790), Factor 3 has a very high significant loading on the variable lack of guidance (0.775), Factor 4 has very high significant loading on the variable Team pressure (0.873) and Factor 5 has very high significant loading on the variable Isolation (0.859).

Findings from the Study

Correlation

There is a positive relationship exist among education qualification and anxiety.

Regression

There is a positive relationship exist among Martial Status and Depression.

Factor Analysis

The variables which have high loading factors are Depression (0.816), Anxiety (0.790), and Lack of guidance (0.775).

The variables which have average loading factors are Team pressure (0.873), and Isolation (0.859).

Implications and Recommendations

Educating your employees on the way to exercise desirable stress management is a powerful manner to prioritize well-being with inside the workplace.

Working for long stretches without breaks ends in stress and exhaustion, while breaks will assist to refresh the mind, refill your employees` mental assets, and can also inspire their creativity.

Adopting an employee assistance program evolved via way of means of educational experts should assist equip supervisors with assets to apprehend and manage troubles associated with mental wellbeing?

Unexpected situations and family circumstances lead to the financial crisis; thus, employees have a backup plan for their financial stability and utilize the financial institutions' schemes and other saving plans wisely.

Conclusion

This research study is to investigate the IT employee’s mental well-being during the Covid-19 pandemic and that the organizational productivity, performance, and working capability of the individual are influenced by the psychological, physical, and social factors in the personal and workplace environment. This study also elevated that the employees who work from home during the covid-19 pandemic faced mental illness by the factors like anxiety, depression, stress, burnout, lay-off, burden, exhaustion, sleep disturbance, lack of guidance, and team pressure, isolation, and discrimination. The study suggests that to maintain positive mental health wellness employees should get professional help if needed, connect with others, stay positive, get physically active, help others, get enough sleep, and develop skills.

References

Avey, J.B., Luthans, F., Smith, R.M., & Palmer, N.F. (2010). Impact of positive psychological capital on employee well-being over time. Journal of Occupational Health Psychology, 15(1), 17.

Indexed at, Google Scholar, Cross ref

Azhagan, T.C., & Kumar, S.S. (2022). A conceptual study on the it employee's mental wellbeing. International Journal of All Research Education and Scientific Methods, 10(5), 429.

Bhardwaj, A., & Srivastava, A. (2008). Occupational health and psychological well-being of industrial employees. Industrial Psychiatry Journal, 17(1), 28.

Indexed at, Google Scholar

Carolan, S., Harris, P.R., & Cavanagh, K. (2017). Improving employee well-being and effectiveness: Systematic review and meta-analysis of web-based psychological interventions delivered in the workplace. Journal of Medical Internet Research, 19(7), e7583.

Indexed at, Google Scholar, Cross ref

Jain, P.K. (2012). A study of depression and psychological well being of doctors in context of their gender area and types of practice.

Google Scholar

Kazmi, S.S.H., Hasan, D.K., Talib, S., & Saxena, S. (2020). COVID-19 and lockdown: A study on the impact on mental health. Available at SSRN 3577515.

Indexed at, Google Scholar, Cross ref

Kundi, Y.M., Aboramadan, M., Elhamalawi, E.M., & Shahid, S. (2020). Employee psychological well-being and job performance: Exploring mediating and moderating mechanisms. International Journal of Organizational Analysis.

Indexed at, Google Scholar, Cross ref

Phadnis, S., Sengupta, S., & Chakraborty, A. (2021). Work from home, mental health and employee needs: A pilot study in selected information technology organizations in India. Asia Pacific Journal of Health Management, 16(3), 103-110.

Indexed at, Google Scholar, Cross ref

Prasad, D.K., Mangipudi, D.M.R., Vaidya, D.R., & Muralidhar, B. (2020). Organizational climate, opportunities, challenges and psychological wellbeing of the remote working employees during COVID-19 pandemic: A general linear model approach with reference to information technology industry in hyderabad. International Journal of Advanced Research in Engineering and Technology (IJARET), 11(4).

Indexed at, Google Scholar

Ranjitha, R. (2021). Measuring the Mental Wellbeing of E-Workers and Its Impact on E-Work Life Balance during COVID-19 Pandemic. Psychology and Education Journal, 58(4), 718-728.

Google Scholar

Shivakumar, B.L., & Rangaraj, T. (2020). Mental wellbeing status of online and work from home women employees with special reference to Coimbatore, Tamilnadu. Public Health, 22, 23rd.

Google Scholar

Received: 01-Aug-2022, Manuscript No. BSJ-22-12485; Editor assigned: 05-Aug-2022, PreQC No. BSJ-22-12485(PQ); Reviewed: 19- Aug-2022, QC No. BSJ-22-12485; Revised: 22-Aug-2022, Manuscript No. BSJ-22-12485(R); Published: 28-Aug-2022