Introduction

People may feel stress if there is a discrepancy between the work demand from organizations and the support organizations provided to complete that work. Because of recent COVID-19 Pandemic, organizations all over the world realized the unknown challenge for unknown period. Many businesses had to close their operations for undetermined time, people movement were restricted, maintaining social-physical distance becomes norms, and working from home becomes culture. This new culture has created different types frustration for all ages, from school going children to office going adult, from employed to unemployed, from junior level positions to upper level positions and from male to female. According to American Psychological Association (APA, 2020), approximately 8 in 10 adults (78%) acknowledged that the coronavirus pandemic is a major source of stress in their life and, 2 in 3 adults (67%) said they have experienced increased stress over the course of the pandemic. The most distress of life in this situation is the fear of death of own self and of family members and friends from corona virus, in one hand and on the other hand, new employment culture has created new types of stress among working people. Increasing high unemployment rate with unstable price level also have made people financially poorer. Though with the time people have started to cope with New Normal situation, still in trauma for their bitter experience with their work and life imbalance. Though, people are staying more time at home, and suppose to give more time to family, but on-line office culture is taking away their personal time. Because of technology, office time has extended to personal time, has created new behavior, new expectations from organizations, blundered between work-life space. According to Jernigan (2020), more than 80% of executives experience modest to severe stress in their roles due to lack of time to finish their work, less sleep, and being constantly tired at work. Out of them 55% of those reported stress, at least one experience with burnout during their career. This research mainly tried to explore the work-life stress level among entry to mid-level managers considering work-demand expected from managers and work support provided by the organizations.


Literature Review

The word stress is not new phenomena to anyone, rather people have dealt with stress since the beginning of civilization. It is a condition of physical or mental strain Hanes (2002). According to Robbins and Sanghi (2006), stress is a dynamic situation in which people encountered with the opportunity, limitations, or demand related to what people desire and for which the outcome is important but uncertain. Homo Sapiens is not the only species that suffer from stress, other non-human species like non-human primates like chimpanzees, savanna baboons, and tamarin monkeys also suffer from stress (Sapolsky, 2005). Researchers focused on stress as the unit of analysis from individuals, to families, to communities. The individual stress theory came fundamentally from psychobiology, sociology, psychiatry, and anthropology (Cannon, 1929; Lindemann, 1944; Caplan, 1974; Holmes and Rahe, 1967; and Hoff, 1989). However, the concept of stress was first introduced in the Physics and biological science. At that time, researchers were more concern about physical stress, as the word has been derived from the ‘stringere’, a Latin word, which means the experience of pain, and physical hardship. According to Selye Hans (1956), stress is the non-specific response of the body for any external event or internal drive. Stress is also considered as the dynamic condition where individual’s opportunity, constraint or demand related to his/her desire and outcome is perceived as important but uncertain (Stephen, 1999; Robbins and Sanghi, 2006).

Hobfoll (1989) assumes that stress occurs because of three reasons: when people loss their assets, when assets are in danger, or when people invest their assets with unequal benefit. Here, four types of resources are identified: physical resources (such as home, clothing, etc.), condition resources (such as employment, personal relationships), personal resources (such as skills or self-efficacy), and energy resources (which need to facilitate other resources, such as money, credit, or knowledge). Modern theories of stress, give answer of three crucial questions in understanding (Cox & Griffiths, 2010) about stress: why, when and what happens after stress? And how to overcome? Among these theories, four prominent work-related stress theories are: Job Demand-Control (Support) Theory; Effort-Reward Imbalance Model (ERI model), Person-Environment Fit theory (P-E Fit theory); and Transactional Model. All these theories have clarified the causes and mechanisms that underlie work-related stress.

Work life stress may be result of work overload, unsupportive colleagues, unhealthy competition and role conflict in workplace (O'driscoll, et al., 1992; Safaria et al. 2011). According to Frese and Zapf (1988), work life stress refers to the process through employee’s perception and respond to any adverse or challenging job situation. It is a condition of perceived tension between demands and support in work environment (Doble, N. and Supriya, M.V, 2011). Work-life stress also can be result of interpersonal relationship with supervisor or the support get from supervisor. Relationship among the co-workers and with supervisor is important in order to sustain the harmonious environment (Razak et al., 2014). Managers may also feel work overload when work demands exceed work support (Elloy and Smith, 2003), and ultimately it may reduce the productivity as a whole.

National Institute for Occupational Safety and Health (NIOSH, 1999)- the US federal research organization on Occupational Safety and Health defined job stress as the harmful emotional and physical responses which do not match the capabilities, resources, or needs of the worker and finally results poor health and even injury. On the other hand, in terms of physiology, Sapolsky (2004) defined stress as the state of homeostasis imbalance where homeostasis stands for various physiological endpoints—body temperature, blood pressure, heart rate, and so on—are at their optimal levels. Sapolsky (2004) also defined stressor as any physical or psychological factor that agitate this homeostasis inside human. Whether stress only exists in post industrialized human or it has prehistoric legacy is an area of academic debate. But Webb et. al (2010) showed the historical legacy of stress in human. In their study, fossilized human hair was tested for cortisol level which is a biomarker of stress and found 1.5 times more cortisol level which indicates human were exposed to stress historically. According to Webmd (2021), cortisol is a nature’s built-in alarm system which is human body’s main stress hormone and works with certain parts of human brain to control mood, motivation, and fear. It’s best known for helping fuel human body’s “fight-or-flight” instinct in a crisis. Barsade et al. (1997) research revealed that about 29% workers feel quite a bit or extremely stressed at work. According to NIOSH, acute and chronic post-traumatic anxiety, reaction to stress, panic disorders, and other neurotic disorders are associated with anxiety, stress and neurotic disorders. These are more severe than the average injury or illness. Down the line the affected workers experience a much greater work loss than those with all nonfatal injuries or illnesses—25 days away from work compared with 6 in 2001.

According to National Institute for Occupational Safety and Health (1999), the primary causes of job stress are worker characteristics and working conditions. Here worker characteristics may include biological factors such as age and gender. Age is a widely used biological indicator which can be a good predictor of cognitive maturity. Cognitive abilities can be divided into several specific cognitive domains including attention, memory, executive cognitive function, language, and visuospatial abilities which typically experience measurable declines with age (Murman, 2015).

According to Fifth Bangladesh Population and Housing Census 2011, where population was grouped into different age group such as 0-4, 5-9, 10-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65+ and each age group has 10.45%, 12.60%, 11.55%, 8.90%, 9.25%, 9.35%, 7.25%, 6.65%, 5.75%, 4.45%, 3.85%, 2.45%, 2.75%, 4.75% percentile composition respectively. This also reflects that 43.5% of the population belongs to within 19 age whereas 39.75% of the population belong to the age band 25-59 which is suitable age range for pursuing managerial career (Alam et al., 2015). Here Bangladesh is going through a flipped age distribution in comparison to developed world where demography is facing aging problem. But very small percent of the population is engaged in managerial career in Bangladesh. Country specific stress data is not available more specifically for the managerial positions in Bangladesh. Whereas the workplace stress picture is grim where systematic study results are available such as USA. The Bureau of Labor Statistics (BLS) (2003) of USA -assessed anxiety, stress, and neurotic disorder cases involving days abscent from work in 2001 and in the majority of the cases, younger age groups have been found accounted for the majority of cases.

Workers aged <25 accounted for 7.6% of cases, workers aged 25–34 accounted for 25.5% of cases, workers aged 35–44 accounted for 28.2% of cases, workers aged 45–54 accounted for 24.6% of cases, and workers aged >54 accounted for 14.1% of cases. Literature is also supporting the reality such as Rauschenbach et. al. (2012) in their study discussed the notion that older workers acquire better jobs the longer they proceed in their career which inevitably leads to better jobs entail fewer work-related stressors.

Academic investigations and debates are also focusing on gender differences in stress and coping behavior. In this 21st century, more participation of women in all different types of economic activities intensifying the curiosity of gender difference in stress. Although the research didn’t find any statistical significance of stress among gender in ancient times (Webb et. al, 2010). But in modern days studies are showing the differences. Women scored significantly higher than the men on chronic stress (Matud, 2004). Female professionals experience unique stressors (Nelson & Quick, 1985). Jick & Mitz’s (1986) bibliographical study showed that nineteen studies indicate that women tend to report higher rates of psychological distress compare to men. Kristina and Stephen (2005) also echoed in same way. Different factors found responsible for work-life stress among female managers, such as multiple roles, discrimination, stereotypes, increased workload, work-family responsibilities, lack of career progress, etc. (Kristina & Stephen, 2005; Maryyam et al., 2010; and Iwasaki et al., 2004). As the economy of Bangladesh is experiencing a take-off stage and increased participation of women in diverse economic activities so women are exposed to typical work place stress. And things should be explored further to find a gender difference in work-related stress.

Bangladesh has experienced different life pattern because of COVID from beginning of 2020, though the Government declared lockdown for all organizations including educational institute at the end of March. This epidemic disease started to spread from end of 2019 from Wuhan, China to all over the world. From fear of death from CORONA virus, people started to maintain social and physical distance and started to work from their home. Though people have started to coop with new normal situation, however, until vaccine reach to everyone, counting death has become the common phenomena to everyone all over the world.

Research Question

It is assumed that work demand and (lack of) support from the organization may create work-life stress among managers. Thus, the main research question of this paper is:

Is work-demand and work support create work-life stress among entry to mid-level managers?

Research Objectives

The main objective of this paper is to assess the overall work-life stress among entry to mid-level managers at workplace because of work from home during COVID 19 Pandemic situation. Considering the primary objective, the specific objectives of this research have been developed as following:

19. To see the level of work-life stress among entry to mid-level managers.
19. To see the impact of age and gender on work-life stress of managers due to the demand for and support of work at workplace.
19. To see the correlation among different factors responsible for work-life stress.

H_{0wd_age}: Stress level from WD is not equal for two different age groups.  

H_{0ws_age}: Stress level from WS is not equal for two different age groups.  

H_{0wd_gender}: Stress level from WD is not equal for both male and female.  

H_{0ws_gender}: Stress level from WS is not equal for both male and female.  

Research Methodology

Variables for the study were identified based on the literature review. For quantitative analyses, a questionnaire survey was done on employees of different organizations who are in their mid-level career. Though all the respondents, however, almost everyone among them is feared about losing their job because of COVID-19. The primary focus of this research was to identify the demand from and support of the organizations towards their employees, and if there is any stress for that. Participants were initially briefed on the aims and objectives of the study along with its confidentiality. Questionnaires link was then sent to the participants and given twenty minutes time for completion. The secondary data are taken from journals, websites, and other references.

Responses were collected from Employees of different organizations who are in their mid-level career. In total 200 managers were surveyed, but ultimately 197 were considered for research as 3 respondents did not fulfill the questionnaire properly. Among 197 respondents, majority are male 136 (69.01%).Following table shows respondents’ gender-based profile:

Table 1: Respondents Age and Gender-based Profile.

Age and Gender		Number of respondents	Total
<30	Male	45 (61.64%)	73 (37.06)
	Female	28 (38.36%)
31-40	Male	91 (73.39%)	124 (62.94)
	Female	33 (26.61%)
Total		197	197

This research followed the smaller item pool, 38 items, aka “Developmental Workplace Stressors Assessment Questionnaire”. The 38 items represented eight scales: demands (10 items), control (6 items), support (5 items), role (4 items), relationships (4 items), rewards (5 items), change (3 items), and communications (1 item) (Maysaa et al., 2010). For this research, only the demands (10 items), and support (5 items) items have been used.

Table 2: Factors Responsible for Work-life Stress.

Demand Factors (10)		Support Factors (5)
D1	Number of meetings	S1	Supervisor is deceitful to employees’ concerns
D2	Demands affect personal relationships	S2	Ability to talk to supervisor is less
D3	Difficulty to unwind at home	S3	Do not get help by colleagues
D4	Too much work	S4	Performance feedback is not clear and timely
D5	Conflicting demands	S5	Supervisors is not helpful with work out problems
D6	Neglected tasks		--
D7	Work long hours		--
D8	Unrealistic time pressures		--
D9	No space for other activities		--
D10	Too much pressure		--

 

A 5-point Likert scale ranging from 1 (1= strongly disagree) to 5 (5= strongly agree) has been used to measure the level of work-life stress among managers.

For our study, both descriptive and inferential analysis have been used. Descriptive analysis (mean) has been used to measure work life stress and the Independent Samples T- test has been used for hypotheses testing. A bivariate analysis was also done to find correlations among 15 factors of work demand and work support.

Scope of the Study

The study mainly attempts to find out the impact of work-life stress among entry-level to mid-level managers. Although there are many factors responsible to develop stress among managers. However, for the purpose of this study only two biological factors, age and gender as independent variables and 15 factors of stress as dependent variables have been considered. This research can be address again with more factors both dependent and independent and in different work settings.

Findings and Analysis

Reliability Test

A reliability test is important to check the appropriateness of the tool used in the research. Higher value of Cronbach alpha indicates the more reliability of the scale generated and scales having Alpha value more than 0.7 can be considered as reliable (Nunnally, 1978). We have conducted reliability test and found Cronbach’s alpha 0.790.

Descriptive Analysis

Analysis have been done to investigate factors, responsible for development of employee’s stress at the time of COVID-19 considering age and gender as independent variables.

  

Impact of Gender on Work Life Stress (Work Support): From the descriptive analysis, we may conclude that overall stress from work support was higher among male employees, however average score (3.596) is very much alarming (table 6).   
 

Table 6: Impact of Gender on Work Life Stress (WLS) because of Work Support (WS).

Support Factors	Gender	Mean	Std	Std. Error	Average Mean
Supervisors deceitfulness	Male	3.6765	1.1475	.0984	3.599
	Female	3.4262	1.3719	.1757
Access to supervisor	Male	3.7132	1.2347	.1059	3.604
	Female	3.3607	1.5169	.1942
Supportive colleague	Male	3.6029	1.1174	.0958	3.568
	Female	3.4918	1.2059	.1544
Performance feedback	Male	3.5809	1.1710	.1004	3.482
	Female	3.2623	1.3153	.1684
Support from supervisor	Male	3.8015	1.1790	.1011	3.726
	Female	3.5574	1.2586	.1612
Overall Support	Male	3.6750	.93268	.0799	3.596
	Female	3.4197	1.0448	1.338

Hypotheses Testing

The analysis of major hypotheses of this research are (Table 7):

H_{0wd_age}: Stress level from work demand (WD) is not equal for two different age groups.   

The p-value of Levene’s test is 0.854 (p>0.05). So, we look at the t-test (Assuming equal variance). The value of t-test is 0.602 (>0.05); hence, we rejected the null hypothesis H_{0wd_age} at 5% level of significance. Thus, stress level from work demand from any organization is same for all age group.

H_{0ws_age}: Stress level from work support (WS) is not equal for two different age groups.  

The p-value of Levene’s test is 0.969 (p>0.05). So, we look at the t-test (Assuming equal variance). The value of t-test is 0.283 (>0.05); hence, we rejected the null hypothesis H_{0ws_age} at 5% level of significance. Thus, stress level from work support from any organization is same for all age group.

H_{0wd_gender}: Stress level from work demand (WD) is not equal for two male and female.

The p-value of Levene’s test is 0.978 (p>0.05). So, we look at the t-test (Assuming equal variance). The value of t-test is 0.870 (>0.05); hence, we rejected the null hypothesis H_{0wd_gender} at 5% level of significance. Thus, stress level from work demand from any organization is equal for both male and female.

H_{0ws_gender}: Stress level from work support (WS) is not equal for two male and female.

The p-value of Levene’s test is 0.286 (p>0.05). So, we look at the t-test (Assuming equal variance). The value of t-test is 0.089 (>0.05); hence, we rejected the null hypothesis H_{0ws_gender} at 5% level of significance. Thus, stress level from work support from any organization is equal for both male and female.

Table 7: Independent Samples Test.

Factors responsible	Assumption of variances	LTEV*		t-test for Equality of Means
		F	Sig.	t	Df	Sig. (2-tailed)	Mean Diff-erence	95% Confidence Interval of the Difference
								Lower	Upper
Age_Work Demand	EVA	.034	.854	-.523	195	.602	-.06169	-.29431	.17093
	EVNA			-.520	148.166	.604	-.06169	-.29623	.17285
Age_Work Support	EVA	.001	.969	-1.077	195	.283	-.15460	-.43766	.12847
	EVNA			-1.078	151.394	.283	-.15460	-.43798	.12879
Gender_Work Demand	EVA	.001	.978	-.164	195	.870	-.02017	-.26331	.22298
	EVNA			-.166	120.192	.868	-.02017	-.26030	.21997
Gender_Work Support	EVA	1.144	.286	1.711	195	.089	.25533	-.03903	.54969
	EVNA			1.638	104.617	.104	.25533	-.05372	.56438

 

*LTEV means Levene's Test for Equality of Variances.

**EVA= Equal variances assumed; and EVNA= Equal variances not assumed

For individual factors under work demand and work support, 15 working hypotheses under two main headings: Age and Gender have been discussed below:

  

Impact of Gender on Work Life Stress (Factors of Work Support): The p-value of Levene’s test is more than 0.05 (p>0.05) for every factors under work support from organizations except the cases of ‘Supervisory sensitivity’ and ‘Access to supervisor’. In these two cases, p-value of Levene’s test are (.028<0.05) and (.001<0.05). So, we look at the t-test (Assuming equal variance). The values of t-test are more than 0.05 (>0.05) for every factors under work support from organizations; hence, we rejected all 5 working hypotheses under work support at 5% level of significance. Thus, stress level from any organization for each factor under work support (WS) is same for both male and female (Table 11).  

*LTEV means Levene's Test for Equality of Variances.

**EVA= Equal variances assumed; and EVNA= Equal variances not assumed

Bivariate Correlation Analysis

Sometimes, one factor may influence other factor(s). That’s why a bivariate correlation analysis was also done among 15 factors responsible for work-life stress among managers at the 0.05 and 0.01 level of significant. Details of analysis has been presented in Table 12.

Table 12: Bivariate Analysis

Pearson’s Correlations
Factors***		D1	D2	D3	D4	D5	D6	D7	D8	D9	D10	S1	S2	S3	S4	S5
D1	X	1
	Y
D2	X	.423**	1
	Y	.000
D3	X	.037	.150*	1
	Y	.608	.036
D4	X	.225**	.302**	-.040	1
	Y	.001	.000	.579
D5	X	.262**	.383**	-.002	.296**	1
	Y	.000	.000	.978	.000
D6	X	.259**	.360**	-.085	.252**	.557**	1
	Y	.000	.000	.233	.000	.000
D7	X	.417**	.374**	-.040	.448**	.229**	.160*	1
	Y	.000	.000	.579	.000	.001	.025
D8	X	.343**	.358**	-.025	.388**	.451**	.553**	.461**	1
	Y	.000	.000	.724	.000	.000	.000	.000
D9	X	.264**	.329**	-.197**	.284**	.356**	.461**	.426**	.421**	1
	Y	.000	.000	.005	.000	.000	.000	.000	.000
D10	X	.444**	.399**	-.084	.366**	.449**	.392**	.487**	.504**	.649**	1
	Y	.000	.000	.239	.000	.000	.000	.000	.000	.000
S1	X	.099	.001	.288**	.074	-.140*	-.019	.009	.020	-.027	.015	1
	Y	.166	.991	.000	.302	.049	.795	.896	.784	.710	.838
S2	X	.037	-.045	.285**	.003	-.098	-.098	-.006	-.036	.014	.027	.618**	1
	Y	.608	.533	.000	.971	.169	.169	.929	.619	.847	.709	.000
S3	X	.148*	.097	.049	.092	-.187**	-.094	.102	.074	.086	.198**	.357**	.439**	1
	Y	.037	.176	.495	.201	.009	.191	.154	.301	.232	.005	.000	.000
S4	X	.087	.086	.181*	.089	-.023	.040	.039	.129	.036	.094	.474**	.586**	.463**	1
	Y	.225	.230	.011	.211	.751	.580	.586	.071	.620	.188	.000	.000	.000
S5	X	.097	.045	.199**	.056	-.081	-.048	.033	-.009	.097	.113	.589**	.661**	.517**	.633**	1
	Y	.175	.534	.005	.432	.259	.501	.650	.905	.175	.115	.000	.000	.000	.000
*. Correlation is significant at the 0.05 level (2-tailed);    **. Correlation is significant at the 0.01 level (2-tailed); and   *** X = Pear Corr, Y= Sig. (2-tailed).

Correlation at 0.05 level of significance: Correlation has been found significant (at the 0.05 level) and positive between meetings and supportive colleagues; between relationship and relax; between relax and performance feedback;  and between neglected tasks and long working hours, however, negative between conflicting demands and supervisory sensitivity.

Correlation at 0.01 level of significance: Correlation also has been found significant (at the 0.01 level) between different factors responsible for creating stress among managers (Table 9 in Appendices):

Conclusion

Whether managers perceive job conditions as stressful or not depends on individual and situational factors-conditioning variables (House and Wells, 1978), and it may be changing life pattern of individuals (Holmes and Rahe, 1967). Therefore, it is important to know the sources of stress before deciding how to manage individual or work-life stress. This study started with the mission to explore managers who is in the early to mid-level stage of their life (less than 40 years) and passing through stress (assumption) because of work demand and work support. This research did not find any significant relations between work-life stress and age or gender, however, managers on average were found to be stressed. Mean average of work-life stress was more than 3.3 for male or female, and for managers, age less than 30 or managers, age 30 to 40. Work demand and work support in both cases, managers, age 30 to 40 were found to be more stressed.  In case of gender, the result is mixed. In case of work demand, female are more stressed and in case of work support, male stressed more. Among all factors all managers regardless their age and gender focused more on unnecessary work pressure and lack of support from supervisor. Organizations may find out the way to avoid all unnecessary work pressure, which may ultimately reduce the work load and time pressure of managers. And managers will be able to concentrate more on important jobs. It is also important to improve interpersonal relationship between supervisors and subordinate. If needed organizations can arrange training programs for supervisors on how to support and keep good relations. Though the different factors responsible for stress were found to be moderate to highly correlated, all the hypotheses regarding stress were accepted and proved to be insignificant. Thus, the research might be misleading if the result is generalized for all levels of management. Therefore, there must be more research on this issue considering stress is harmful, and sometimes devastating for individual life as well as work-life. On the other hand, this study has been done only on the mid-level management with the selective factors of developmental workplace stressors assessment questionnaire which was not found in earlier research on work-life stress measurement in the context of Bangladesh. Future researchers may explore work-life stress with remaining set of factors (variables) with a different sets of sample compositions.

Acknowledgement

We convey our special thanks to all 40 students of the executive program, who were doing their Executive MBA. They individually collected information from 5 employees of mid-level careers including themselves. Therefore, thanks to all 200 sample employees who had voluntarily support us by giving their time to fill out the survey questionnaire, though 197 were usable.

Funding Sources

The study is totally self-funded.

Conflict of Interest

There is no conflict of interest.

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