The term work-life balance is a combination of two words, work and life which denotes how an individual combine both of them to achieve an equilibrium. Healthcare workers on the other hand includes the doctors, nurses and other health care administrators who work in hospitals. The life of a health worker includes an overwhelming level of personal and professional accomplishment, but is associated with a huge degree of anxiety and psychological stress involved in it. Relevant studies have shown that the health care workers are susceptible to mental health issues especially during COVID-19 pandemic. In the course of our study, we have found that factors like workplace stress have been responsible for physical and emotional exhaustion which reduces the enthusiasm to work and can cause anxiety and depression. Various factors inherent to the job, responsibilities related to the patients, the feeling of being overburdened, responsibilities towards the organizations and issues relating to working relationships and ambitions related to the career growth are mainly identified as occupational stressors among the healthcare professionals. It has also been found that emotional fatigue leads to the situation of burnout among the healthcare professionals. The present study tries to identify the various issues and challenges which hampers the work-life balance of the health workers in varied situations in the health care sector during COVID-19 pandemic and to undertake an empirical study on the topic.
The COVID-19 pandemic made it more difficult for the health workers to achieve work life balance, especially in Assam, India. The extraordinary burden the pandemic placed on the healthcare sector presented many challenges for the medical staff in both public and private facilities. They often had to overcome obstacles that were logical, emotional, psychological and physical. The various issues and challenges faced by the health workers of the Government hospitals includes high patient load, workplace violence, resource constraints, administrative burden, psychological stress, financial pressures, inadequate legal protection. The various issues and challenges faced by health workers of private hospitals includes long working hours, disproportionate patient load, violence and safety concerns, administrative and bureaucratic burdens, economic pressures, balancing expectations and mental health issues. Among the main issues concerning the healthcare industry, it was felt that the issues of health workers were unnoticed. (Wu Y., Wang J., Luo C., Hu S., Lin X., Anderson A.E, 2020). The health care centres should take numerous steps to ensure the healthcare workers jobs is fulfilling and satisfying. (Pabalkar V., Prakash S, 2020). It was also found that people in most of the professions are finding it difficult to align the work and non-work obligations due to rapid technological changes as well as imbalance in working life. (Lai J., Ma S., Wang Y., Cai Z., Hu J., Wei N., Hu S., 2020). The healthcare workers often expect collaboration, advice and assistance both from their families and also from the hospitals in order to maintain a degree of balance. (Karan A., Negandhi H., Nair R., Sharma A., Tiwari R., Zodpey S.,2019). It was seen that curing patients who have been infected by the deadly disease is a herculean job for the healthcare workers who are under immense stress due to long working hours in humid and hot conditions. (Humphries N., McDermott A.M., Creese J., Matthews A., Conway E., Byrne J.P.,2020). On the other hand, the health workers need to be concerned about the high number of deaths of the patients even though they may be drained physically and emotionally due to the deficient balance in their work life and subsequent decrease in job satisfaction. (Paffenholz P., Peine A., Hellmich M., Paffenholz S.V., Martin L., Luedde M., Loosen S.H.,2020). One also has to understand the wellbeing of the doctors and also suggest various methods for the improvement of the same. (Hyland-Wood B., Gardner J., Leask J., Ecker U.K.2021). It was also seen that the healthcare professionals especially the doctors experienced greater level of stress than others even in normal circumstances, let alone the Covid-19 pandemic. (Yadav R.K., Yadav S.S.,2014). Mental conditions such as stress, anxiety, depression and insomnia have become common among the healthcare professionals. (Tremblay D.G., Ilama I.I.,2015). The working conditions of the workforce among industries during Covid-19 exposed severe limitations in the purview of access to employment benefits. (Nayeri N.D., Salehi T., Noghabi A.A.A.,2011). Also, policies on work life balance based on the concept that flexibility and fairness can achieve the desired results for the benefit of the workers, employees and the society as well. (Hildt-Ciupińska K., Pawłowska-Cyprysiak K.,2020).
The main objective of the study is to analyse and study the issues and challenges faced by the health workers during the Covid-19 pandemic. The research design for the study is descriptive and exploratory which has been aimed at providing an in-depth understanding of the work life balance among the health workers. A combination of quantitative and qualitative approaches often referred to as a mixed-method design was used. Descriptive design is appropriate here because it describes what is happening in the field, particularly in terms of work-life stress and imbalance outcomes. Descriptive design is also suitable for examining relationships between variables, such as the association between work hours and health outcomes or the effect of organizational support on work-life balance. The research design aligns with the research objectives of the study and based on the objectives, various hypothesis is being framed and tested. To collect the required data, a structured questionnaire was administered to the healthcare workers in various hospitals which allowed for quantitative measurement of work life balance, job stress and organizational support. The target population for this study includes healthcare workers of both government and private hospitals in the state of Assam, India. These workers include both doctors and nurses all of whom are critical in managing healthcare during the Covid-19 pandemic. This makes them an ideal population for studying work-life balance in different work environments. By targeting the specific population, the research aims to provide insights into the effects of long working hours and high stress on personal and family life and also how the healthcare workers managed their responsibilities during the pandemic. The sample size for this study was calculated to ensure that the research findings would be statistically valid and consequently 510 valid responses were considered. Multistage sampling method was used as this approach allows to capture different levels of variability in the population and geographic diversity. Out of the total responses 240 respondents were from government hospitals and 270 respondents were from private hospitals. The analysis of the data was carried out using frequency distribution and percentages and Chi-square test of independence was used to examine the association between the categorical variables
1.1 Problem Associated with Health-workers during Pandemic:
The following are the quantitative analysis of the information that were collected through structured questionnaire:
Table No 1: Training on infection control
|
Training on infection |
Doctor |
Nurse |
Total |
|||
|
Count |
% |
Count |
% |
Count |
% |
|
|
Training in Hospitals |
204 |
57.8 |
114 |
72.6 |
318 |
62.4 |
|
Self-Knowledge on infection |
149 |
42.2 |
43 |
27.4 |
192 |
37.6 |
|
Total |
353 |
100 |
157 |
100 |
510 |
100 |
In case of the training on infection control is concerned, it was found that 57.8 percent of the doctors received training in hospitals whereas 42.2 percent of the doctors revealed that they used their self-knowledge on infection control.
Similarly, in the case of nurses, 72.6 percent of the nurses revealed that they received the required training in their respective hospitals followed by 27.4 percent of the nurses used their self-knowledge on infection control.
Table No 2: Injury while wearing PPE Kits
|
Injury |
Doctor |
Nurse |
Total |
|||
|
Frequency |
% |
Frequency |
% |
Frequency |
% |
|
|
Device related pressure injury |
75 |
21.20 |
39 |
24.80 |
114 |
22.4 |
|
Moist associated injury |
108 |
30.60 |
52 |
33.10 |
160 |
31.4 |
|
Skin tear injury |
82 |
23.20 |
64 |
40.80 |
146 |
28.6 |
In case of Injury caused by wearing PPE Kits are concerned, 30.60 percent of the doctors reported to have moist associated injury, followed by 23.20 percent of the doctors complained of Skin tear injury and 21.20 percent of the doctors suffered Device related pressure injury.
Similarly in the case of nurse, 40.80 percent of the nurses complained of Skin tear injury, followed by 33.10 percent of the nurses complained of Moist associated injury and 24.80 percent of the nurses revealed that they had Device related pressure injury.
Table No 3: Problem faced by health workers during pandemic
|
Main Issues of Health workers during pandemic |
Doctor |
Nurse |
Total |
|||
|
Frequency |
% |
Frequency |
% |
Frequency |
% |
|
|
Lack of amenities |
117 |
33.1 |
33 |
21 |
150 |
29.4 |
|
Inadequate training regarding COVID |
105 |
29.7 |
32 |
20.4 |
137 |
26.9 |
|
Less untrained paramedical staff |
93 |
26.3 |
34 |
21.7 |
127 |
24.9 |
|
Risk of acquiring infection |
179 |
50.7 |
83 |
52.9 |
262 |
51.4 |
In case of the issues faced by the doctor during pandemic, 50.70 percent of the doctors felt that there has been a Risk of acquiring the infection, 33.1 percent of the doctors felt there was lack of amenities, 29.7 percent of the doctors felt there was Inadequate training regarding COVID and 26.3 percent of the doctors felt there was Less untrained paramedical staff.
Similarly in the problems faced by the nurses during pandemic, 52.90 percent of the nurses felt that there is a Risk of acquiring infection, 21.70 percent of the nurses felt there was Less untrained paramedical staff, 21 percent of the nurses felt there was Lack of amenities and 20.40 percent of the nurses felt there was Inadequate training regarding COVID.
Table No 4: Problem faced by health workers at personal level
|
Problem faced at personal Level during pandemic |
Doctor |
Nurse |
Total |
|||
|
Frequency |
% |
Frequency |
% |
Frequency |
% |
|
|
Fear of being isolated by society |
70 |
19.8 |
63 |
40.1 |
133 |
26.1 |
|
Fear of risk of infection to family |
184 |
52.1 |
85 |
54.1 |
269 |
52.7 |
|
Family pressure not to work in Covid duty |
71 |
20.1 |
38 |
24.2 |
109 |
21.4 |
In case of the problems faced by the health workers at the personal level, 52.1 percent of the doctors revealed that they faced the Fear of risk of infection to family, 20.1 percent of the doctors felt there was Family pressure not to work in Covid duty, and 19.8 percent of the doctors had the Fear of being isolated by the society.
Similarly in the case of the nurses, 54.1 percent of the nurses felt there was Fear of risk of infection to family, followed by 40.1 percent of the nurses felt there was Fear of being isolated by society and finally 24.2 percent of the nurses felt there was Family pressure not to work in Covid duty.
Table No 5: Training on Infection of health workers of Government and Private Hospitals
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Training in Hospitals |
Yes |
156 |
65 |
Yes |
162 |
60 |
|
|
No |
84 |
35 |
No |
108 |
40 |
Table No 6: Chi-Square Tests on training in Infection control
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
1.353a |
1 |
0.245 |
|
|
|
Continuity Correctionb |
1.149 |
1 |
0.284 |
|
|
|
Likelihood Ratio |
1.355 |
1 |
0.244 |
|
|
|
Fisher's Exact Test |
|
|
|
0.272 |
0.142 |
|
Linear-by-Linear Association |
1.351 |
1 |
0.245 |
|
|
|
N of Valid Cases |
510 |
|
|
|
|
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 90.35. |
|||||
|
b. Computed only for a 2x2 table |
|||||
From the table above it was felt that 65% of the health workers of government hospitals received training in hospitals and 35% of the health workers revealed that they had no training in the hospitals. Similarly in the case of private hospitals, it was found that 60% of the health workers received training in the hospitals itself and 40% of the doctors revealed that they did not receive any kind of training. As per the Chi-square table, the P-Value is 0.245 which is more than 0.05 and therefore we conclude there has been no significant difference between the health workers of government and private hospitals in having training on infection control during COVID-19 pandemic.
Table No 7: Self-knowledge of health workers of Government and Private Hospitals
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Self-Knowledge |
Yes |
93 |
38.8 |
Yes |
149 |
55.2 |
|
|
No |
147 |
61.3 |
No |
121 |
44.8 |
Table No 8: Chi-Square Tests regarding having self-knowledge
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
13.764a |
1 |
0.000 |
||
|
Continuity Correctionb |
13.113 |
1 |
0.000 |
||
|
Likelihood Ratio |
13.838 |
1 |
0.000 |
||
|
Fisher's Exact Test |
0.000 |
0.000 |
|||
|
Linear-by-Linear Association |
13.737 |
1 |
0.000 |
||
|
N of Valid Cases |
510 |
||||
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 113.88. |
|||||
|
b. Computed only for a 2x2 table |
|||||
In case of the health workers working in the government hospitals, it was found that 38.8% of the health workers used self-knowledge in their work compared to 55.2% of the health workers in the private hospitals used self-knowledge in their work. As per the Chi-square table, the P-Value is 0.00 which is less than 0.05 and therefore we conclude there is a significant difference between the health workers of government and private hospitals in having self-knowledge during COVID-19 pandemic. Therefore we find that in case of private hospitals, the health workers deal with COVID-19 pandemic on their Self-Knowledge as compared to the health workers of government hospitals. It may be due to more autonomy in the private hospitals which allows them to use their own knowledge in dealing with the COVID-19 pandemic. While in case of government hospitals the health workers need to follow procedures rather than their self knowledge.
Table No 9: Injury related to wearing PPE Kits of health workers of Government and Private Hospitals:
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Device related pressure Injury |
Yes |
69 |
28.7 |
Yes |
45 |
16.7 |
|
|
No |
171 |
71.3 |
No |
225 |
83.3 |
|
Moist associated Injury |
Yes |
95 |
39.6 |
Yes |
65 |
24.1 |
|
|
No |
145 |
60.4 |
No |
205 |
75.9 |
|
Skin Tear Injury |
Yes |
70 |
29.2 |
Yes |
76 |
28.1 |
|
|
No |
170 |
70.8 |
No |
194 |
71.9 |
Table No 10: Chi-Square Tests regarding Device related pressure Injury
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
10.689a |
1 |
0.001 |
||
|
Continuity Correctionb |
10.004 |
1 |
0.002 |
||
|
Likelihood Ratio |
10.712 |
1 |
0.001 |
||
|
Fisher's Exact Test |
|
0.001 |
0.001 |
||
|
Linear-by-Linear Association |
10.668 |
1 |
0.001 |
||
|
N of Valid Cases |
510 |
||||
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 53.65. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.01 which is less than 0.05 and therefore we conclude there is a significant difference between the health workers of government and private hospitals in having device related pressure injury during COVID-19 pandemic. It is because of the health workers of government hospitals need to handle more cases and need to wear PPE kit for longer hours as compared to the health workers of private hospitals which leads to device related pressure injury during the COVID-19 pandemic.
Table No 11: Chi-Square Tests regarding Moist associated Injury
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
14.195a |
1 |
0.000 |
||
|
Continuity Correctionb |
13.484 |
1 |
0.000 |
||
|
Likelihood Ratio |
14.229 |
1 |
0.000 |
||
|
Fisher's Exact Test |
0.000 |
0.000 |
|||
|
Linear-by-Linear Association |
14.167 |
1 |
0.000 |
||
|
N of Valid Cases |
510 |
||||
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 75.29. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.00 which is less than 0.05 and therefore we conclude there is a significant difference between the health workers of government and private hospitals in having moist associated injury during COVID-19 pandemic. It is because of the health workers of government hospitals need to handle more cases and need to wear PPE kit for longer hours as compared to the health workers of private hospitals which leads to device related pressure injury during the COVID-19 pandemic.
Table No 12: Chi-Square Tests regarding Skin tear injury
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
.065a |
1 |
0.800 |
||
|
Continuity Correctionb |
0.024 |
1 |
0.876 |
||
|
Likelihood Ratio |
0.064 |
1 |
0.800 |
||
|
Fisher's Exact Test |
0.845 |
0.438 |
|||
|
Linear-by-Linear Association |
0.064 |
1 |
0.800 |
||
|
N of Valid Cases |
510 |
||||
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 68.71. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.80 which is more than 0.05 and therefore we conclude there is no significant difference between the health workers of government and private hospitals in having skin tear injury during COVID-19 pandemic.
4.6 Problems faced by the health workers in Hospital:
Table No 13: Lack of Amenities
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Lack of Amenities |
Yes |
83 |
34.6 |
Yes |
67 |
24.8 |
|
|
No |
157 |
65.4 |
No |
203 |
75.2 |
Table No 14: Chi-Square Tests having required amenities
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
5.840a |
1 |
0.016 |
||
|
Continuity Correctionb |
5.379 |
1 |
0.020 |
||
|
Likelihood Ratio |
5.838 |
1 |
0.016 |
||
|
Fisher's Exact Test |
0.019 |
0.010 |
|||
|
Linear-by-Linear Association |
5.828 |
1 |
0.016 |
||
|
N of Valid Cases |
510 |
||||
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 70.59. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.01 which is less than 0.05 and therefore we conclude there is a significant difference between the health workers of government and private hospitals in having lack of amenities during COVID-19 pandemic. It is because the government hospitals were lacking of proper amenities to handle the huge number of COVID affected people compared to the private hospitals. The number of COVID cases that need to be handled by health workers of private hospitals were relatively much lower as compared to the government hospitals. The affordability of the patients to pay for private hospitals was another issue for lower number of patients in private hospitals compared to the government hospitals.
4.7 Inadequate training regarding COVID:
Table No 15: Inadequate training regarding COVID
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Inadequate training regarding COVID |
Yes |
70 |
29.2 |
Yes |
67 |
24.8 |
|
|
No |
170 |
70.8 |
No |
203 |
75.2 |
Table No 16: Chi-Square Tests having Inadequate training regarding COVID
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
1.225a |
1 |
0.268 |
||
|
Continuity Correctionb |
1.013 |
1 |
0.314 |
||
|
Likelihood Ratio |
1.223 |
1 |
0.269 |
||
|
Fisher's Exact Test |
0.273 |
0.157 |
|||
|
Linear-by-Linear Association |
1.222 |
1 |
0.269 |
||
|
N of Valid Cases |
510 |
||||
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 64.47. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.26 which is more than 0.05 and therefore we conclude there is no significant difference between the health workers of government and private hospitals in having Inadequate training regarding COVID-19 pandemic and therefore we reject Hypothesis 5 that there is a significant difference between the health workers of government and private hospitals in having Inadequate training regarding COVID-19 pandemic
4.8 Less Untrained Paramedical Staff:
Table No 17: Less Untrained Paramedical Staff
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Less Untrained Paramedical Staff |
Yes |
76 |
31.7 |
Yes |
51 |
18.9 |
|
|
No |
164 |
68.3 |
No |
219 |
81.1 |
Table No 18: Chi-Square Tests having Less Untrained Paramedical Staff
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
11.093a |
1 |
0.001 |
||
|
Continuity Correctionb |
10.420 |
1 |
0.001 |
||
|
Likelihood Ratio |
11.113 |
1 |
0.001 |
||
|
Fisher's Exact Test |
0.001 |
0.001 |
|||
|
Linear-by-Linear Association |
11.071 |
1 |
0.001 |
||
|
N of Valid Cases |
510 |
||||
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 59.76. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.01 which is less than 0.05 and we conclude there is a significant difference between the health workers of government and private hospitals in having Less Untrained Paramedical Staff during COVID-19 pandemic. In case of private hospitals, the paramedical staffs were well trained to handle the pandemic situation compared to the government hospitals. It may be due to the recruitment process which has a bureaucratic red tape in case of government hospitals which make them less efficient as compared to the private hospitals.
4.9 Risk of Acquiring Infection:
Table No 19: Risk of Acquiring Infection
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Risk of Acquiring Infection |
Yes |
160 |
66.7 |
Yes |
102 |
37.8 |
|
|
No |
80 |
33.3 |
No |
168 |
62.2 |
Table No 20: Chi-Square Tests having Risk of Acquiring Infection
|
Chi-Square Tests |
|||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
|
Pearson Chi-Square |
44.297a |
2 |
0.000 |
|
Likelihood Ratio |
45.369 |
2 |
0.000 |
|
Linear-by-Linear Association |
40.507 |
1 |
0.000 |
|
N of Valid Cases |
510 |
||
|
a. 2 cells (33.3%) have expected count less than 5. The minimum expected count is .47. |
|||
As per the Chi-square table, the P-Value is 0.00 which is less than 0.05 and we conclude there is a significant difference between the health workers of government and private hospitals in having Risk of Acquiring Infection during COVID-19 pandemic. This risk of acquiring infection is higher in the government hospitals as compared to the private hospitals because the health workers of the government hospitals handled more number of COVID cases during pandemic which make them more susceptible to acquire the infection as compared to the health workers of the private hospitals.
4.10 Problems faced at Personal Level:
Table No 21: Problems faced at Personal Level
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Fear of being Isolated by Society |
Yes |
70 |
29.2 |
Yes |
63 |
23.3 |
|
|
No |
170 |
70.8 |
No |
207 |
76.7 |
|
Fear of Risk of Infection to family |
Yes |
161 |
67.1 |
Yes |
108 |
40 |
|
|
No |
79 |
32.9 |
No |
162 |
60 |
|
Family Pressure not to work in COVID Duty |
Yes |
58 |
24.2 |
Yes |
51 |
18.9 |
|
|
No |
182 |
75.8 |
No |
219 |
81.1 |
Table No 21.1: Fear of being Isolated by Society
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Fear of being Isolated by Society |
Yes |
70 |
29.2 |
Yes |
63 |
23.3 |
|
|
No |
170 |
70.8 |
No |
207 |
76.7 |
Table No 21.2: Chi-Square Tests having Fear of being Isolated by Society
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
2.243a |
1 |
0.134 |
|
|
|
Continuity Correctionb |
1.950 |
1 |
0.163 |
|
|
|
Likelihood Ratio |
2.240 |
1 |
0.134 |
|
|
|
Fisher's Exact Test |
|
|
|
0.157 |
0.081 |
|
Linear-by-Linear Association |
2.238 |
1 |
0.135 |
|
|
|
N of Valid Cases |
510 |
|
|
|
|
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 62.59. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.13 which is more than 0.05 and therefore we conclude there is no significant difference between the health workers of government and private hospitals in having Fear of being Isolated by Society during COVID-19 pandemic. This may be because COVID-19 virus spread among the public and the fear was irrespective of government or private hospital employees. All employees had similar feeling of being isolated from society irrespective of where they work.
Table No 22: Fear of Risk of Infection to family
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Fear of Risk of Infection to family |
Yes |
161 |
67.1 |
Yes |
108 |
40 |
|
|
No |
79 |
32.9 |
No |
162 |
60 |
Table No 23: Chi-Square Tests having Fear of Risk of Infection to family
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
37.392a |
1 |
0.000 |
|
|
|
Continuity Correctionb |
36.313 |
1 |
0.000 |
|
|
|
Likelihood Ratio |
37.924 |
1 |
0.000 |
|
|
|
Fisher's Exact Test |
|
|
|
0.000 |
0.000 |
|
Linear-by-Linear Association |
37.319 |
1 |
0.000 |
|
|
|
N of Valid Cases |
510 |
|
|
|
|
|
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 113.41. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table, the P-Value is 0.00 which is less than 0.01 and therefore we conclude there is a significant difference between the health workers of government and private hospitals in having Fear of Risk of infection to family during COVID-19 pandemic at 99% level of confidence. This is mainly because the health workers of government hospitals could not take proper care and proper sanitization, adequate precautions, equipment were not sufficient in government hospitals compared to any private hospitals due to the high patient rate and unavailability of all required COVID-19 materials.
Table No 24: Family Pressure not to work in COVID Duty
|
|
Govt Hospitals |
Private Hospitals |
||||
|
|
|
Frequency |
Percent |
|
Frequency |
Percent |
|
Family Pressure not to work in COVID Duty |
Yes |
58 |
24.2 |
Yes |
51 |
18.9 |
|
|
No |
182 |
75.8 |
No |
219 |
81.1 |
From the table no. 4.24, we found that 24% of the health workers of Government hospitals were pressurized by the family members not to work in COVID duty and in case of Private hospitals 19% of the health workers were pressurized by the family members not to work in COVID duty.
Table No 25: Chi-Square Tests having Family Pressure not to work in COVID Duty
|
Chi-Square Tests |
|||||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
Exact Sig. (2-sided) |
Exact Sig. (1-sided) |
|
Pearson Chi-Square |
2.106a |
1 |
0.147 |
|
|
|
Continuity Correctionb |
1.804 |
1 |
0.179 |
|
|
|
Likelihood Ratio |
2.103 |
1 |
0.147 |
|
|
|
Fisher's Exact Test |
|
|
|
0.160 |
0.090 |
|
Linear-by-Linear Association |
2.102 |
1 |
0.147 |
|
|
|
N of Valid Cases |
510 |
|
|
|
|
|
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 51.29. |
|||||
|
b. Computed only for a 2x2 table |
|||||
As per the Chi-square table 4.25, the P-Value is 0.14 which is more than 0.05 and therefore we conclude there is no significant difference between the health workers of government and private hospitals in having Family pressure not to work in COVID duty during COVID-19 pandemic. From the table no 4.24 we can see that only 24.2% and 18.9% in case of government and private hospitals employees had pressure from family not to work in COVID duty. Otherwise, it was a general consensus among health workers in India to work for society irrespective of where they work but to save public life at any cost.
Table No 26: Psychological Issues faced by Health Workers in Government and Private Hospitals
|
Psychological Issues |
Government Hospitals |
Private Hospitals |
||||
|
N |
Mean |
Std. Deviation |
N |
Mean |
Std. Deviation |
|
|
Fear of getting infection |
240 |
4.2458 |
0.85446 |
270 |
4.1630 |
0.87261 |
|
Stressed |
240 |
4.0125 |
0.95278 |
270 |
3.9815 |
0.93845 |
|
Anxious |
240 |
3.0958 |
1.04460 |
270 |
3.3667 |
1.06429 |
|
Temper Outburst |
240 |
3.0167 |
1.12025 |
270 |
3.2148 |
1.00100 |
|
Insomnia |
240 |
2.9000 |
1.00125 |
270 |
3.0556 |
0.95272 |
|
Optimistic |
240 |
2.7667 |
1.14792 |
270 |
3.0481 |
1.09472 |
Table No 27: ANOVA Table of Psychological Issues faced by health workers
|
|
||||||
|
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Optimistic |
Between Groups |
10.067 |
1 |
10.067 |
8.025 |
0.005 |
|
|
Within Groups |
637.307 |
508 |
1.255 |
|
|
|
|
Total |
647.375 |
509 |
|
|
|
|
Anxious |
Between Groups |
9.32 |
1 |
9.32 |
8.372 |
0.004 |
|
|
Within Groups |
565.496 |
508 |
1.113 |
|
|
|
|
Total |
574.816 |
509 |
|
|
|
|
Temper Outburst |
Between Groups |
4.989 |
1 |
4.989 |
4.45 |
0.035 |
|
|
Within Groups |
569.474 |
508 |
1.121 |
|
|
|
|
Total |
574.463 |
509 |
|
|
|
|
Stressed |
Between Groups |
0.122 |
1 |
0.122 |
0.137 |
0.712 |
|
|
Within Groups |
453.87 |
508 |
0.893 |
|
|
|
|
Total |
453.992 |
509 |
|
|
|
|
Fear of getting infection |
Between Groups |
0.873 |
1 |
0.873 |
1.169 |
0.28 |
|
|
Within Groups |
379.325 |
508 |
0.747 |
|
|
|
|
Total |
380.198 |
509 |
|
|
|
|
Insomnia |
Between Groups |
3.075 |
1 |
3.075 |
3.229 |
0.073 |
|
|
Within Groups |
483.767 |
508 |
0.952 |
|
|
|
|
Total |
486.841 |
509 |
|
|
|
As per the ANOVA table 27, we find that the P-Value of F-test for Optimism, Anxiousness and Temper Outburst among the health workers of government and private hospitals is 0.005, 0.004 and 0.035 which are less than 0.05. Therefore we reject the null hypothesis and can conclude that there is a significant difference in Optimism, Anxiousness and Temper Outburst among the health workers of government and private hospitals during the COVID-19 pandemic.
But the P-Value of F-test for Stressed, Fear and Insomnia is 0.712, 0.28 and 0.073 which are more than 0.05 and therefore we accept the null hypothesis that there is no significant difference between health workers of government and private hospitals in case of stress, fear and insomnia during the pandemic.
Table No 28: Does Health worker’s Job become more Challenging during Pandemic:
|
Health workers job more challenging |
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
Doctor |
353 |
1.00 |
5.00 |
4.3569 |
0.83432 |
|
Nurses |
157 |
2.00 |
5.00 |
4.4968 |
0.76480 |
From the table no 4.28 we can state that during pandemic health workers job was more challenging as compared to normal situation. Out of 5-point scale where 1 means Least challenging and 5 means Most challenging, the mean value of doctors is 4.36 and for nurses is 4.50. It simply means the health workers job during pandemic was more challenging.
Table No 29: Health workers job challenging
|
Group Statistics |
|||||
|
Where do you work |
N |
Mean |
Std. Deviation |
Std. Error Mean |
|
|
Health workers job challenging |
Govt. Hospital |
240 |
4.3917 |
0.80579 |
0.05201 |
|
Private Hospital |
270 |
4.4074 |
0.82522 |
0.05022 |
|
The job of health workers was very challenging during COVID-19 pandemic. It could be understood from the fact that the mean value of challenging job out of 5 point rating scale where 1 was least challenging and 5 was most challenging for the health workers of government and private hospitals was 4.39 and 4.40 out of 5. It shows the challenges they face in rendering their services in hospitals.
Table No 30: T-test for Health workers job challenging
|
|
Levene's Test for Equality of Variances |
t-test for Equality of Means |
|
|||||||
|
F |
Sig. |
t |
df |
Sig. (2-tailed) |
Mean Difference |
Std. Error Difference |
|
|||
|
Health workers job challenging |
Equal variances assumed |
0.033 |
0.857 |
-0.217 |
508 |
0.828 |
-0.01574 |
0.07240 |
||
|
Equal variances not assumed |
-0.218 |
503.525 |
0.828 |
-0.01574 |
0.07230 |
|||||
From the table no 30 the P-Value of t-test is 0.828 which is higher than 0.05, hence we reject the alternate hypothesis that health workers of government hospital’s job was more challenging compared to the health workers of private hospitals during COVID-19 pandemic. So we can conclude that there is no significant difference between government and private hospital employees in job challenges during COVID-19 pandemic.
4.11 Psychological mindset of Health workers:
4.11.1 Positive Feelings:
The following table 31 depicts the psychological mindset of health workers before and during pandemic. 19 positive feelings were studied among the health workers. Wilcoxon Signed Rank Test has been calculated along with Mean and Standard Deviation for each positive feeling to check whether there was any significant difference in the positive feelings of health workers before and during pandemic. The P-Value indicates the level of significance of the Z-Value.
Table No 31: Positive feelings of health workers
|
Variables |
|
Mean |
SD |
Mean Rank |
Z |
P-value |
|
Alert |
Before |
4.92 |
1.09 |
210.29 |
-4.497 |
0.000 |
|
During |
4.62 |
1.23 |
189.54 |
|||
|
Attentive |
Before |
4.99 |
1.06 |
199.31 |
-4.805 |
0.000 |
|
During |
4.68 |
1.17 |
164.11 |
|||
|
Determined |
Before |
4.51 |
1.1 |
192.7 |
-0.36 |
0.719 |
|
During |
4.52 |
1.17 |
187.48 |
|||
|
Concentrating |
Before |
5.02 |
1.02 |
200.69 |
-7.125 |
0.000 |
|
During |
4.58 |
1.18 |
165.98 |
|||
|
Active |
Before |
5.09 |
1.03 |
186.14 |
-0.4 |
0.689 |
|
During |
5.1 |
1.17 |
167.31 |
|||
|
Excited |
Before |
3.65 |
1.17 |
184.16 |
-4.653 |
0.000 |
|
During |
3.99 |
1.25 |
202.74 |
|||
|
Inspired |
Before |
4.56 |
1.12 |
191.75 |
-0.761 |
0.447 |
|
During |
4.5 |
1.2 |
188.12 |
|||
|
Interested |
Before |
4.91 |
1.04 |
176.31 |
-4.141 |
0.000 |
|
During |
4.65 |
1.13 |
164.03 |
|||
|
Proud |
Before |
3.18 |
1.13 |
171.89 |
-2.711 |
0.007 |
|
During |
3.37 |
1.25 |
196.82 |
|||
|
Confident |
Before |
4.85 |
1.01 |
199.84 |
-7.56 |
0.000 |
|
During |
4.38 |
1.11 |
167.53 |
|||
|
Daring |
Before |
3.9 |
1.22 |
179.89 |
-3.839 |
0.000 |
|
During |
4.17 |
1.29 |
202.42 |
|||
|
Energetic |
Before |
4.94 |
1.08 |
232.42 |
-14.839 |
0.000 |
|
During |
3.67 |
1.16 |
142.22 |
|||
|
Happy |
Before |
4.66 |
1.02 |
204.33 |
-14.777 |
0.000 |
|
During |
3.47 |
0.99 |
152.71 |
|||
|
Joyful |
Before |
4.31 |
0.97 |
209.68 |
-14.912 |
0.000 |
|
During |
3.19 |
0.97 |
160.57 |
|||
|
Delighted |
Before |
4.25 |
1.02 |
212.56 |
-14.994 |
0.000 |
|
During |
3.08 |
0.96 |
152.68 |
|||
|
Enthusiastic |
Before |
4.66 |
1.11 |
201.79 |
-11.162 |
0.000 |
|
During |
3.86 |
1.09 |
149.21 |
|||
|
Calm |
Before |
4.49 |
1.11 |
209.5 |
-12.743 |
0.000 |
|
During |
3.5 |
1.09 |
144.74 |
|||
|
Relaxed |
Before |
4.6 |
1.08 |
222.51 |
-14.683 |
0.000 |
|
During |
3.35 |
1.09 |
145.88 |
|||
|
At Ease |
Before |
4.37 |
1.11 |
221.99 |
-14.1 |
0.000 |
|
During |
3.28 |
1.05 |
159.12 |
It can be observed that the positive feelings like Alert, Attentive, Concentrating, Excited, Interested, Proud, Confident, Daring, Energetic, Happy, Joyful, Delighted, Enthusiastic, Calm, Relaxed and At Ease have significant difference among health workers during and before pandemic.
On the other hand, the psychological variable like Determined, Active and Inspired didn’t have any difference during and before pandemic because as a health worker they need to be determined, active and inspired all the time irrespective of pandemic or normal situation. It can be validated by the P-Value which are 0.719, 0.689 and 0.447.
Hence the hypothesis no.13 as Positive feelings of health workers has significantly decreased during the COVID-19 pandemic is accepted as 16 out of 19 positive feelings of health workers has significantly decreased during the pandemic. But the null hypothesis is acceptable to determination, activeness and inspiration because these feelings didn’t have any significant difference during and before the pandemic.
4.11.2 Negative Feelings of health workers:
The following table depicts the psychological mindset of health workers before and during pandemic. 18 negative feelings were studied among the health workers. Z-Test has been calculated along with Mean and Standard Deviation for each negative feelings to check whether there were any significant difference in the negative feelings of health workers before and during pandemic. The P-Value indicates the level of significance of the Z-Value.
Table No 32: Negative feelings of health workers
|
Variables |
|
Mean |
SD |
Mean Rank |
Z |
P-value |
|
Angry |
Before |
3.20 |
1.11 |
150.68 |
-13.141 |
0.000 |
|
During |
4.28 |
1.25 |
224.58 |
|||
|
Frightened |
Before |
2.84 |
1.1 |
163.06 |
-13.373 |
0.000 |
|
During |
3.99 |
1.3 |
224.68 |
|||
|
Distressed |
Before |
3.13 |
1.02 |
155.21 |
-12.45 |
0.000 |
|
During |
4.10 |
1.19 |
213.23 |
|||
|
Irritable |
Before |
3.09 |
1.06 |
143.29 |
-12.768 |
0.000 |
|
During |
4.10 |
1.25 |
214.93 |
|||
|
Upset |
Before |
3.10 |
0.99 |
144.92 |
-12.918 |
0.000 |
|
During |
4.10 |
1.17 |
215.27 |
|||
|
Angry at self |
Before |
2.68 |
1.02 |
155.36 |
-7.858 |
0.000 |
|
During |
3.15 |
1.12 |
181.87 |
|||
|
Nervous |
Before |
3.12 |
1.14 |
181.95 |
-11.238 |
0.000 |
|
During |
4.03 |
1.26 |
218.51 |
|||
|
Lonely |
Before |
3.14 |
1.15 |
175.45 |
-6.509 |
0.000 |
|
During |
3.62 |
1.22 |
204.67 |
|||
|
Sad |
Before |
2.89 |
1.01 |
165.65 |
-12.302 |
0.000 |
|
During |
3.90 |
1.34 |
220.53 |
|||
|
Blameworthy |
Before |
2.91 |
1.04 |
140.58 |
-9.483 |
0.000 |
|
During |
3.53 |
1.25 |
207.56 |
|||
|
Drowsy |
Before |
3.44 |
1.12 |
176.03 |
-9.832 |
0.000 |
|
During |
4.19 |
1.29 |
204.51 |
|||
|
Alone |
Before |
3.27 |
1.14 |
177.29 |
-4.987 |
0.000 |
|
During |
3.62 |
1.23 |
187.08 |
|||
|
Sleepy |
Before |
3.43 |
1.15 |
175.18 |
-9.992 |
0.000 |
|
During |
4.21 |
1.29 |
209.58 |
|||
|
Downhearted |
Before |
3.04 |
1.08 |
156.08 |
-9.968 |
0.000 |
|
During |
3.74 |
1.26 |
204.06 |
|||
|
Disgusted with Self |
Before |
2.74 |
1.09 |
161.16 |
-7.176 |
0.000 |
|
During |
3.18 |
1.17 |
185.86 |
|||
|
Tired |
Before |
4.21 |
1.11 |
171.95 |
-11.413 |
0.000 |
|
During |
5.09 |
1.21 |
214.06 |
|||
|
Sluggish |
Before |
3.33 |
1.17 |
156.01 |
-11.146 |
0.000 |
|
During |
4.15 |
1.25 |
202.11 |
|||
|
Dissatisfied with self |
Before |
2.96 |
1.06 |
153.37 |
-8.344 |
0.000 |
|
During |
3.48 |
1.18 |
193.62 |
It can be observed that all the negative feelings that we have studied like Angry, Frightened, Distressed, Irritable, Upset, Angry at self, Nervous, Lonely, Sad, Blameworthy, Drowsy, Alone, Sleepy, Downhearted, Disgusted with Self, Tired, Sluggish and Dissatisfied with self have significant difference among health workers during and before pandemic.
Hence we reject the null hypothesis that there is no significant difference in negative feelings at 99% level of confidence and comparing the mean values of different negative feelings during and before pandemic we can state that the negative feelings have been increased among health workers during the pandemic as compared to the normal situation (before pandemic).
4.12 Work Life balance of Health Workers:
Table No 33: Paired Sample Statistics of WLB General & during pandemic
|
Paired Samples Statistics |
||||
|
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
|
AVG_WLBG |
4.7871 |
510 |
0.79564 |
0.03523 |
|
AVG_WLBD |
3.5778 |
510 |
0.76659 |
0.03395 |
Table No 34: Paired Samples Correlations of WLB General & during pandemic
|
Paired Samples Correlations |
|||
|
|
N |
Correlation |
Sig. |
|
AVG_WLBG & AVG_WLBD |
510 |
0.124 |
0.005 |
Table No 35: Paired Samples Test of WLB General & during pandemic
|
Paired Samples Test |
||||||||
|
|
Paired Differences |
|
|
|
|
|
|
|
|
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
t |
df |
Sig. (2-tailed) |
|
|
|
|
|
|
Lower |
Upper |
|
|
|
|
AVG_WLBG - AVG_WLBD |
1.20929 |
1.03437 |
0.04580 |
1.11931 |
1.29928 |
26.402 |
509 |
0.000 |
The following table shows the Paired t-test value of work life balance of health workers in general and during pandemic. The result shows the p-value is 0.00 which is less than 0.01. It means that at 99% confidence level we can state that there is a significant difference in the WLB of health workers before and during pandemic.
4.13 Health workers opinion on their profession during COVID-19 pandemic:
During the pandemic whether the health worker has chosen the wrong profession.
Table No 36: Health workers of hospitals and their profession
|
Have you chosen the wrong profession |
Total |
||
|
Yes |
No |
||
|
Govt. Hospital |
59 (24.58%) |
181 (75.42%) |
240 (100%) |
|
Private Hospital |
68 (25.19%) |
202 (74.81%) |
270 (100%) |
|
Total |
127 (24.90%) |
383 (75.10%) |
510 (100%) |
From the Table No. 4.39, we find that 25% of the health workers felt that they have chosen the wrong profession during the COVID-19 pandemic. In case of health workers of both Government and Private hospitals, 25% of the health workers of each feels that they have chosen the wrong profession during the COVID-19 pandemic. From this number, we can visualize the impact of COVID-19 on the mindset of the health workers. The reason for this one-forth of the health workers had this type of feelings are:
Table No. 37: Reason for choosing the wrong profession in Government and Private Hospital during pandemic
|
|
Govt Hospital |
Private Hospital |
||
|
|
Frequency |
Percent |
Frequency |
Percent |
|
Our life is at risk |
12 |
20.3 |
14 |
20.6 |
|
Can be an easy victim of public anger |
11 |
18.6 |
12 |
17.6 |
|
Job is too demanding and stressful |
16 |
27.1 |
17 |
25.0 |
|
Unable to enjoy family and social life |
14 |
23.7 |
12 |
17.6 |
|
Did not get expected rewards and recognition |
6 |
10.2 |
11 |
16.2 |
|
Total |
59 |
100.0 |
2 |
2.9 |
From the Table No. 37, we can state that during pandemic the health profession job was too demanding and stressful because of which they feel that they were in a wrong profession by health workers of both government and private hospitals. It was followed by ‘Unable to enjoy family and social life’ by health workers of government hospitals which accounts for 24% of respondents, and 21% of the private hospital health workers felt that there life was at risk during the pandemic.
4.14 Total hours of working of the health workers:
Table No 38: Paired Sample Statistics of duty during COVID-19
|
Paired Samples Statistics |
||||
|
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
|
Duty before COVID-19 |
8.8451 |
510 |
2.31369 |
0.10245 |
|
Duty after COVID-19 |
11.3275 |
510 |
2.99519 |
0.13263 |
Table No 39: Paired Samples Correlations of duty during COVID-19
|
Paired Samples Correlations |
|||
|
|
N |
Correlation |
Sig. |
|
Duty before COVID-19 & Duty after COVID-19 |
510 |
0.693 |
0.000 |
Table No 40: Paired Samples Test of duty during COVID-19
|
Paired Samples Test |
||||||||
|
|
Paired Differences |
|
|
|
|
t |
df |
Sig. (2-tailed) |
|
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||
|
|
Lower |
Upper |
||||||
|
Duty before COVID-19 - Duty after COVID-19 |
-2.48235 |
2.17204 |
0.09618 |
-2.67131 |
-2.29340 |
-25.810 |
509 |
0.000 |
From the Paired t-test, we can state at 99 % confidence level that the work hours of doctors have significantly increased during the Covid-19 pandemic compared to the normal situation (Before pandemic). The mean working hours of health workers has increased to 11.3 hours from 8.8 hours during the pandemic.
Similarly, for the nurses also the mean working hour has been increased to 9.58 hours from 7.24 hours. The Chi-square table indicated that the difference is significant at 99% level of confidence.
The health workers in hospitals faces multiple issues and challenges which prominently impact their ability to provide quality care. To name a few of the challenges which include in the case of the government hospitals- higher patient load, violence in the workplace, resource constraints, administrative burdens, psychological stress, financial pressures and also inadequate legal protection. In the case of the private hospitals, we find that the issues pertaining to disproportionate patient load, longer working hours, various economic pressures, bureaucratic and administrative burden, balancing expectations, issues related to mental health are found to be significant factors faced by the healthcare workers. Violence in workplace with the addition pressure to perform in adverse environments, increases the emotional as well as the mental strain which often leads to burnout, depression and anxiety.
In the case of issues related to pandemic, it was found that issues such as shortage of medical equipment’s like PPE kits, deficient infrastructure, disruptions in supply chain, insufficient testing, vaccination challenges and ethical dilemmas and fear of carrying the disease to home were some notable issues faced by the health workers. Moreover, the health workers were observed to have PPE kit related injuries like skin tear injury, moist associated injuries, device related injury, etc. They also had to face serious psychological challenges as many of their family members did not support them to work during pandemic.
At the end of the day, improving the safety and the working conditions of the health workers is the need of the hour not only for the wellbeing of the health workers, but also for ensuring that the health workers provide considerable and effective care to the patients. In the absence of such reforms, the healthcare systems would be at a risk of losing talented professionals to dissatisfaction, burnout and increased turnover.