Table
2. Cronbach’s alpha values for factors used in this study
Sl.
No
Factor
Cronbach’s alpha
Women
Men
Overall independent Stress Factors (1-8)
0.79
0.83
1
Shift
work
0.64*
0.67
2
Working Hours
0.71
0.81
3
Lack
of control
0.72
0.83
4
Social
Support
0.82
0.71
5
Job-insecurity
0.80
0.73
6
Lack
of reward
0.78
0.74
7
Social
support
0.84
0.70
8
Performance
0.76
0.77
Overall:
C-alpha: 0.83; Women: 0.79; Men: 0.83(*very few women work in shifts)
Source:
Primary Data
Statistical analysis
The chi-squared test was
applied to study the if any statistically significant association between
occupational stress factors, general characteristics and its effect on
performance. Univariate and multivariate logistic regression analysis carried
out to test the statistical association between seven occupational stress
causing factors – Shift work, Demanding job (excessive work demand), Working
Hours, Lack of Control, Social Support, Job Insecurity, Lack of reward and
their effect of employee performance. The univariate logistic regression
analysis was carried out to determine the influence of occupational stress
factors and employee performance, and the multivariate logistic regression
analysis was carried out to adjust the variables showing statistically significant
association in the univariate analysis. All the statistical analyses were
conducted using Statistical Analysis System (SAS) ver. 9.4.
Results
Influence of general characteristics and health behaviours on
employee performance: The association between general characteristics, physiological
and psychological factors are presented in Table 3. In this study Women (50.4%)
and men 49.6%) participants more or less equal. There was a high correlation
between gender parity (p=0.028), Age
group (p<0.001), Marital status (p=0.009),
having children (p<0.01), diabetes
(p<0.01), physiological factors (p<0.001), psychological factors (p=0.003)
and experience (tenure of employment, p<0.01) shown significant association
with employee performance. The employee health factor hypertension shown no
statistically significant association with employee performance (p=0.612). Therefore except, hypertension
all other factors effecting the employee performance, however the association
between the general characteristic age group, having children, health factor
diabetes and tenure of employment more significant effect on employee
performance.
Table 3: The association between general
characteristics, occupational stress factors physiological and psychological
factors, and its effect of employee performance
Effect on Performance
Gender
N2
%
Numbers
%
p-value1
Women
381
50.4
236
61.9
0.028
Men
375
49.6
208
55.5
Age (Years)
20-29
226
29.9
26
11.5
<0.01
30-35
265
35
157
59.2
36-40
173
22.9
87
50.2
>40
92
12.2
57
62.0
Marital status
0.009
Married
623
82.4
444
71.3
Unmarried
123
17.6
56
45.5
Children
<0.001 Yes 542 71.7 431 79.5 No 224 29.3 13 5.8 Diabetic Yes 348 46.0 296 85.0 <0.001 No 408 54.0 148 36.2 Hypertension Yes 287 38 165 57.5 0.612 No 469 62 287 61.2 Physiological <0.01 Yes 375 49.6 221 58.9 No 381 50.4 112 29.4 Psychological 0.003 Yes 175 23.1 81 46.3 No 581 76.9 164 28.22 Experience (Years) <0.01 0-5 188 24.9 16 8.5 6-10 318 42.1 196 62.2 11-15 159 21.0 85 53.5 >15
91
12.0
56
61.5
1Comparison
by chi-square test
2All
numbers are based on weighed frequencies
The univariate analysis
of occupational stress factors and employee performance are presented in Table.
The performance of the employees who work in shifts slightly more effected than
non-shift workers as the shift workers were more prone to occupational stress
than the non-shift employees, however the differences were not statistically
significant (p=0.55). The performance
of the group whose job is more demanding (64.0%) significantly affected when
compared with low demand of job (29.1%) and the differences are statistically
different (p=<0.01). The group of employees who worked >60 workers per
week (53.8%) showed high occupational stress so more effect on their
performance when com compared with <40 hrs per week (13.8%), 41-50 hours per
week (19.1%), 51-60 hrs (17.1%) and the differences are statistically different
(p=<0.01). Occupational stressors like lack of control, social support, job
insecurity and lack of reward have statistically significant association with
performance. The stress factor lack of control (p<0.01) effects performance
significantly when compared with other factors (social support p=0.029, job insecurity p=0.024 and lack of reward (p=0.042) Table 4.
Table 4: The association between occupational
stress factors and performance
Effect on Performance
N2
%
Numbers
%
p-value1
Shift work
No
671
88.75
135
20.1
0.55
Yes
85
11.25
20
23.5
Demand Job
Low
423
55.5
123
29.1
<0.001
High
333
44.5
213
64.0
Working hours/week
<40
362
47.9
50
13.8
<0.01
41-50
220
29.2
42
19.1
51-60
105
14.1
18
17.1
>60
69
8.8
35
53.8
Lack of control
Low
521
68.9
123
23.6
<0.01
High
235
31.1
111
47.2
Social Support
Low
587
77.65
233
39.7
0.029
High
169
22.35
45
26.6
Job insecurity
Low
616
81.48
400
64.9
0.024
High
140
18.52
67
47.85
Lack of reward
Low
456
60.32
245
53.7
0.042
High
300
39.68
123
41.0
1Comparison
by chi-square test
2All
numbers are based on weighed frequencies
The multivariate analysis of
occupational stress factors and their association with employee performance at
95% CI is shown in Table. Working in shifts (p=0.39, OR) demanding job (p=0.54,
OR), lack of control (p=0.67, OR) and lack of reward (p=0.29, OR) has no statistically
significant relationship on its association with performance. However, working
for long hours has significant risk factor and effect employee performance.
Compared with the reference group of <40 hours/week, the ORs for working
>60 hours 1.94 (95% CI 1.65-2.44), 51-60 hrs 1.41 (95% CI 1.09-1.71); and
41-50 hours 1.12 (95% CI 1.02-1.41) and P<0.01 for unadjusted model, whereas
1.87 (95% CI 1.54-1.62), 1.52 (95% CI 0.97-1.76), and 1.17 (95% 1.03-1.61)
(p<0.01) in adjusted model respectively, indicating statistically
significant association between working hours and effect on employee
performance.
We also found statistically
significant association between occupational stress factors and employee
performance were significant for Job insecurity and social support. The odds
ratios for job insecurity 3.42 (95% CI 2.86-6.83) social support 4.47 (95% CI
4.38-5.98) for unadjusted model and 4.27 (95% CI 2.86-6.87) and 4.47 (95% CI
4.38-5.98) respectively. Lack of inadequate support and high job insecurity
significantly influence on the occupational stress and employee performance
(Table 5.)
Discussion
In this study we identified
the association between occupational tress factors and its effect on employee
performance using the large representative data collected through a survey
questionnaire circulated among the agricultural research sector employee in and
around the Hyderabad. We have observed a strong association between employee
performance and factors like gender, age, health factor, diabetes, marital
status. The women experience more stress than the men because of their dual
roles as employee and handling the family.
The physiological factors like back/neck pain, short of breathlessness,
nervousness, relaxing issues, psychological factors like anxiety, sleep
disorders, health conditions and depression will cause the stress and effect
the performance. This hypothesis was supported by recent studies (de Graaf et
al. 2012). We also found significant relationship between working hours and
effect on performance. Those who worked more than 60 overs per week had nearly
a 2-fold higher odds ration than those who worked 40 or less hours per week.
Respondents working 51-60 higher odds ration followed by 41-50 hours. This
explains the adverse health effects of long working hours and this is in line
with the studies carried out by (Kivimaki et al. 2011 and Karasek R, 1981).
Table
5: Univariate and multivariate logistic regression analysis of occupational
stress factors and their association with employee performance
(the
odds ratios and 95% CI levels)
Unadjusted OR
Adjusted OR1
OR
(95% CI)
p
OR
(95% CI)
p
Shift work
No
1.00
1.00
Yes
1.21
0.92-1.36
0.45
1.10
0.81-1.41
0.39
Demanding Job
Low
1.00
High
1.76
1.54-2.25
0.68
1.62
1.47-2.92
0.54
Working
hours/week
<40
1.00
1.00
41-50
1.12
1.02-1.41
1.17
1.03-1.61
51-60
1.41
1.09-1.71
<0.01
1.52
0.97-1.76
<0.01
>60
1.94
1.65-2.44
1.87
1.54-2.67
Lack of control
Low
1.00
1.00
High
0.97
0.87-1.14
0.55
0.98
0.84-1.31
0.67
Social support
Low
1.00
1.00
High
4.42
2.76-6.74
<0.01 4.47 4.38-5.98 <0.01 Job insecurity Low 1.00 1.00 High 3.42 2.86-6.83 <0.01 4.27 2.86-6.87 <0.01 Lack of reward Low 1.00 1.00 High 1.72 1.67-3.86 0.34 1.67 1.32-2.94 0.29 1Adjusted model for all listed variables ; OR: odds ratio; CI: Confidence interval The other stress causing factors which have strong association with the employee performance are job insecurity and social support. There was an increase in odds ration with increase in social support indicating the adequate social support will reduce the stress and improves the performance. The similar results were reported in a study carried on CBSE teacher in and around Hyderabad (Prasad et al. 2016). The insecurity was studied the factors of job displacement, change of work place in the same organization, unable to code the new technologies. The job insecurity is one of the major factors of occupation stress in our study and this confirm the studies carried out by (Prasad et al. 2015). Most of our results are in confirmatory with the results of the several studies of the recent past published in referred journal articles. Conclusions and limitations The main reason for conducting this study is that authors are unable to find sufficient literature for finding the association between occupational stress factors and its relationship with performance. We made a sincere attempt to use multivariate logistic regression analysis and univariate logistic regression to analyse dichotomous data and like odd ratios using adjusted and unadjusted models. The limitation of the study is that the authors are not aware that the responses are submitted are top of the mind decision and are own, not influenced by other factors. We have used the Cronbach Alpha reliability statistic to measure the internal consistencies of the research instrument. However, survey research other limitation like the authors have no idea the environment and mood of the respondent when submit the questionnaire. We are surprised by the active participation of the women employees and receipt of the responses were quick and frank compared with men employees. We recommend this type of studies considering gender-related parity on each and every occupational stress factor and its effect on performance.
