Research maximum variability, which is equal to 50%

Research Methodology

 

Research Objective

 

To study the association among Occupational
Stress factors and Performance at workplace among Agricultural Research Sector
Employees at Hyderabad, India.

 

The exploratory and
descriptive research method was followed, with agricultural research sector
employees being the universe of population. The sample size was determined
using Cochran (1977) formula assuming p=0.05 maximum variability and 95% CI
level with 3.5% precision being set (Malhotra and Dash, 2010). The simple
random sampling without replacement being followed where all samples have equal
chance of being selected.

 

Cochran (1977)
developed a formula to calculate a representative sample for proportions as

                                               

 

Where no is sample size, z is the
selected critical value of desired confidence level, p is the estimated
proportion of an attribute that is present in the population,  q =1 – p and e is the desired level of
precision.

 

Assuming the maximum
variability, which is equal to 50% ( p =0.5) and taking 95% confidence level
with ±5% precision, the calculation for required  sample size will be  as follows:

 

          p
= 0.5 and hence q=1-0.5 = 0.5;   e=
0.035;   z =1.96

 

 = 786

 

Subjects: During June 2016-March 2017 the structured questionnaire was
circulated through google form link and hard copy wherever required to over 900
employees of agricultural research sector and received 826 responses and 756 responses
was selected and 70 responses were not considered because the response were not
complete.

 

General
characteristics: The general characteristics examined are respondents age,
gender, marital status and level of education. Age was stratified into four
groups: 20-29 years, 30-35 years, 36-40 years and >40 years.

 

Health behaviours and work-related factors: The participants were
asked to fill about smoking habits, whether diabetic or not, suffer from
hypertension, employment tenure, working hours per week, depressive symptoms
for examining the psychological factors, work-related factors that cause stress
– physiological factors, job insecurity, lack of control, lack of rewards,
excessive job demand and social support. The statements of like “Over the past
six months have you experienced any stress? Did stress effect your job
performance?” used and measured using dichotomous variables Yes/No for
measuring the general characteristics smoking, diabetic, hypertension, etc.

 

Assessment of
occupational stress and its effect on performance: The occupational stress
scale based on occupational stress index constructed and standardized by
Srivastava and Singh (1984); the modified version of the performance scale
(Campbell 1990) and coping strategies scale constructed and standardized by
Srivastava (2001) was used for assessing the occupational stress and its effect
on employee performance.

 

 

Demography
of the sample

Gender

Frequency

Percent

Women

381

50.40

Men

375

49.60

Total

756

100

 

Sample
description

Age group (Years)

No of respondents

Percentage

20-29

226

29.9

30-35

265

35.0

36-40

173

22.9

>40

92                               

12.2

 

 

Research instrument used
for the survey is a standardized, structured undisguised questionnaire, the
main source of primary data collection. Secondary data was collected from
archives of websites, journals, and conference papers. The questionnaire was
divided into two sections and in the Section I the information related to the
general characteristics was gathered. The occupational stress levels and their
impact on employee performance was measured using the Section II of the
questionnaire. To measure the each factor a range of 5-8 statements related to
the occupational stress factors and employee performance were used to gather
data using a 5-point likert type scale. The questions were systematically mixed
to avoid the bias.  The factor analysis
was used to reduce the factors to 7 with the help of SAS 9.4 ver (Table 1)

 

Table
1. Occupational stress factors causing effect on employee performance

Factor

Description

Factors

1

Work in shifts

6 factors –Shift work, reliever issues, transport issues during
late shifts

2

Job demand

6 factors- Seasonal job demand, several job assignment, job
place, excessive work pressure, time management,  etc.

3

Working Hours
 

5 factors – late hours, transport issues, continue to work more
than 8 hours/day, issues of late hours, food

4

Lack of Control
 

8 factors – Job independency, decision making issues,
sub-ordinate control etc.

5

Social Support
 

8  factors – social
support issues like instrumental support, emotional support, support from
family, tangible support, informational support etc.,

6

Job Insecurity
 

6 factors- termination, pink slip, place insecurity, transfer,
job stability etc.

7

Lack of reward
 

6 factors – appreciation, cash rewards, promotions, involving in
decisions, etc.,

8

Performance

5 Factors – Experience Stress, effect on output, absenteeism,
poor work relations

 

Reliability of the research instrument: The
Likert-type scale with items 1-5 was used (where 1=Strongly disagree,
2=Disagree, 3=Neutral, 4=Agree and 5=Strongly agree) in this study.  The reliability statistic C-alpha coefficient
value was calculated to test the internal consistency of the instrument, by
determining how all items in the instrument related to the total instrument (Cronbach,
1951; Gay, Mills, and Airasian, 2006). This instrument was tested on a pilot
group of 100 employees each among both men and Women. They were asked to fill
out the 55-questions, and requested to select the appropriate answer on 5-point
Likert Scale. After analysing their responses from the pilot study with SAS
program, the C-alpha statistic was found to be 0.62 and 0.75 respectively for
Men and Women with overall C-alpha 0.73, suggesting a strong internal
consistency. Three months later, the same instrument was used with 756
employees, 375 Men and 391Women to collect the responses. Five questions were
dropped out from a set of 50 questions because of unsatisfactory C-Alpha
coefficient values. The C-Alpha values for the seven independent and one
dependent factor ranged from 0.67 to 0.83 for Men and from 0.64 to 0.86 for Women,
whereas the overall C-alpha values are, 0.87 and 0.79 for respectively for Men
and Women. The increase in C-alpha values is an effect of dropping the five
questions with low C-Alpha values (Table 2).

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