Available via license: CC BY-NC-ND 4.0
Content may be subject to copyright.
KANSAS JOURNAL of MEDICINE
Workplace Stress and Productivity:
A Cross-Sectional Study
Tina Bui, M.D.1, Rosey Zackula, M.A.2, Katelyn Dugan, MS-33,
Elizabeth Ablah, Ph.D., MPH3
1University of Oklahoma at Tulsa, Tulsa, OK
University of Kansas School of Medicine-Wichita, Wichita, KS
2Oce of Research
3Department of Population Health
Received Feb. 7, 2020; Accepted for publication Oct. 29, 2020; Published online Feb. 12, 2021
https://doi.org/10.17161/kjm.vol1413424
ABSTRACT
Introduction. The primary purpose of this study was to evaluate
the association between workplace stress and productivity among
employees from worksites participating in a WorkWell KS Well-
Being workshop and assess any dierences by sex and race.
Methods.xA multi-site, cross-sectional study was conducted to
survey employees across four worksites participating in a WorkWell
KS Well Being workshop to assess levels of stress and productiv-
ity. Stress was measured by the Perceived Stress Scale (PSS) and
productivity was measured by the Health and Work Questionnaire
(HWQ). Pearson correlations were conducted to measure the asso-
ciation between stress and productivity scores. T-tests evaluated
dierences in scores by sex and race.
Results. Of the 186 participants who completed the survey, most
reported being white (94%), female (85%), married (80%), and
having a college degree (74%). A significant inverse relationship was
observed between the scores for PSS and HWQ, r = -0.35, p < 0.001; as
stress increased, productivity appeared to decrease. Another notable
inverse relationship was PSS with Work Satisfaction subscale, r =
-0.61, p < 0.001. One dierence was observed by sex; males scored
significantly higher on the HWQ Supervisor Relations subscale com-
pared with females, 8.4 (SD 2.1) vs. 6.9 (SD 2.7), respectively, p =
0.005.
Conclusions. Scores from PSS and the HWQ appeared to be inverse-
ly correlated; higher stress scores were associated significantly with
lower productivity scores. This negative association was observed for
all HWQ subscales, but was especially strong for work satisfaction.
This study also suggested that males may have better supervisor rela-
tions compared with females, although no dierences between sexes
were observed by perceived levels of stress.
Kans J Med 2021;14:42-45
INTRODUCTION
Psychological well-being, which is influenced by stressors in the
workplace, has been identified as the biggest predictor of self-assessed
employee productivity.1 The relationship between stress and pro-
ductivity suggests that greater stress correlates with less employee
productivity.1,2 However, few studies have examined productivity at a
worksite in relation to stress.
Previous research focused on burnout, job satisfaction, or psycho-
social factors and their association with productivity;3-7 all highlight the
importance of examining overall stress on productivity. Other studies
focused on self-perceived stress and employer-evaluated job perfor-
mance instead of self-assessed productivity.8 However, most studies
examining this relationship have been occupation specific.8,9 Larger
studies examining this relationship were performed in other coun-
tries.1,5,9,10
The purpose of this study was twofold. First, the study sought to elu-
cidate the relationship between stress and productivity in four work-
sites in Kansas. Second, the study sought to examine potential dier-
ences in stress and productivity by sex and race.
METHODS
Recruitment and Sampling Procedures. The target population
was employees from four WorkWell KS worksites. WorkWell KS is
a statewide worksite initiative in Kansas that provides leadership
and resources for businesses and organizations to support work-
site health. Because access to employee emails was unavailable, a
URL link to an online survey was sent to the worksite contact, who
was responsible for ensuring the distribution of the URL link to a
cross-section of employees at the worksite. Following a WorkWell KS
workshop (held in Topeka, Kansas on November 6, 2017) attendees
from the four worksites were recruited to distribute a link to an online
survey to their employees. Workshop attendees were members of
wellness committees or were worksite representatives. Employee
responses to the online survey were collected through mid-Decem-
ber 2017. No compensation was given for disseminating the survey
link or for participating in the study. This study was approved by the
University of Kansas School of Medicine-Wichita’s Human Subjects
Committee.
Online Survey. The online survey comprised demographic items
with two instruments, the Perceived Stress Scale (PSS),11 and the
Health and Work Questionnaire (HWQ).12 Demographic items
included employee, sex, race, age, marital status, and highest level of
education completed.
Perceived Stress Scale. Stress was measured by the PSS, a
10-item questionnaire designed for use in community samples. The
purpose of the instrument is to assess global perceived stress during
the past month. Each item is measured with a Likert-type scale (0 =
Never, 1 = Almost Never, 2 = Sometimes, 3 = Fairly Often, 4 = Very
Often). This scale is reversed on four positively stated questions.
Scoring of the PSS is obtained by summing all responses. Results
range from zero to 40, with higher PSS scores indicating elevated
stress: scores of 0 - 13 are considered low stress, 14 - 26 moderate
stress, and 27 - 40 are high perceived stress. The results for perceived
stress were used by this study as an indication of psychological well-
being.
Health and Work Questionnaire. The HWQ is a 24-item
instrument that measures multidimensional worksite productiv-
ity. Productivity is assessed by asking respondents how they would
describe their eciency, overall quality of work, or overall amount
of work in one week. All items are scaled with Likert-type response
anchors, each ranging from 1 to 10 points. Most are positively worded
items with response scales from least (scored as a 1) to most favorable
42
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (by-nc-nd) License. (CC-BY-NC-ND 4.0: https://creativecommons.
org/licenses/by-nc-nd/4.0/)
KANSAS JOURNAL of MEDICINE
43
WORKPLACE STRESS AND PRODUCTIVITY
continued.
(scored as a 10). Exceptions are items 1 and 16 through 24, which are
negatively worded and reversed scored. Items are divided into six
sub-scales: productivity, concentration/focus, supervisor relations,
non-work satisfaction, work satisfaction, and impatience/irritability.
As part of the HWQ, employees assessed productivity two ways: on
themselves and how their supervisor or co-workers might perceive it.
Accordingly, productivity is stratified into a self-assessed sub-score
and perceived other-assessed sub-score. HWQ scores are tallied and
averaged for each sub-scale, with higher scores generally indicating
greater productivity.
The Consent Process. Representatives who participated in the
WorkWell KS workshop sent an e-mail to their employees with a
request to click on the link and complete the online survey. The link
opened the electronic consent, which was the opening remark, fol-
lowed by the two assessment instruments and the demographic
items. Consent was implied by participation in the survey. To encour-
age survey participation, representatives also sent employees a few
e-mail reminders at their own discretion.
Statistical Analysis. The statistical analysis included descrip-
tive statistics, measures of association, and comparisons of survey
responses by sex and race. Descriptive statistics comprised response
summaries; means and standard deviations were used for continuous
variables, while frequency and percentages were used for categori-
cal responses. The relationship between stress and productivity
measures were assessed using Pearson correlations. Sex and race
comparisons for PSS and HWQ subscales were evaluated using two-
sided t-tests; alpha was set at 0.05 as the level of significance. Study
participants with missing values were excluded pairwise from the
analysis.
Response Rates. Four of nine worksites participated in the study,
including two health departments (89 participants), one school
district (76 participants), and one non-profit for the medically under-
served (21 participants). A total of 188 employees opened the survey
link, 186 employees answered the first question of the survey, and
174 employees completed the survey items. The 12 study partici-
pants with missing values were excluded from the pairwise analysis.
The response rate, defined as those participants who completed the
survey, was 58.6% (n = 174). To protect the confidentiality of respon-
dents, data were aggregated and no other comparisons were made
by location.
RESULTS
Participants who completed the survey included 174 employees
from four worksites in Kansas. Of those who responded, 94% (155
out of 165) reported being white, 85% (142 of 167) reported being
female, 81% (124 of 153) reported being between 30 and 59 years,
and 60% (99 of 166) reported having a bachelor’s degree or higher
(Table 1).
With regard to measures of stress, the mean PSS was 16.4, with
a standard deviation of 6.2, suggesting that employees have moder-
ate levels of stress at these locations. This result was consistent with
the HWQ question regarding “overall stress felt this week”, with a
mean score of 4.7 (SD 2.5; 10 is “very stressed”). Regarding measures
of productivity, the mean overall HWQ was 6.3 (SD 0.7). With the
exception of reverse items, as noted below, scores of 10 indicated
high levels of productivity. Mean scores by scale were: 7.3 (SD 1.0)
for overall productivity, with 7.5 (SD 1.3) for own assessment, and
7.5 (SD 1.2) for perceived other’s assessment; 7.1 (SD 2.7) supervisor
relations, 7.8 (SD 1.8) for non-work satisfaction, and 7.3 (SD 1.7) for
work satisfaction. The mean scale for the reverse items scores were
concentration/focus at 3.4 (SD 2.0), and impatience/irritability 3.2
(SD 1.6).
Table 1. Participant demographics.
Missing Total
Characteristics N = 186 100% n %
Male 19 0.10 25 15.0
Female 142 85.0
White 21 0.11 155 93.9
Minority 10 6.1
Age group 33 0.18
20 - 29 15 9.8
30 - 39 30 19.6
40 - 49 41 26.8
50 - 59 53 34.6
60 - 69 12 7.8
70+ 2 1.3
Married 17 0.09 136 80.5
Unmarried 33 19.5
Highest level of education completed 20 0.11
High school graduate or GED 12 7.2
Some college, no degree 32 19.3
Associate degree 23 13.9
Bachelor degree 65 39.2
Graduate or professional degree 34 20.5
Correlations between the PSS and the HWQ subscales ranged
from -0.61 to 0.55 (Table 2). A negative association was observed
between the PSS and the overall HWQ, r(177) = - 0.35, p < 0.001.
While each of the positively-coded HWQ subscales was associated
negatively with the PSS, the strongest correlation occurred between
work satisfaction and PSS, r(177) = -0.61, p < 0.001, suggesting that
as stress increases work satisfaction declines.
In evaluating dierences by sex, mean scores were significantly
higher for males compared with females for the HWQ Supervisor
Relations subscale (8.4 (SD 2.1) versus 6.9 (SD 2.7), respectively; p
< 0.005; Table 3). No other sex dierences were observed for either
instrument. Similarly, there were no significant dierences by race.
KANSAS JOURNAL of MEDICINE
Table 2. Measures of correlation within and between the PSS and HWQ.
Productivity
Description Total
HWQ Overall Own
assessment
Other's
assessment
Concentration/
focus*
Supervisor
relations
Non-work
satisfaction
Work
satisfaction
Impatience/
irritability*
Overall productivity 0.76 --
- own assessment 0.60 0.89 --
- other's assessment 0.77 0.9 4 0.75 --
Concentration/
focus* -0.02 -0.40 -0.49 -0.37 --
Supervisor relations 0.52 0.30 0.17 0.38 -0.25 --
Non-work
satisfaction 0.47 0.35 0.35 0.38 -0.34 0.14 --
Work satisfaction 0.6 2 0.50 0.42 0.55 -0.48 0.58 0.44 --
Impatience/
irritability* 0.06 -0.07 -0.02 -0.17 0.44 -0.31 -0.34 -0.47 --
PSS -0.35 -0.41 -0.38 -0.45 0.55 -0.39 -0.55 -0.61 0.53
*Reverse scored item
HWQ: Health and Work Questionnaire mean score; PSS: Perceived Stress Scale mean score
Table 3. Comparing results of the PSS and the HWQ by sex.
Male Female
N = 25 N = 142
Description Mean (SD) Mean (SD) p
Total HWQ 6.5 (0.7) 6.3 (0.7) 0.298
Productivity 7.2 (1.3) 7.4 (0.9) 0.461
- own assessment 7.3 (1.7) 7.5 (1.2) 0.414
- other's assessment 7.3 (1.5) 7.5 (1.2) 0.483
Concentration/focus 3.7 (2.2) 3.4 (2.1) 0.446
Supervisor relationship* 8.4 (2.1) 6.9 (2.7) 0.005
Non-work satisfaction 7.8 (2.1) 7.8 (1.8) 0.954
Work satisfaction 7.6 (1.5) 7.2 (1.7) 0.348
Impatience/irritability 3.2 (1.6) 3.2 (1.6) 0.934
PSS 15.8 (6.4) 16.7 (6.2) 0.552
*t-test, two-sided test of equality; equal variances not assumed
44
WORKPLACE STRESS AND PRODUCTIVITY
continued.
DISCUSSION
Findings suggested there is an inverse association between over-
all stress and productivity; higher PSS scores were associated with
lower HWQ scores. These findings are consistent with other cross-
sectional studies comparing productivity and other measures of psy-
chological well-being.1,8,9,10 Thus, employer eorts to decrease stress
in the workplace may benefit employee productivity levels.
In addition, males scored higher for supervisor relations in the
HWQ than females. This finding may suggest that males have stron-
ger relationships with their supervisors. Indeed, there is compelling
evidence to suggest the main factor aecting job satisfaction and per-
formance is the relationship between supervisors and employees.13
Although, this relationship may be mitigated by employee-supervi-
sor interactions of sex, race/ethnicity, status, education, age, support
systems, and other factors, none of which were evaluated in the cur-
rent study.
For example, Rivera-Torres et al.14 suggested that women with
support systems, defined as co-workers and supervisors, experi-
enced less work stress than males. Results from this study seemed to
support Rivera-Torres et al.14 in that females tended to report higher
levels of stress compared with males (although not significant) and
reported weaker relationships with their supervisors. In addition,
Peterson15 evaluated what employee’s value at work and found that
males and females diered significantly. When asked to rank work
values, men valued pay/money/benefits along with results/achieve-
ment/success most, whereas women valued friends/relationships
along with recognition/respect. Perhaps, more research is necessary
to understand the nuances between co-worker and supervisor re-
garding work satisfaction and productivity.
The study contributes to the literature in the use of dierent met-
rics for psychological well-being, defined as stress. Multiple organiza-
tions within Kansas were evaluated for both productivity and stress.
KANSAS JOURNAL of MEDICINE
45
WORKPLACE STRESS AND PRODUCTIVITY
continued.
To our knowledge, the PSS and HWQ have never been used together
to measure the relationship between stress and productivity. Results
suggested that overall productivity (HWQ) was associated with the
HWQ “work satisfaction” subscale. Perceived stress also had the stron-
gest inverse relationship with HWQ sub-scale “work satisfaction” when
compared with HWQ sub-scale “productivity”.
This study suggested that productivity, stress, and job satisfaction
were correlated, therefore, additional research needs to include each
of these variables in greater detail as the current literature has been
mixed on their relationships and potential collinearity. For example,
one study examining two occupations suggested psychological well-
being (defined as psychological functioning) was associated with
productivity, whereas job satisfaction did not.7 In contrast, another
study suggested that psychological well-being has been a bigger factor
in job productivity than work satisfaction alone, but both are associ-
ated with job productivity.9 This current study was able to examine this
relationship by using the PSS and the HWQ together.
More research is needed to understand these dierences by stan-
dardizing terminology. In this study, psychological well-being was
defined as stress. However, other studies have defined psychological
well-being as happiness or as one’s psychological functioning.7,8 This
study also expanded the relationship between psychological well-being
and stress. Previous research focused more on the relationship between
productivity and burnout or job satisfaction.
This study had limitations such as a small sample size (in number
of organizations and number of employees). The sample size assessed
small organizations in the United States, whereas many other large
scale studies on stress occurred over multiple large organizations in
other countries.1,10 There was limited racial diversity in the current
study, as 6.1% (10 of 165) reported being non-white. The population
studied was also primarily female, limiting the strength of compari-
sons made between sexes. Furthermore, because worksites often share
computers, questionnaires may have been completed using the same
IP address; thus, we were unable to prevent multiple entries from the
same individual.
The current study did not detect a dierence in productivity or stress
by race. This diered from other research. For instance, non-whites
experience greater overall stress than whites potentially attributable to
poorer employment status, income, and education.16 Non-whites expe-
rience stress secondary to racial discrimination.17,18 In one study, when
examining productivity among university faculty, non-whites reported
greater stress and produced less research (productivity) compared to
whites.16 Further research needs to be conducted on productivity and
stress by race and ethnicity, and associated variables, such as employ-
ment status, income, education, and occupation, need to be accounted
for in analysis. Dierences between other research and the current study
regarding race may be attributed to the fact that only 6% of respondents
who answered race reported being non-white, making racial diversity in
this study limited, although representative of the population sampled.
CONCLUSIONS
This study suggested there is a negative correlation between over-
all stress and productivity: higher stress scores were significantly as-
sociated with lower productivity scores. This negative association
was observed for all HWQ subscales, but was especially strong for
work satisfaction. This study also suggested that males may have
better supervisor relations compared to females, although no dif-
ferences between sexes were observed by perceived levels of stress.
There was no dierence in productivity or stress by race. The results
of this study suggested that employer eorts to decrease employee
stress in the workplace may increase employee productivity.
REFERENCES
1Donald I, Taylor P, Johnson S, Cooper C, Cartwright S, Robertson S. Work
environments, stress, and productivity: An examination using ASSET. Int J
Stress Manag 2005; 12(4):409-423.
2VanWormer JJ, Fyfe-Johnson AL, Boucher JL, et al. Stress and workplace
productivity loss in the Heart of New Ulm project. J Occup Environ Med
2011; 53(10):1106-1109. PMID: 21983810.
3Singh J. Performance productivity and quality of frontline employees in
service organizations. J Mark 2000; 64(2):15-34.
4Singh J, Goolsby JR, Rhoads GK. Behavioral and psychological conse-
quences of boundary spanning burnout for customer service representa-
tives. J Mark Res 1994; 31(4):558-569.
5van den Heuvel SG, Geuskens GA, Hooftman WE, Koppes LL, van den
Bossche SN. Productivity loss at work; health-related and work-related fac-
tors. J Occup Rehabil 2010; 20(3):331-339. PMID: 19921406.
6Wright TA, Bonett DG. The contribution of burnout to work performance.
J Organ Behav 1997; 18(5):491-499.
7Wright TA, Cropanzano R. Psychological well-being and job satisfaction
as predictors of job performance. J Occup Health Psychol 2000; 5(1):84-
94. PMID: 10658888.
8Cropanzano R, Wright TA. A 5-year study of change in the relation-
ship between well-being and job performance. Consult Psychol J 1999;
51(4):252-265.
9Robertson IT, Birch AJ, Cooper CL. Job and work attitudes, engagement
and employee performance. Leadership & Organization Development
Journal 2012; 33(3):224-232.
10 Jacobs PA, Tytherleigh MY, Webb C, Cooper CL. Predictors of work per-
formance among higher education employees: An examination using the
ASSET Model of Stress. Int J Stress Manag 2007; 14(2):199-210.
11 Cohen S, Kamarck T, Mermelstein R. A global measure of perceived
stress. J Health Soc Behav 1983; 24(4):385-396. PMID: 6668417.
12 Shikiar R, Halpern MT, Rentz AM, Khan ZM. Development of the Health
and Work Questionnaire (HWQ): An instrument for assessing workplace
productivity in relation to worker health. Work 2004; 22(3):219-229.
PMID: 15156087.
13 Tsitmideli G, Skordoulis M, Chalikias M, Sidiropoulos G, Papagrigoriou
A. Supervisors and subordinates relationship impact on job satisfaction and
eciency: The case of obstetric clinics in Greece. International Journal of
Strategic Innovative Marketing 2016; 3(3):1-2.
14 Rivera-Torres P, Araque-Padilla RA, Montero-Simó MJ. Job stress
across gender: The importance of emotional and intellectual demands and
social support in women. Int J Environ Res Public Health 2013; 10(1):375-
389. PMID: 23343989.
15 Peterson M. What men and women value at work: Implications for work-
place health. Gend Med 2004; 1(2):106-124. PMID: 16115589.
16 Cohen S, Janicki‐Deverts DE. Who's stressed? Distributions of psycho-
logical stress in the United States in probability samples from 1983, 2006,
and 2009 J Applied Soc Psychol 2012; 42(6):1320-1334.
17 Din-Dzietham R, Nembhard WN, Collins R, Davis SK. Perceived stress
following race-based discrimination at work is associated with hypertension
in African-Americans. The metro Atlanta heart disease study, 1999-2001.
Soc Sci Med 2004; 58(3):449-461. PMID: 14652043.
18 Mays VM, Coleman LM, Jackson JS. Perceived race-based discrimina-
tion, employment status, and job stress in a national sample of Black women:
Implications for health outcomes. J Occup Health Psychol 1996; 1(3):319-
329. PMID: 9547054.
Keywords: workplace, occupational stress, productivity