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ORIGINAL RESEARCH ARTICLE
Walk your Way to Well-Being at Work: Impact
of a Treadmill Workstation on Employee
Occupational Health Outcomes
Gary W. Giumetti
1
&Samantha A. O’Connor
1
&Berlynn N. Weissner
1
&
Nathaniel R. Keegan
1
&Richard S. Feinn
2
&Carrie A. Bulger
1
Received: 31 August 2020 /Revised: 18 May 2021 / Accepted: 24 May 2021
#The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021
Abstract
Evidence suggests that many employees spend most of their day sitting at their desk
while using a computer workstation. Such sedentary behavior is linked with obesity,
heart disease, and reduced arousal and mood. The current study aimed to expand
existing research on the benefits of an active workstation for reducing sedentary time
at work and improving employee occupational health outcomes. We conducted a
within-subjects experiment in which 25 university employees used a treadmill work-
station for an hour on three workdays and worked at their desk as usual for three
additional workdays (with the order of conditions counterbalanced). At the end of each
workday, participants completed measures of vigor, inattention, mood, job satisfaction,
self-perceived performance, and physical health symptoms. We also gathered step
count through pedometers that participants wore throughout the day. Results indicated
that participants reported significantly higher levels of physical, cognitive, and emo-
tional vigor and positive affect, and lower levels of negative affect and inattention on
days when they used the treadmill workstation than on days when they worked at their
desk as usual. However, we found no significant differences in job satisfaction,
physical symptoms, nor self-perceived performance. We found that participants walked
an average of 4500 more steps (~ 2 miles) on days when they used the treadmill
workstation as compared to their desk as usual. These findings suggest that using a
treadmill workstation may have beneficial effects on employee well-being and physical
activity while not detracting from performance.
Keywords Active workstation .Treadmill desk .Vigor .Attention .Mood .Physical
activity
Occupational Health Science
https://doi.org/10.1007/s41542-021-00091-8
*Gary W. Giumetti
gary.giumetti@quinnipiac.edu
Extended author information available on the last page of the article
In today’s wired workplace, many jobs require prolonged periods of sitting at a desk
and working at a computer workstation. For example, several studies of office
workers found that employees are sitting for most or all of their day while at work
(i.e., 6–10 h; Mackenzie et al., 2017;McCrady&Levine,2009). Such sedentary
behavior has been linked to obesity (Hamilton et al., 2007), as well as metabolic
syndrome, thus increasing one’s risk of heart disease, stroke, and diabetes (Zhou
et al., 2016). Beyond these medical conditions, sitting at work for prolonged
periods of time has also been linked with decreased arousal, mood, and increased
fatigue (Mailey et al., 2017), as well as decreased productivity (Hendriksen et al.,
2016). Estimates of the economic costs associated with physical inactivity and
excessive weight are astronomical, with projected costs estimated at $708 billion
per year (Chenoweth & Leutzinger, 2006).
Given the costs associated with physical inactivity, researchers have begun to
examine the potential benefits of active workstations in the workplace. Such worksta-
tions enable workers to complete work at their desks while also being physically active
through pedaling or walking. Preliminary evidence suggests that active workstations
can reduce sedentary time at work and help with weight loss (Koepp et al., 2013)as
well as increase satisfaction and arousal, and decrease boredom and stress (Sliter &
Yuan, 2015). However, there is relatively little research on the occupational health
impact of such active workstations among working adults. More specifically, previous
research has examined how active workstation use among college students in a lab
setting is linked with improved arousal/energy, mood, and task satisfaction (e.g., see
Pilcher & Baker, 2016; Sliter & Yuan, 2015). In the current study, we build on this
existing research by examining how the use of active workstations impacts similar
outcomes assessed at the end-of-the workday among full-time employees in a work
setting. Additionally, we will further extend this research by examining how active
workstation use is linked with an additional occupational health outcome - somatic
symptoms.
Thus, the purpose of the current study is to examine the impact of an active
workstation on end-of-the-workday employee sedentariness and occupational health
outcomes (e.g., vigor, engagement, attention, somatic symptoms) in a sample of faculty
and staff over a 2-week period. We focus on the relatively immediate effects of using
an active workstation, rather than examining the longer-term impact of such use, as
evidence suggests that light to moderate physical activity can have immediate benefits
for users’cognitive functioning and psychological well-being (e.g., see Centers for
Disease Control and Prevention, 2020; Hogan et al., 2013). In the sections below, we
will describe existing research linking physical activity or use of active workstations
with employee outcomes and propose a series of hypotheses that will be tested in the
current study.
Hypothesis Development
Given our interest in the relatively immediate effects of using an active workstation at
work, we argue in the following paragraphs that such use will impact elements of
employee engagement, mood, physical health symptoms, job attitudes, and perceptions
of performance.
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Vigor The first outcome we will consider is employee vigor. Vigor is one of the
three dimensions of employee engagement and is described as elevated energy and
mental toughness at work, willingness to put in effort at work, and perseverance
when things get difficult (Schaufeli et al., 2002). Several studies support the linkage
between being physically active and improved energy or vigor (Puetz et al., 2006).
For example, Sliter and Yuan (2015) found that undergraduate participants reported
an immediate increase in arousal after using either a walking workstation or a
cycling workstation compared to those who were sitting. Additionally, de Vries
et al. (2017) found that employees who engaged in an exercise intervention had less
emotional exhaustion, fatigue, and need for recovery from the baseline to a 12 week
follow up compared to the control group. Further, Oerlemans and Bakker (2014)
found that engaging in physical activities during off-work hours was linked with
higher levels of both physical and cognitive vigor the next day. Additionally, Ruiter
et al. (2017) found that use of a desk bike was linked with an immediate increase in
energy as compared to when sitting still among a sample of undergraduate students.
Therefore, we developed the following hypothesis:
Hypothesis 1: Relative to days when participants are working at their desk as
usual, participants will report increased end-of-the-workday physical, cognitive,
and emotional vigor on days when they use the treadmill desk.
Attention In addition to employee vigor, we also expect that use of an active work-
station will improve attention. Previous research supports a linkage between physical
activity or active workstation use and improved attention or cognitive abilities. For
example, Coleman et al. (2018) found a relationship between moderate exercise, such
as walking in place, and faster performance on attention-based cognitive tests taken
immediately after exercising. Fenesi et al. (2018) explored the use of light exercise
breaks for university students during lectures and found these breaks promoted in-
creased attention, as assessed by a measure of mind-wandering taken during the lecture.
Similarly, Hillman et al. (2009) found that light treadmill exercise increased attention
and led to better performance on academic achievement tests measured just after the
treadmill session in preadolescent children. Finally, and most directly related to the
current study, Sliter and Yuan (2015) found that participants experienced increased
attention (less boredom) just after using an active workstation compared to sitting and
standing. Together, these studies suggest that light exercise or treadmill use is linked
with immediate gains in attention for participants. Therefore, we developed the fol-
lowing hypothesis:
Hypothesis 2: Relative to days when participants are working at their desk as
usual, participants will report increased end-of-the-workday attention (lower
inattention) on days when they use the treadmill desk.
Mood Previous research has explored how physical activity and active workstations
are linked with positive and negative affect (mood; Wiese et al., 2018). An
extensive literature review by Yeung (1996) suggests that mood was significantly
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higher in those who had exercised than those who had not exercised across the
board. Additionally, Bergouignan et al. (2016) examined how three conditions
(sitting for the entire day, one 30-min walking exercise during the day, and multiple
5-min workouts throughout the day) impacted mood. Their results indicated that
mood increased after one episode of 30-min walking but decreased in as little as one
hour after exercise. Meanwhile, the 5-min workouts scattered throughout the day
led to increased mood after each individual exercise session; thus, mood was
increased many times throughout the day. Similarly, Sliter and Yuan (2015) found
that those who were using walking workstations and cycling workstations experi-
enced higher levels of arousal/positive affect (e.g., active, energetic) and lower
levels of stress/negative mood (e.g., tense, worried) immediately after exercising
than those in standing and sitting conditions. Lastly, among a sample of
undergraduate students, Pilcher and Baker (2016) found that light physical activity
on a cycling workstation was linked with an immediate improvement in positive
mood as compared to when participants were seated at a traditional desk. Together,
these studies suggest that light exercise or workstation use is linked with an
immediate improvement in mood for participants. Thus, we developed the follow-
ing hypothesis:
Hypothesis 3: Relative to days when participants are working at their desk as
usual, participants will report increased end-of-the-workday positive affect and
decreased negative affect on days when they use the treadmill desk.
Physical Health Symptoms A substantial body of research supports the linkage be-
tween exercise or physical activity and improved physical health outcomes (e.g.,
Penedo & Dahn, 2005; Shephard, 1996). Workplace intervention studies in particular
have shown that physical activity can decrease physical health symptoms such as
headache, dizziness, and insomnia (e.g., see Proper et al., 2003 for a review of
longitudinal studies). For example, Pedersen et al. (2019)conductedarandomized
controlled trial with employees in the logistics industry in Norway in which participants
were assigned to either an intervention group (focusing on increasing leisure time
physical activity) or a control group. They found that participants in the intervention
group reported significantly lower somatic symptoms than the control group in the 5-
month post-test.
Limited research has explored the impact of active workstations on reducing
employee somatic symptoms. The available evidence suggests that sit-stand worksta-
tions can be beneficial for reducing musculoskeletal symptoms at the end of the
workday (Husemann et al., 2009; Robertson et al., 2013)aswellasfatigueandsleep
problems measured monthly over six months (Konradt et al., 2020). To our knowledge,
no studies have examined the immediate impact of treadmill workstations on somatic
symptoms. However, based on the existing literature examining physical activity and
somatic symptoms, we developed the following hypothesis:
Hypothesis 4: Relative to days when participants are working at their desk as
usual, participants will report reduced end-of-the-workday somatic symptoms on
days when they use the treadmill desk.
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Job Satisfaction Beyond mental and physical well-being, use of an active workstation
may also boost employee job attitudes and productivity. Previous research has linked
workplace physical activity more broadly and active workstation use more specifically
with improved job satisfaction. First, Haslam et al. (2019) showed that a walking
intervention at work improved levels of organizational commitment and job satisfaction
over a 2-year period compared to a control group (Haslam et al., 2019). Additionally,
meta-analytic evidence suggests that physical activity intervention studies that used a
two-group pre-post design had beneficial effects for job satisfaction (Conn et al., 2009).
Beyond general workplace physical activity interventions, some evidence also suggests
that active workstations can improve job attitudes (e.g., Proença et al., 2018; Sliter &
Yuan, 2015). For example, in a lab setting, Sliter and Yuan (2015) found that use of a
treadmill desk led to an immediate increase in task satisfaction as compared to a
standing desk condition among a sample of college students. These findings suggest
that use of an active workstation to engage in physical activity during the workday may
lead to improved job satisfaction.
Hypothesis 5: Relative to days when participants are working at their desk as
usual, participants will report increased end-of-the-workday job satisfaction.
Performance Perceptions In addition to improved job attitudes, evidence also suggests
that use of a treadmill workstation may impact performance. Although some studies
show that active workstations led to reduced motor speed and control, increased errors,
and impaired executive function (e.g., Podrekar et al., 2020; Zhang et al., 2018), other
studies show that use of a treadmill desk does not impact cognitive functioning nor task
performance compared to using a traditional desk (Alderman et al., 2014; Cao et al.,
2016; Koren et al., 2016;Podrekaretal.,2020; Sliter & Yuan, 2015). For example,
Sliter and Yuan (2015) found that participants using active workstations did not make
more errors in task performance while using a cycling workstation or a treadmill
workstation compared to sedentary workstations. Additionally, Koren et al. (2016)
found no differences in the number of typing errors and cognitive performance between
sitting, cycling at 40 watts, and cycling at 80 watts. Thus, the evidence is unclear about
whether there might be differences in performance after using a treadmill desk as
compared to sitting at one’s desk as usual. Therefore, we developed the following
research question:
Research Question 1: Relative to days when participants are working at their desk
as usual, will participants report changes in perceived performance on days when
they use the treadmill desk?
Method
Participants
Twenty-eight full-time faculty and staff members at a private university in the north-
eastern US enrolled in the study and 25 participants completed the full two weeks of the
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study during either the Fall 2019 semester or the beginning of the Spring 2020 semester
(62.1% female, 37.9% male). In terms of race, 85.2% of the sample identified as white,
7.4% identified as Hispanic or Latino, 3.7% identified as Black or African American,
and 3.7% identified as Middle Eastern or Northern African. The average age was
44.11 years (SD = 9.36), and ages ranged from 24 to 59. The average number of years
that each participant had worked at the university was 7.20 (SD =5.07).Whenaskedto
identify their position type at the university, 65.4% were in professional roles (e.g.,
professor, IT professional, or librarian), 23.1% were in managerial positions (e.g.,
department chair, dean, or administrator), and 11.5% were in clerical positions (e.g.,
secretary or office clerk). The mean BMI for the sample was 25.04 (SD =4.59). When
asked if they had used a treadmill desk previously while completing work, 23 partic-
ipants indicated that they had not, and 2 indicated that they had used one previously. In
terms of physical activity, participants had a mean score of 1.76 (SD = 0.72) on the
Concise Physical Activity Questionnaire (Sliter & Sliter, 2014). This indicates that the
average participant engaged in some form of physical activity 2–3 days per week.
Procedure
Participants were recruited using the campus mail system, fliers hung around campus,
and through email. One orientation session was held for each participant, where they
signed the consent form, filled out a brief background survey (with questions about
demographics and physical activity) while practicing using the treadmill, received their
pedometer and the study instructions, and scheduled their sessions for the study. Each
participant signed up for six days, three of which consisted of walking on the treadmill
in the lab for approximately one hour and three of which consisted of completing their
work at their desk as usual. The six days were completed in two separate weeks, with
one week comprising only treadmill sessions and the other week the desk sessions. The
specific days of the week and times of the day for each session varied based on
participants’schedules (e.g., one participant might have come to the lab on Monday
at 2 pm, Wednesday at 9 am, and Friday at 12 pm, whereas another might have come
on Tuesday at 3 pm, Wednesday at 4 pm, and Thursday at 3 pm).
1
For all six days,
participants were instructed to wear a pedometer from the time they woke until the time
they went to bed. The order of conditions was counterbalanced.
Each participant completed a daily survey at the end of each of the six workdays (see
Measures below) and sent in their daily total step count via text message at the end of
the day. To ensure participant involvement, each participant chose to get reminders
through either email or text message. The research team used Gmail’s‘schedule send’
feature to automate the reminder sending process and customize it for each participant.
These reminders helped the participant to remember to put their pedometer on each
morning, fill out the survey before they left work for the day, and send in their daily
1
To test whether the time of day that participants used the treadmill influenced the outcomes on treadmill
days, we created a 3-category variable to represent the time of the day that participants started their treadmill
session –1=morning(8am–11 am); 2 = midday (11 am-2 pm); 3 = afternoon (2 pm–5 pm). We then
included this variable as a fixed effect in a series of HLM analyses. There were no significant main effects for
any of the outcome variables (all p’s > .10), suggesting that outcomes did not differ based on the time of the
day that the treadmill session took place.
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step count in the evening before bed. When the pedometer was returned, we sent the
participant a $15 gift card for their time.
Equipment
The treadmill workstation consisted of a Lifespan Fitness TR-5000 under desk tread-
mill, an adjustable height desk, and a computer monitor, mouse, and keyboard.
Participants were instructed to wear comfortable clothing and shoes that would be
appropriate for walking. To be consistent with previous research (Sliter & Yuan, 2015),
participants were instructed to choose their own speed for walking, and the treadmill
was set so that it could not operate faster than 2 miles per hour (for user safety). After
completing their treadmill session, participants filled out a treadmill log, where they
entered the speed that they walked, the duration walked, and the type of work they
completed. The mean speed walked among participants was 1.63 mph (SD =0.38mph)
and the mean duration walked was 58.97 min (SD = 14.83). Out of the 66 completed
treadmill logs (there were 9 missing logs), the most commonly reported type of work
activity was emailing (N= 50, or 76%), with the next most common work activities
including class preparation (N= 10, or 15.1%), grading (N= 9, or 13.6%), and working
with spreadsheets (N= 6, or 9.1%). Step count was measured using Omron HJ325
Alvita Ultimate pedometers, which were worn on the body of each participant.
Measures
The daily diary survey contained the following scales:
Momentary vigor was measured with a 9-item scale (Bakker et al., 2013), with 3
items each for physical, cognitive, and emotional vigor. Sample items include “Right
now, I feel vital”(physical), “Right now, I feel I can think rapidly”(cognitive), and
“Right now, I feel I am able to show warmth to others”(emotional). Participants
responded using a 7-point semantic differential scale ranging from 1 (“To little or no
extent”)to7(“To a great extent”). Internal consistency reliability estimates were
acceptable across the six days for each scale (α’s range from .69 to .92 for physical
vigor, .89 to .95 for cognitive vigor, and .85 to .98 for emotional vigor).
Job satisfaction was measured with a 3-item scale (Judge et al., 2000). A sample
item is “Right now, I feel fairly satisfied with my present job”. Participants
responded using a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree).
Internal consistency reliability estimates were good across the six days (α’srange
from .90 to .97).
Inattention was measured with a 3-item subscale from the State Boredom Inventory
(Baratta & Spence, 2018). A sample item is “Today, I had difficulty maintaining my
attention.”Participants responded using a 7-point Likert scale (1 = strongly disagree;
7 = strongly agree). Internal consistency reliability estimates were good across the six
days (α’s range from .85 to .98).
Perceived performance was measured with a 3-item scale (Quiñones, 1995). A
sample item is “Today, I performed very well on my work”. Participants responded
using a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree). Internal consis-
tency reliability estimates were acceptable across the six days (α’s range from .68 to
.96).
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Mood was measured with a 6-item scale adapted from the Positive and Negative
Affect Schedule (PANAS; Watson et al., 1988). Participants were instructed to indicate
to what extent they felt each of the emotions right now, at this present moment using a
5-point Likert scale (1 = very slightly or not at all; 5= extremely). The adjectives for
positive affect were “Interested”,“Enthusiastic”,and“Inspired”and for negative affect,
“Distressed”,“Irritable”,and“Upset”. Internal consistency reliability estimates were
acceptable across the six days (α’s range from .86 to .96 for positive affect, and from
.60 to .92 for negative affect).
Somatic symptoms were measured with a 13-item scale (Kroenke et al., 2002).
Participants were asked to indicate to what extent they were bothered by each of 13
symptoms during that day. Response options ranged from 0 (“not bothered at all”)
to2(“bothered a lot”). Sample symptoms include “Stomach pain”,“Back pain”,
“Pain in your arms, legs, or joints (knees, hips, etc.)”,and“Headaches”.Internal
consistency reliability estimates were acceptable across the six days (α’srange
from .57 to .76).
Data Analysis
A power analysis indicated a sample of 25 subjects would have power of 0.87 to detect
a medium size effect (d = 0.5) between conditions. Given that participants are filling out
the same measures in both conditions, we expected the responses across conditions to
be correlated at a level of 0.70 and we used a two-tailed test for the power analysis. To
compare the effects of working at a treadmill workstation to a desk as usual, a
multilevel linear mixed model (MLMM) was used, where the three repetition days
within the same condition (treadmill or desk as usual) were nested within condition and
the two conditions were nested within each participant. Fixed effects included condi-
tion, day (1, 2, 3), and order (treadmill/desk or desk/treadmill), and random effects
included the intercept, which varied by subject and by condition within subject. The
model also included a fixed effect for the interaction between condition and day to test
if the outcome variables varied across the three days differently between treadmill and
desk conditions. Descriptive statistics included estimated marginal means and standard
errors from the MLMM analyses. For effect size, we calculated the standardized mean
difference, analogous to Cohen’sd, by first taking the difference in estimated marginal
means between the two conditions and dividing this by the square root of the sum of the
variance components for each MLMM analysis (see Westfall et al., 2014). Analyses
were conducted in SPSS v26 and the alpha level for statistical significance was set at
.05.
Results
Table 1shows the estimated marginal mean scores for each outcome variable under
each condition along with results from the test of fixed effects and the Cohen’sdeffect
size for each outcome comparison. There were no significant condition by day inter-
action effects nor conditional main effects for day, suggesting that the outcome
variables did not vary across the three days differently between the treadmill and desk
conditions.
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First, as a manipulation check, we examined whether participants accumulated a
significantly greater total daily step count on days when they used the treadmill desk as
compared to days when they worked at their desk as usual. We found a significant
effect of condition on total daily step count, γ= 4270.58, SE =498.05,p< .001. This
finding indicates that indeed participants in the treadmill phase walked significantly
more steps than they did during the desk phase (d= 1.01). More specifically, partic-
ipants walked an average of 4,270 steps more on days when they used the treadmill
than days when they worked at their desk as usual. This is equivalent to roughly 2
additional miles of walking per day.
For hypothesis 1, results from the MLMM analyses revealed a significant effect of
condition on physical vigor, γ=.66,SE =.20,p= .003, cognitive vigor, γ= .83, SE =.23,
p= .001, and emotional vigor, γ= .60, SE =.20,p= .007. Examination of the estimated
marginal means reveals that participants reported significantly greater end-of-workday
physical (d= 0.54), cognitive (d= 0.70), and emotional vigor (d= 0.45) during the treadmill
condition as compared to the desk condition (see Table 1). These effect sizes might be
considered a medium sized effect (Cohen, 1992). These results support hypothesis 1.
Next, we examined hypothesis 2. We found a significant effect of condition on
inattention, γ=.88, SE =.30,p= .006. Examination of the estimated marginal means
reveals that participants reported significantly lower inattention (higher attention) in the
treadmill condition than in the desk condition (d=−0.54), thus supporting hypothesis
2. Regarding our third hypothesis, we found a significant effect of condition on both
positive affect (γ= .57, SE = .17,p= .003) and negative affect (γ=−.32, SE = .13,
p= .023). Examination of the estimated marginal means indicates that participants
reported significantly greater end-of-the-workday positive affect (d= .57) and lower
negative affect (d=−.48) as compared to when they completed the desk condition.
These results support hypothesis 3.
Table 1 Descriptive Statistics and Results from Multilevel Linear Mixed Modeling (MLMM) Analyses for
Treadmill vs. Desk as Usual Phases
Treadmill Phase Desk Phase
EMM SE EMM SE F p d*
Physical Vigor 5.02 0.19 4.36 0.19 10.81 .003 0.54
Cognitive Vigor 4.99 0.20 4.15 0.19 13.30 .001 0.70
Emotional Vigor 5.30 0.22 4.70 0.22 8.73 .007 0.45
Inattention 2.24 0.25 3.12 0.24 8.90 .006 −0.54
Positive Affect 3.42 0.16 2.85 0.16 10.92 .003 0.57
Negative Affect 1.31 0.11 1.63 0.10 5.84 .023 −0.48
Job Satisfaction 5.56 0.22 5.32 0.22 1.52 .232 0.19
Performance 5.65 0.16 5.51 0.15 0.64 .430 0.13
Physical Symptoms 0.17 0.03 0.22 0.03 2.13 .158 −0.25
Pedometer Reading 10,809.78 694.72 6539.21 688.85 73.52 < .001 1.01
Note. EMM = estimated marginal mean from the MLMM analysis; SE = standard error from the MLMM
analysis; d* = standardized mean difference from MLMM, analogous to Cohen’sd.TheF-statistic is from the
test of Fixed effects for condition
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For hypothesis 4, we did not find a significant effect of condition on physical
symptoms, γ=−.05, SE =.03,p= .158. Examination of the estimated marginal means
reveals that participants reported only slightly lower end-of-the-workday physical
symptoms after using the treadmill desk as compared to the desk as usual condition
(d=−.25). Thus, hypothesis 4 was not supported. We also found no support for
hypothesis 5, as there was no significant effect of condition on job satisfaction,
γ=.24, SE =.19,p= .232, indicating that there were no differences in end-of-the-
workday job satisfaction between the treadmill phase and the desk phase (d=.18).
Lastly, we found no effect of condition on performance, γ=.14, SE =.17,p=.430,
indicating that there were no differences in end-of-the-workday self-perceived perfor-
mance between the treadmill phase and the desk as usual phase (d=.13).
Discussion
The purpose of the current study was to extend the existing literature examining the
impact of active workstations on employee sedentariness and occupational health
outcomes (e.g., vigor, mood, attention, somatic symptoms). Existing research has
primarily explored performance, energy expenditure, physiological health markers,
and sedentariness as outcomes (e.g., see Cao et al., 2016; MacEwen et al., 2015;
Torbeyns et al., 2014), but few studies had examined occupational health outcomes
among an employed sample.
Our results suggest that use of a treadmill workstation over 3 days led to improved
vigor at the end of the workday as compared to working at one’s desk as usual. These
findings support the existing research linking physical activity (more generally) with
increased energy or vigor (e.g., Puetz et al., 2006) as well as studies that examined an
active workstation more specifically (e.g., Ruiter et al., 2017; Sliter & Yuan, 2015). We
also found that participants reported greater attention and positive mood as well as
lower negative mood at the end of the workday on days when they used the treadmill
desk as compared to days when they worked at their desk as usual. These findings
replicate and extend existing research linking physical activity (e.g., Buecker et al.,
2020; Coleman et al., 2018;Fenesietal.,2018; Hillman et al., 2009;Yeung,1996)or
active workstation use (Pilcher & Baker, 2016; Sliter & Yuan, 2015)withimproved
attention and mood. For vigor, attention, and mood, the existing literature has primarily
focused on short-term active workstation interventions with college student samples.
Therefore, our findings extend this line of inquiry to a longer-term duration of treadmill
workstation use as well as to an employed adult sample.
Whereas we found positive effects of the treadmill workstation on vigor, attention,
and mood, we found no differences in physical symptoms nor job satisfaction between
the treadmill desk phase and the desk as usual phase. These findings fail to support the
existing literature linking physical activity (e.g., Pedersen et al., 2019; Penedo & Dahn,
2005;Properetal.,2003) with decreased physical health problems. To our knowledge,
the current study was the first to explore whether treadmill active workstation use
would impact physical health symptoms. Whereas sit-stand desks appear to be bene-
ficial for reducing musculoskeletal symptoms and sleep problems (Husemann et al.,
2009; Konradt et al., 2020), it is interesting to note that three days of treadmill use was
not linked with differences in somatic symptoms, such as pain in the arms, legs, or
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joints, back pain, or dizziness as compared to days when they used their desks as usual.
It is possible that longer term use of the treadmill workstation (either for a longer
duration on a given day or over a greater number of days, weeks, or months) may be
likely to relate to reduced somatic symptoms or improved physical health outcomes.
Previous research showed that active workstation use was linked with increased
satisfaction and arousal (Sliter & Yuan, 2015). However, we found no significant
differences in job satisfaction between the desk phase and treadmill phase. One possible
explanation for these differences is that in the current study we measured momentary
job satisfaction at the end of the workday, whereas existing research measured satis-
faction immediately after using the active workstation. Thus, it is possible that the boost
to job attitudes is short-lived and does not persist to the end of the workday.
We also found no differences in self-perceived performance. This finding aligns
with most existing research, which has shown no differences in cognitive functioning
nor task performance while using an active workstation (Koren et al., 2016;Podrekar
et al., 2020; Sliter & Yuan, 2015). Finally, as expected, our manipulation check
revealed that participants had a greater daily step count on the treadmill days compared
to days when they worked at their desk. Pederson and colleagues (2019) found that a
16-week intervention was sufficient to see a significant increase in physical activity
levels. Both our study and previous studies have found physical activity levels to
increase when participating in exercise during or outside of work. Like other research,
our study also supports the claim that active workstations can reduce sedentary time at
work (Koepp et al., 2013).
Practical Implications
The results obtained from this study highlight the potential benefits that come with the
use of an active workstation for employees. For example, the finding of higher physical,
cognitive, and emotional vigor highlights the value of using the active workstation by
increasing energy during the workday with just light exercise. Participants also reported
greater attention when using the active workstation which may help employees to keep
their focus on the tasks they are assigned. Together, the findings regarding improved
energy, attention, and mood suggest that employees may be more likely to experience
thriving at work after using an active workstation. Existing research suggests that
thriving at work is linked with numerous positive outcomes, including work engage-
ment and task performance (Kleine et al., 2019). Additionally, existing research has
linked positive mood at work with improved business outcomes, including greater
customer loyalty and profitability and reduced turnover (Harter et al., 2003).
One possible concern that managers may have when considering implementing
active workstations is whether they may detract from employee performance. Our
finding that there were no differences in self-rated performance between treadmill days
and typical workdays suggests that managers and supervisors do not have to worry
about the workstation interfering with getting work done. Another practical implication
of our results relates to the finding that participants took an average of 4500 more steps
on days when they used the active workstation as compared to typical workdays. These
findings suggest that use of a treadmill workstation over time may be one way to help
employees to become more physically active, which may lead to improved cardiovas-
cular health and reduced BMI (Healy et al., 2015; Koepp et al., 2013). Overall, the
Occupational Health Science
results suggest that the active workstation offers various physical and mental benefits to
employees with little to no downside.
Limitations and Future Research Directions
Whereas the current study had several strengths, including the focus on employed
adults, the longitudinal nature of the study, and the examination of unique occupational
health outcomes, there were a few limitations that deserve attention. First, we only
examined one type of active workstation –the treadmill desk. Previous research has
used other forms of active workstations to study outcomes relating to work, such as
cycling stations (e.g., Pilcher & Baker, 2016; Sliter & Yuan, 2015), and found similar
results regarding mood and inattention. Using multiple types of active workstations
would have given us the ability to further understand the differences, if any, between
the treadmill desk and other active workstations such as a cycling desk. Future research
should continue to compare the many forms of active workstations to further under-
stand the benefits of each, as well as which is the most user friendly.
Another limitation that the study faced is that the participants were all university
employees. While many studies rely on university staff or students (Yeung, 1996),
studying employees in other professions can help to expand the knowledge on who can
benefit from active workstations and exercise at work. It is possible that the type of
work completed in other occupations that relies on precise mouse movements (e.g.,
graphic design) might be more difficult to complete while using an active workstation.
Future research that examines several different occupations with varying levels of
occupational stressors might help to increase the external validity of the study findings.
Another limitation of the current study is that we did not set a requirement for
treadmill speed, as participants were allowed to adjust their speed to be up to two miles
per hour. Future research could measure how walking at different speeds (e.g., 1 mph, 2
mph, 3 mph) produces different reports on the measures. Another limitation is that most
of the daily outcome measures (except step count) were obtained via self-report.
Further research should consider gathering ratings from other individuals for some
outcomes (such as supervisor-rated performance or co-worker-rated organizational
citizenship behaviors) as well as objective measures of performance and continue
expanding the possible outcome variables tested. For example, studies may wish to
examine the impact of active workstation use on absenteeism and turnover intentions,
as well as workplace safety outcomes and health-related incidents on the job. A further
limitation deals with possible demand characteristics. That is, participants may have
guessed the aims of the study (to improve occupational health by walking at a treadmill
desk), so it is possible that they completed the surveys in line with the study aims. Since
we did not include a post-study question assessing whether they knew the aims of the
study, we are unable to test for this. Future research should include such a manipulation
check as well as utilize a randomized controlled trial design to see if the results of the
current study persist when comparing the results between-subjects as opposed to
within-subjects as was done in the current study. Finally, the current study only lasted
for two weeks for each participant. This short duration provides only a snapshot of
potential positive results of using the active workstation. Future research should have
longer time frames, such as one month or longer, to see if the results produced might be
different.
Occupational Health Science
Future research is also needed that explores the mechanisms for why acute exercise
at work might be linked with positive effects on mood, concentration, and occupational
health outcomes. Several hypotheses have been proposed to explain this linkage. First,
researchers have pointed to a number of possible brain-based changes that take place
following exercise, including increases in peptides such as endorphins (McGeer &
McGeer, 1980; Yeung, 1996), or increases in polypeptides such as brain-derived
neurotrophic factors (BDNF; Szuhany et al., 2015) and these neurochemical changes
are linked with improved mood and concentration. Another hypothesis is that engaging
in exercise serves as a distraction from worrisome thoughts or a chance to detach and
engage in recovery (Yeung, 1996). For example, Sianoja et al. (2018)showedthat
taking a 15-min lunchtime park walk was linked with increased enjoyment and better
afternoon concentration and less fatigue. A third hypothesis focuses on mastery or
accomplishment. That is, accomplishing an important task, such as getting work done
while also engaging in light exercise, leads to a sense of mastery or achievement, which
enhances mood (Yeung, 1996). Future research that tests these mechanisms (or other
possible mechanisms) would add to our understanding of how engaging in acute
physical activity while working leads to enhanced occupational health outcomes.
Conclusion
In summary, the current study found that 3 days of using a treadmill workstation for an
hour each day was linked with higher levels of physical, cognitive, and emotional
vigor, increased attention and positive affect, and decreased negative affect as com-
pared to days when participants worked at their desks as usual. We also found that there
were no differences in self-rated performance (nor in physical symptoms and job
satisfaction) between days when using the treadmill workstation and days when
working at one’s desk as usual. Further, on days when participants used the treadmill
workstation, they walked about 2 additional miles compared to typical workdays. Thus,
the treadmill workstation appears to be a promising tool for helping employees to
increase their levels of light physical activity and boost several occupational health
outcomes while not reducing performance levels.
Declarations
Conflict of Interest We have no known conflicts of interests to disclose.
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Gary W. Giumetti
1
&Samantha A. O’Connor
1
&Berlynn N. Weissner
1
&Nathaniel R.
Keegan
1
&Richard S. Feinn
2
&Carrie A. Bulger
1
1
Department of Psychology, Quinnipiac University, 275 Mount Carmel Avenue, Hamden,
CT 06518, USA
2
Department of Medical Sciences, Quinnipiac University Medical School, 370 Bassett Road, North
Haven, CT 06473, USA
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