Content uploaded by Tine Torbeyns
Author content
All content in this area was uploaded by Tine Torbeyns on Jun 03, 2015
Content may be subject to copyright.
SYSTEMATIC REVIEW
Active Workstations to Fight Sedentary Behaviour
Tine Torbeyns
•
Stephen Bailey
•
Inge Bos
•
Romain Meeusen
Published online: 20 May 2014
Ó Springer International Publishing Switzerland 2014
Abstract
Background The impact of active workstations has been
studied in several settings, and several outcomes have been
investigated. However, the effects on health, work perfor-
mance, quality of life, etc., have never been systematically
reviewed.
Objective To evaluate the existing literature about active
workstations and their possible positive health and work
performance effects.
Data Sources We searched the electronic databases Pub-
Med and Web of Science (up until 28 February 2014). The
search terms we used were ‘active workstation’, ‘standing
workstation’, ‘standing desk’, ‘stand up workstation’, ‘stand
up desk’, ‘walking desk’, ‘walking workstation’, ‘treadmill
workstation’, ‘treadmill desk’, ‘cycling workstation’,
‘cycling desk’ and ‘bike desk’, in combination with ‘health’,
‘quality of life’, ‘cognition’, ‘computer task performance’,
‘absenteeism’, ‘productivity’, ‘academic achievement’,
‘cognitive decline’, and ‘independent living’. In addition, we
searched the reference lists of relevant published articles.
Study Selection Randomized controlled trials, non-ran-
domized controlled trials and non-randomized non-con-
trolled trials investigating the introduction of active
workstations in humans were included in this systematic
review. Only original studies were included, and we did not
accept studies combining the introduction of active work-
stations with other interventions. Outcomes concerning
health, energy expenditure, cognition, quality of life and
work performance were included.
Results We included 32 studies, of which five were longi-
tudinal studies in school-aged children, 10 were longitudinal
studies in adults and 17 were non-longitudinal studies in
adults. Sixteen studies investigated standing desks, 15 inves-
tigated walking desks, and one investigated a cycling work-
station. The general findings were decreased sitting time,
increased energy expenditure, a positive effect on several
health markers, no detrimental effect on work performance,
no acute effect on cognitive function and no straightforward
findings concerning computer task performance.
Conclusion The implementation of active workstations
might contribute to improving people’s health and physical
activity levels. The effect of the use of these active
workstations on cognition and applied work tasks, such as
computer task performance, needs further investigation
before conclusions can be drawn. Another aspect that needs
further investigation is the implementation of the different
active workstations in all age groups.
1 Introduction
It is becoming more and more clear that physical activity,
defined as ‘any bodily movement produced by skeletal
muscles that requires energy expenditure’ [1] or ‘any body
movement that works your muscles and requires more
energy than resting’ [2], is very important for several
aspects of a long and high-quality life.
The literature clearly shows that a physically active
lifestyle has beneficial effects on several health parameters
T. Torbeyns I. Bos R. Meeusen (&)
Department of Human Physiology and Sports Medicine, Vrije
Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium
e-mail: rmeeusen@vub.ac.be
S. Bailey
Department of Physical Therapy Education, Elon University,
Elon, NC 27244, USA
R. Meeusen
School of Public Health, Tropical Medicine and Rehabilitation
Sciences, James Cook University, Queensland, Australia
123
Sports Med (2014) 44:1261–1273
DOI 10.1007/s40279-014-0202-x
[3]. People with higher physical activity levels show lower
risks of developing metabolic syndrome, cardiovascular
disease, diabetes, cancer, hypertension, obesity and mental
health problems, such as anxiety and depression [4]. They
also experience a better quality of life, less stress, better
social interaction and a better self-perception [3, 5].
Physical activity is also known to favourably influence
brain plasticity by facilitating neurogenerative, neuro-
adaptive and neuroprotective processes, and to enhance
executive functions, cognition and some types of learning,
including motor learning [3]. Studies also show that the
combination of physical activity with cognitive challenge,
the so-called enriched environment, is a very important
trigger of neurogenesis and cognitive development [6].
Other benefits of a physically active lifestyle, which are
more specific for certain age groups, include better aca-
demic performance in students [7], better productivity and
less absenteeism in office workers [8, 9], and a decrease in
cognitive decline and an improvement in independent liv-
ing in elderly people [10, 11].
Despite all of these known benefits of being physically
active, worldwide, in 2008, about 31 % of all people aged
15 years and older did not meet the physical activity
guidelines (at least 30 min of moderate physical activity
five times per week) [12]. This has a large impact on
society, specifically in terms of direct and indirect health
care costs [13, 14].
It is not just a focus on physical activity that is needed.
Recent literature suggests that in fact, sedentary behaviour,
referring to ‘any waking activity characterized by an
energy expenditure B1.5 metabolic equivalents and a sit-
ting or reclining posture’ [15], is an even stronger deter-
mining factor for health than physical activity [16].
Mechanization and automation of society have resulted in
significantly reduced demands for physical activity in the
population. Since the middle of the last century, sedentary
behaviour pursuits—such as television viewing, computer
use and electronic games, time spent in automobiles and
occupational sitting—have increased significantly [17].
A common reason that is given for not being physically
active is a lack of time [18, 19]. Therefore, integrating
physical activity into people’s daily life activity could be a
good solution. One possibility is to encourage people to
initiate active transport. In a systematic review by Oja
et al. [20], a strong inverse relationship between commuter
cycling and all-cause mortality, cancer mortality and
morbidity among middle-aged to elderly subjects was
found. Also, consistent improvements in cardiovascular
fitness and some improvements in cardiovascular risk
factors among working-age adults were found. de Geus
et al. [21] confirmed the positive influence on cardiovas-
cular risk factors and additionally found a positive effect on
the health-related quality of life. According to the latter
reports, active transport leads to benefits similar to those
observed with normal physical activity. However, choosing
active transport—for instance, for travelling to work—
might not be possible for everyone, as some people have to
commute over large distances. Another possibility to
increase physical activity levels, and especially to reduce
sedentary time, which is also appropriate for people who
cannot initiate active transport, is to introduce active
workstations into people’s daily life. These workstations
allow people to incorporate physical activity into normally
sedentary desk tasks. No review of the research concerning
active workstations exists so far. Therefore, the purpose of
this systematic review was to evaluate the existing litera-
ture about active workstations, and the possible positive
health and work performance effects.
2 Methods
2.1 Eligibility Criteria
To be included in this systematic review, articles had to
meet certain criteria. These criteria were formulated on the
basis of the PICOS (Participants, Interventions, Compari-
sons, Outcomes, Study design) approach (see Table 1)
[22]. Randomized controlled trials (RCTs), non-random-
ized controlled trials (nRCTs) and non-randomized non-
controlled trials (nRnCTs) investigating the introduction of
active workstations in humans aged 6–18 years (school-
aged children and adolescents), 19–64 years (adults) and
older than 65 years (elderly people) were included. Only
original studies were included, and we did not accept
studies combining the introduction of active workstations
with other interventions. Outcomes concerning health,
Table 1 PICOS (Participants, Interventions, Comparisons, Out-
comes, Study design)—used to define a researchable question [22]
PICOS
component
Details
Participants (P) Humans: school-aged children and adolescents
(aged 6–18 years), adults (aged 19–64 years),
elderly people (aged C65 years)
Interventions (I) Introduction of active workstations (no
combination with other interventions, no
observational studies)
Comparisons (C) Sitting workstation
Outcomes (O) Health, energy expenditure, cognition, quality of
life, computer task performance, productivity,
absenteeism, independent living, cognitive
decline, academic achievement
Study design (S) RCTs, nRCTs and nRnCTs
nRCT non-randomized controlled trial, nRnCT non-randomized non-
controlled trial, RCT randomized controlled trial
1262 T. Torbeyns et al.
123
energy expenditure, cognition, quality of life and work
performance were included. We also only examined arti-
cles written in English.
2.2 Information Sources and Search Strategy
We searched the electronic databases PubMed and Web of
Science (up until 28 February 2014). The search terms we
used were ‘active workstation’, ‘standing workstation’,
‘standing desk’, ‘stand up workstation’, ‘stand up desk’,
‘walking desk’, ‘walking workstation’, ‘treadmill work-
station’, ‘treadmill desk’, ‘cycling workstation’, ‘cycling
desk’ and ‘bike desk’, in combination with ‘health’,
‘quality of life’, ‘cognition’, ‘computer task performance’,
‘absenteeism’, ‘productivity’, ‘academic performance’,
‘cognitive decline’ and ‘independent living’. In addition,
we searched the reference lists of relevant published arti-
cles to make the search as complete as possible.
2.3 Study Selection and Data Collection Process
First, the articles were screened on the basis of their titles
and abstracts. Full-text articles were retrieved if the citation
was considered potentially eligible and relevant. Second,
these full-text articles were screened once again for their
eligibility (fulfilling the PICOS approach). The data col-
lection process is presented in Fig. 1.
2.4 Quality Assessment
To assess the methodological quality of the studies inclu-
ded in this systematic review, we selected relevant ques-
tions from two assessment tools: the SIGN (Scottish
Intercollegiate Guidelines Network) methodology checklist
[23] and the EPHPP (Effective Public Health Practice
Project) quality-assessment tool for quantitative studies
[24]. Two researchers (T.T. and S.B.) independently scored
the studies (Cronbach’s alpha = 0.8). They assessed whe-
ther each criterion was fulfilled. Where disagreement
occurred, a third researcher (I.B.) was called upon to make
the final decision. Studies received a ’?’ when the criterion
was present in the study, a ‘-’ when it was not present in
the study, a ‘?/-’ when it was partly present in the study
and a ‘?’ when it was not mentioned (counted as ‘-’). To
assess dropout, we considered a dropout of 20 % and less
as ‘?’, a dropout between 20 and 40 % as ‘?/-’ and a
dropout of more than 40 % as ‘-’. Studies scoring no ‘-’
(not present in the study) were considered to be strong,
studies scoring 0.5 to 2.5 ‘-’ were considered to be of
moderate quality and studies scoring 3 or more ‘-’ were
considered to be of weak quality. This resulted in 12 strong
studies, 10 moderate studies and 10 weak studies (see
Table 2).
3 Results
3.1 Study Selection
Our search resulted in 767 hits, of which 121 remained
after screening of the titles and abstracts. After duplicates
were removed, 41 studies were withdrawn. Consequently,
all records not leading to full texts were excluded. This led
to 39 remaining full texts, of which two were excluded for
not introducing an intervention [25, 26], two were excluded
for not mentioning any outcomes [27, 28], two were
excluded for combining active workstations with other
interventions at the same time [29, 30] and one was
excluded for not being published in a scientific journal
[31].
3.2 Samples
Studies on the use of active workstations have mainly
focused on the adult population. Of those focusing on
implementation of standing workstations, 11 were con-
ducted in adults and five were conducted in school-aged
children. All 16 studies on the use of walking and cycling
workstations, stepping devices, elliptical machines and
pedal exercise machines investigated their use in adults.
3.3 Interventions in School-Aged Children
The studies performed in school-aged children could all be
classified as either nRCTs [32–35] or nRnCTs [36]. The
influence of introducing standing workstations into the
classroom environment on several parameters has been
examined. Two studies investigated energy expenditure
[32, 33], three investigated physically active/sedentary
behaviour [34–36], two investigated the effect on class-
room behaviour [33, 36], one investigated musculoskeletal
pain and fatigue [34], and one investigated changes in the
body mass index (BMI) [36]. All studies conducted in
school-aged children were longitudinal, with a timespan
varying from 8 weeks [35] to 1 year [32, 33]. During this
time, children had the option to use their standing desks but
were not given a certain duration of time they had to spend
standing. All subjects were taking classes at elementary
school. The investigated population varied from first-grade
[32, 33] to sixth-grade students [36]. An overview of the
studies conducted in school-aged children can be found in
Table 3.
3.4 Interventions in Adults
RCTs, nRCTs and nRnCTs on active workstations were
conducted in the adult population. Also, both longitudi-
nal and cross-sectional designs were used. The studies
Active Workstations 1263
123
mainly focused on three different active workstations—
namely, standing workstations, walking workstations and
cycling workstations. Three research groups assessed a
different active workstation. McAlpine et al. [37] inves-
tigated a portable stepping device, Carr et al. [38]
investigated a portable pedal exercise machine and Bot-
ter et al. [39] investigated an elliptical machine. An
overview of the studies conducted in adults can be found
in Table 4.
3.4.1 Longitudinal Studies
Two studies could be classified as RCTs [40, 41], four as
nRCTs [42–44] and five as nRnCTs [38, 45–48]. The
duration of the interventions varied from 1 week [45]to
1 year [40, 48]. Four studies investigated standing work-
stations [42, 43, 45, 46], five investigated walking
workstations [40, 41, 44, 47, 48] and one investigated a
portable pedal exercise machine [38]. None of the studies
Fig. 1 Flow chart of study
selection for this systematic
review
1264 T. Torbeyns et al.
123
required participants to spend a set amount of time on the
active workstation; they could use them whenever they
wanted.
Ten studies investigated sitting time/sedentary behav-
iour/physically active behaviour [38, 40–48], three inves-
tigated energy expenditure [40, 41, 44], five investigated
several health parameters [41–43, 47, 48], five investigated
work performance [40, 42–44, 48] and two investigated
mood states and other wellbeing-related parameters
[41, 43].
3.4.2 Non-longitudinal Studies
Thirteen of the non-longitudinal studies could be classified
as RCTs [39, 49–60], three studies were classified as
nRCTs [37, 61, 62] and one did not properly define the
randomization method and thus could not be classified
[63]. Seven articles evaluated standing workstations
[49–52, 60, 61, 63], seven evaluated walking workstations
[53–57, 59, 62], one evaluated both walking and cycling
workstations [58], one evaluated both a walking
Table 2 Critical appraisal
Clearly focused
research
question
a
Randomization
a
Control
group
a
Control for
confounders
(matched groups)
a
Valid and reliable
data collection
tools
a
Dropout
(%)
b
Rating
c
Benden et al. [32] --?? ? 5(?) Weak
Blake et al. [33] --?? ?/- ?(-) Weak
Hinckson et al. [34] ?-?? ? ?(-) Weak
Koepp et al. [36] ?--- ?/- 0(?) Weak
Lanningham-Foster et al. [35] ?-?? ? 0(?) Moderate
Alkhajah et al. [42] ?-?? ? 6(?) Moderate
Gilson et al. [45] ?--- ? 0(?) Weak
Grunseit et al. [46] ?--- ? 39 (?/-) Weak
Pronk et al. [43] ?-?? ? 38 (?/-) Moderate
Ben-Ner et al. [40] ???? ?/- 9(?) Moderate
John et al. [47] ?--- ? 0(?) Weak
Koepp et al. [48] ?--- ?
0(?) Weak
Thompson et al. [44] ?-?? ? 4(?) Moderate
Thompson et al. [41] ???? ? 15 (?) Strong
Carr et al. [38] ?--- ? 0(?) Weak
Buckley et al. [61] ?-?? ? 0(?) Moderate
Chester et al. [49] ???? ? 0(?) Strong
Ebara et al. [50] ???? ? 0(?) Strong
Hedge et al. [51] ???? ?11(?) Moderate
Reiff et al. [52] ???? ? 0(?) Strong
Speck and Schmitz [63] ? ? ?? ? 0(?) Moderate
Alderman et al. [53] ???? ? 0(?) Strong
Botter et al. [39] ???? ? 0(?) Strong
Cox et al. [54] ???? ? 0(?) Strong
Funk et al. [55] ???? ? 0(?) Strong
John et al. [56] ???? ? 0(
?) Strong
Levine and Miller [62] ?-?? ? 0(?) Moderate
McAlpine et al. [37] ?-?? ? 0(?) Moderate
Ohlinger et al. [57] ???? ? 0(?) Strong
Straker et al. [58] ???? ? 4(?) Strong
Thompson and Levine [59] ???? ? 0(?) Strong
Hasegawa et al. [60] -??- - 0(?) Weak
a
‘?’ present in the study, ‘-’ not present in the study, ‘/-’ partly present in the study ‘?’ not mentioned, counted as ‘-’
b
‘(?)’ dropout of 20 % or less, ‘(?/-)’ dropout between 20 and 40 %, ‘(-)’ dropout of more than 40 %
c
Studies scoring no ‘-’ (not present in the study) = strong, studies scoring 0.5 or 2.5 ‘-’ = moderate, studies scoring 3 or more ‘-’ = weak
Active Workstations 1265
123
workstation and an elliptical machine [39] and one evalu-
ated both a walking workstation and the use of a portable
stepping device [37].
Eight studies evaluated energy expenditure [37, 39, 52,
54, 59, 61–63], one evaluated physical activity [39], eight
evaluated work performance (mouse clicking, transcrip-
tion, etc.) [50, 51, 55–60], three evaluated discomfort [49–
51] and three evaluated cognitive function [53, 56, 57].
Other outcomes were alertness [50], posture [51], speech
quality and the rate of perceived exertion [54], heart rate
[39], blood glucose excursion [61] and perceived workload
[60].
4 Discussion
As stated in the introduction, physical activity is important
for several reasons, therefore the integration of active
workstations into people’s daily lives has considerable
potential as an intervention. If the effects of using an active
workstation prove to be similar to those achieved by nor-
mal physical activity, people can obtain the same benefits
by combining working/sitting in the classroom or work
environment with being physically active. This also means
that a lack of time can no longer be used as an excuse for
not being physically active [18, 19]. Introducing active
workstations in schools or workplaces can be considered as
the creation of a so-called enriched environment. Several
studies have reported that the combination of cognitive
tasks and physical activity leads to an improvement in
learning capability and cognitive function [6, 64, 65]. The
introduction of these active workstations into people’s
daily lives could thus lead to positive effects in several
aspects—not only in terms of general health but also in
terms of mental health.
Most investigations included in this systematic review
were of moderate to good quality. When quality criteria
were checked, many studies lost points for not having a
control group [36, 38, 45–48, 60], not randomizing the
subjects [32
–38, 42–48, 61, 62], not reporting whether
the questionnaires and measurement methods they used
were valid and reliable [33, 36, 40, 51, 60] and not
matching groups [32–34, 36, 38, 42, 43, 45–48, 60].
Other weaknesses we found were use of the number of
typed words without checking for accuracy to measure
work performance [51], use of a pedometer to assess
standing/sitting time [36] and not allowing any foot
movement during the test [49]. Also, some studies had
small sample sizes, which could have led to non-signifi-
cant findings [47].
4.1 Interventions in School-Aged Children
Benden et al. [32], Blake et al. [33] and Hinckson
et al. [34] reported reduced sitting time due to the imple-
mentation of standing workstations in the classroom. This
Table 3 Active workstation interventions in school-aged children
Reference Sample Intervention Methodological
characteristics
Outcome Remarks
Benden
et al. [32]
31 intervention subjects, 27 control
subjects; first-grade elementary
school students
Standing
workstation;
1 year
nRCT;
longitudinal
Increased energy expenditure (assessed
using BodyBugg armband)
Sex and
age not
reported
Blake
et al. [33]
2 intervention classrooms, 2 control
classrooms, 1 half control and
half intervention classroom
(58 subjects); age range 6–7 years
Standing
workstation;
1 year
nRCT;
longitudinal
Increased energy expenditure (assessed
using BodyBugg armband); potential
behavioural effects: attention, active
participation in class (assessed by
teacher and parents)
Sex not
reported
Hinckson
et al. [34]
23 intervention subjects, 7 control
subjects (14 male); mean age
10 years; elementary school
students
Standing
workstation;
3 months
nRCT;
longitudinal
Reduced sitting (assessed using
ActivPal accelerometer); little to no
musculoskeletal pain or fatigue
(assessed using questionnaire and
observation)
Koepp
et al. [36]
8 subjects (5 male); mean age
11.3 years; sixth-grade
elementary school students
Standing
workstation;
8 months
nRnCT;
longitudinal
No change in BMI; no change in step
counts (assessed using pedometer);
no change in classroom management,
concentration and discomfort
(assessed by teacher)
Pedometer
activity?
Lanningham-
Foster
et al. [35]
24 intervention subjects (10 male),
16 control subjects (10 male);
fourth/fifth-grade elementary
school students
Standing
workstation;
8 weeks
nRCT;
longitudinal,
crossover
No difference in physical activity
(assessed using accelerometer)
Age not
reported
BMI body mass index, nRCT non-randomized controlled trial, nRnCT non-randomized non-controlled trial
1266 T. Torbeyns et al.
123
Table 4 Active workstation interventions in adults
Reference Sample Intervention Methodological
characteristics
Outcome
a
Remarks
Alkhajah
et al. [42]
18 intervention subjects
(1 male), 14 control
subjects (2 male); age
range 20–65 years; office
workers
Standing
workstation;
1 week/
3 months
nRCT;
longitudinal
Reduced sitting time: -143 min/
day (assessed using ActivPal
accelerometer); increased HDL;
no other biomarker change; no
difference in self-reported health
and work performance (assessed
using logbook)
Gilson
et al. [45]
11 subjects (4 male); mean
(± SD) age
46.9 ± 9.8 years;
employees
Standing
workstation;
1 week
nRnCT;
longitudinal
No change in sedentary time
(assessed using SenseWear)
Grunseit
et al. [46]
19 subjects (9 male); age
range 27–59 years
Standing
workstation;
3 months
nRnCT;
longitudinal
Reduced self-reported sitting time:
-102 min/day (OSPAQ and
WSQ)
Pronk
et al. [43]
24 intervention subjects,
10 control subjects;
sedentary occupation
Standing
workstation;
4 weeks
nRCT;
longitudinal
Reduced sitting time: -66 min/
day (experience-sampling
methodology); reduced upper
back and neck pain (assessed
using questionnaire); improved
mood states (assessed using
POMS questionnaire); positive
effect on perceived comfort,
energy, health, focus,
productivity, happiness, stress
(assessed using questionnaire)
Sex and age not
reported
Ben-Ner
et al. [40]
20 intervention subjects for
52 weeks (7 male),
23 control subjects for
29 weeks—intervention
23 weeks (4 male)
Treadmill
workstation;
52 weeks–23
weeks
RCT;
longitudinal
Improved overall work
performance, quality and
quantity of performance,
interactions with co-workers
(assessed using weekly and
quarterly surveys and company
administrative records);
increased daily physical activity
(assessed using accelerometer);
increased energy expenditure:
? [74 kcal/day (assessed using
accelerometer)
Age not reported
John
et al. [47]
12 subjects (5 male); mean
(± SD) age
46.2 ± 9.2 years;
overweight or obese
office workers
Treadmill
workstation;
3 months/
9 months
nRnCT;
longitudinal
Reduction in waist (-5.5 cm) and
hip (-4.8 cm) circumferences,
LDL, total cholesterol; non-
significant decreases in BW
(-2.5 kg), BMI (-1.0 kg/m
2
)
and fat% (-2 %); reduced
sedentary time (assessed using
ActivPal accelerometer)
The nonsignificant
change in BW, BMI
and fat% could have
been due to a too-
small sample
Koepp
et al. [48]
36 subjects (11 male);
sedentary occupation
Treadmill
workstation;
1 year
nRnCT;
longitudinal
Reduced sedentary time:
-43 min/day (assessed using
accelerometer); weight loss
(-1.2 kg); no effect on work
performance (assessed using
validated weekly and quarterly
questionnaires)
Active Workstations 1267
123
Table 4 continued
Reference Sample Intervention Methodological
characteristics
Outcome
a
Remarks
Thompson
et al. [44]
25 subjects; nurses, clinical
assistants, secretaries
Treadmill
workstation;
2 weeks
nRCT;
longitudinal,
crossover
Increase of 2,000 steps per day
(assessed using StepWatch
activity monitor system);
increased energy expenditure:
?100 kcal/day (estimation
based on number of steps/day);
no effect on perceived tiredness
or productivity (assessed using
questionnaire)
Sex and age not
reported
Thompson
et al. [41]
20 subjects; age range
25–70 years; overweight
or obese
Treadmill
workstation;
12 weeks
RCT;
longitudinal,
crossover
Increased physical activity;
increased energy expenditure:
?197 kcal/day (assessed using
accelerometer); weight loss
(-1.85 kg); decreased fat%
(-1.9 %); no difference in
metabolic or wellbeing measures
Sex not reported
Carr
et al. [38]
18 subjects (2 male); mean
(± SD) age
40.2 ± 10.7 years;
sedentary occupation
Pedal exercise
machine;
4 weeks
nRnCT;
longitudinal
Decreased sedentary time
(assessed using physical activity
recall questionnaire)
Buckley
et al. [61]
10 subjects (2 male); age
range 21–61 years
Standing
workstation;
185 min
nRCT; non-
longitudinal,
crossover
Attenuated blood glucose
excursion by 43 % (CGM);
increased energy expenditure:
?0.83 kcal/min (assessed using
Cortex Metalyser 3B); no
difference assessed using
accelerometer
Chester
et al. [49]
18 subjects (11 male); age
range 20–29 years
Standing
workstation
RCT; non-
longitudinal,
crossover
Fatigue and discomfort in standing
[ sit/standing [ sitting
(assessed using validated body
comfort rating chart and Borg
scale)
No movement allowed
in the standing
position
Ebara
et al. [50]
24 subjects (12 male); age
ranges 20–29 years and
60–69 years
Standing
workstation
RCT; non-
longitudinal,
crossover
Increased arousal level: alertness
(LF/HF ratio); increased
musculoskeletal discomfort
(assessed using VAS and
VAMS); no effect on work
performance: transcription
(number of correct letters/min)
Hedge
et al. [51]
18 subjects (6 male); mean
age 19.7 years; university
students
Standing
workstation
RCT; non-
longitudinal,
crossover
More wrist extension; less
comfortable; no effect on work
performance: transcription
(words/min); less foot
movement; more weight shifting
Number of words
typed used to
measure work
performance; no
errors taken into
account
Reiff
et al. [52]
20 subjects (10 male);
mean (± SD) age
22.8 ± 1.9 years
Standing
workstation;
45 min
RCT; non-
longitudinal,
crossover
Increased energy expenditure:
?0.34 kcal/min (assessed using
metabolic gas system)
Speck and
Schmitz [63]
13 subjects (5 male); age
range 25–60 years;
physically inactive
Standing
workstation;
7 min
?; non-
longitudinal,
crossover
No difference in energy
expenditure (assessed using
indirect calorimetry)
Randomized?
Alderman
et al. [53]
66 subjects (27 male);
mean (± SD) age
21.06 ± 1.6 years
Treadmill
workstation
RCT; non-
longitudinal,
crossover
No effect on response speed or
accuracy (assessed using Stroop
test, modified flanker task, test of
reading comprehension)
1268 T. Torbeyns et al.
123
Table 4 continued
Reference Sample Intervention Methodological
characteristics
Outcome
a
Remarks
Botter
et al. [39]
12 subjects (6 male); mean
(± SD) age
38.7 ± 11.4 years
Treadmill
workstation
RCT; non-
longitudinal,
crossover
Increased physical activity;
increased energy expenditure
(assessed using CUELA
system); increased heart rate
Cox et al. [54] 31 subjects (9 male); mean
(± SD) age
37 ± 2.5 years; regularly
physically active
Treadmill
workstation
RCT; non-
longitudinal,
crossover
Increased metabolic rate:
?0.3 mLkg
-1
min
-1
(assessed
using open-circuit spirometry);
no effect on speech quality
(assessed using Adobe
Audition 1.0); no effect on RPE
Funk
et al. [55]
24 subjects (9 male); mean
(± SD) age
23.2 ± 3.1 years
Treadmill
workstation
RCT; non-
longitudinal,
crossover
Decreased typing performance,
except when walking at 2.2 km/
h (assessed using Mavis Beacon
Teaches Typing 2.0, AWPM)
John
et al. [56]
20 subjects (11 male);
mean (± SD) age
24.6 ± 3.5 years
Treadmill
workstation
RCT; non-
longitudinal,
crossover
Decreased mouse clicking and
drag-and-drop test results, typing
(assessed using Mavis Beacon
Teaches Typing 17; AWPM)
and mathematics tests (GRE); no
effect on selective attention,
processing speed (assessed using
Stroop test) and reading
comprehension (assessed using
GRE)
Levine and
Miller [62]
15 subjects (1 male); mean
(± SD) age
43 ± 7.5 years;
sedentary, obese office
workers
Treadmill
workstation
nRCT; non-
longitudinal,
crossover
Increased energy expenditure:
?100 kcal/h (assessed using
indirect calorimetry)
McAlpine
et al. [37]
19 subjects (11 male);
mean (± SD) age
27 ± 9 years; 9 lean,
10 obese
Treadmill
workstation
nRCT; non-
longitudinal,
crossover
Increased energy expenditure:
?163–405 kcal/h (assessed
using indirect calorimetry)
Ohlinger
et al. [57]
50 subjects; mean (± SD)
age 43.2 ± 9.3 years;
university employees
Treadmill
workstation
RCT; non-
longitudinal,
crossover
Decrease in motor speed and
motor control: simple motor task
(digital finger tapping test); no
effect on divided attention and
short-term auditory verbal
memory (assessed using auditory
consonant trigram test) and
selective attention (assessed
using Stroop test)
Sex not reported
Straker
et al. [58]
30 subjects (14 male); age
range 22–64 years; office
workers
Treadmill
workstation
RCT; non-
longitudinal,
crossover
Decreased computer task
performance; mouse
performance was more affected
than typing (assessed using Type
Master Pro, WPM and error rate)
Thompson and
Levine [59]
11 subjects (no males);
experienced medical
transcriptionists
Treadmill
workstation
RCT; non-
longitudinal,
crossover
No effect on accuracy of
transcription (time needed to
transcribe letters and error rate);
increased energy expenditure:
?100 kcal/h (assessed using
ActiCal accelerometer)
Age not reported
McAlpine
et al. [37]
19 subjects (11 male);
mean (± SD) age
27 ± 9 years; 9 lean,
10 obese
Stepping
device
nRCT; non-
longitudinal,
crossover
Increased energy expenditure:
?289 kcal/h, similar to treadmill
walking (assessed using indirect
calorimetry)
Active Workstations 1269
123
reduction in sitting time was accompanied by an increase in
energy expenditure [32, 33]. Lanningham-Foster et al. [35]
and Koepp et al. [36] investigated possible increases in
physical activity levels but did not find a significant
change. Koepp et al. [36] also examined BMI and param-
eters such as classroom management, concentration and
discomfort but did not find any significant changes. Also,
for musculoskeletal pain and fatigue, no significant results
were reported [34].
4.2 Interventions in Adults
4.2.1 Longitudinal Studies
The standing workstation studies by Alkhajah et al. [42],
Pronk et al. [43] and Grunseit et al. [46] reported reduced
sitting time due to the implementation of the workstations.
The reduction varied from 66 min/day [43] to 143 min/day
[42]. In contrast, Gilson et al. [45] found no change in the
time spent being sedentary. This might be due to the fact
that Gilson et al. [45] assessed use of the workstations for
only 1 week, while the other research groups assessed their
use for 4 weeks to 3 months [42, 43, 46]. In terms of
health, Alkhajah et al. [42] found an increase in high-
density lipoprotein (HDL) cholesterol, and Pronk
et al. [43] reported reduced pain in the upper back and
neck. In the study by Pronk et al. [43], people also reported
a positive effect on perceived comfort, energy, health,
focus, productivity, happiness, stress and mood states in
general. However, Alkhajah et al. [42] found no changes in
self-reported health and work performance. These contra-
dictory findings could be due to the use of different
surveys.
John et al. [47] and Koepp et al. [48] found that the
time spent being sedentary was reduced by the introduction
of walking workstations. Ben-Ner et al. [40] and Thomp-
son et al. [41, 44] confirmed this by reporting an increase
of 2,000 steps/day and an increase in energy expenditure of
about 74–197 kcal/day. The health benefits that were found
included reductions in hip and waist circumference [47],
weight loss [41, 48], a decrease in the body fat percentage
[41], and increased HDL [48], decreased low-density
lipoprotein (LDL) [47] and decreased total cholesterol [47].
Thompson et al. [
44] and Koepp et al. [48] studied the
effect on work performance and found no effect. However,
Ben-Ner et al. [40] found that work performance was
improved, on the basis of responses to survey questions.
They also found an improvement in the interactions
between co-workers. The differences in the findings of
these studies could be due to their use of different surveys.
The one study that investigated the effects of a portable
pedal exercise machine [38] reported that the provision of
these machines led to a decrease in the time spent being
sedentary.
Table 4 continued
Reference Sample Intervention Methodological
characteristics
Outcome
a
Remarks
Straker
et al. [58]
30 subjects (14 male); age
range 22–64 years; office
workers
Cycling
workstation
RCT; non-
longitudinal,
crossover
Slightly decreased computer task
performance; mouse
performance was more affected
than typing (assessed using
Typemaster Pro, WPM and error
rate)
Botter
et al. [39]
12 subjects (6 male); mean
(± SD) age
38.7 ± 11.4 years
Elliptical
machine
workstation
RCT; non-
longitudinal,
crossover
Slightly increased physical
activity; increased energy
expenditure (assessed using
CUELA system); increased heart
rate
Hasegawa
et al. [60]
8 subjects in condition A,
8 subjects in condition B
(male); age range
19–25 years
Standing
workstation
RCT; non-
longitudinal,
crossover
Lower perceived workload (CFF
and subjective feelings of
fatigue); higher work
performance (multiplication of
one-digit numbers)
AWPM adjusted words per minute, BMI body mass index, BW body weight, CFF critical flicker fusion frequency, CGM continuous glucose
monitoring, GRE graduate record examination, HDL high-density lipoprotein, HF high-frequency (0.15–0.4 Hz) components of heart rate
variability, LDL low-density lipoprotein, LF low-frequency (0.04–0.15 Hz) components of heart rate variability, nRCT non-randomized con-
trolled trial, nRnCT non-randomized non-controlled trial, OSPAQ Occupational Sitting and Physical Activity Questionnaire, POMS Profile of
Mood States, RCT randomized controlled trial, RPE rate of perceived exertion, SD standard deviation, VAS Visual Analogue Scale, VAMS -
Visual Analogue Mood Scales, WPM words per minute, WSQ Workforce Sitting Questionnaire
a
All data in the ‘Outcome’ column are mean values
1270 T. Torbeyns et al.
123
Although it seems from the aforementioned studies that
active workstations have a positive effect on several health
parameters and no detrimental effect on work performance,
it is not always easy to compare them, because of differ-
ences in the study populations, measurement methods and
durations of the interventions. For example, no consistent
methods for reporting age were used. Some authors
reported mean ages with standard deviations, while others
reported age ranges.
4.2.2 Non-longitudinal Studies
Hasegawa et al. [60] found that people using a standing
workstation had greater work performance and reported a
lower perceived workload. In contrast, Ebara et al. [50]
and Hedge et al. [51] did not find any differences in work
performance. This could be due to the use of a different
method to assess work performance, as Hasegawa
et al. [60] used a multiplication of one-digit number test,
while Ebara et al. [50] and Hedge et al. [51] used a tran-
scription test. Ebara et al. [50] reported that their study
participants had increased alertness. Some studies reported
greater musculoskeletal discomfort when using the stand-
ing desk [49–51], and Buckley et al. [61] reported 43 %
attenuated blood glucose excursion when standing. Speck
and Schmitz [63] did not find any differences in energy
expenditure between use of the standing workstation and
sitting. This is contradictory to the findings of Reiff
et al. [52] and Buckley et al. [61], which included average
increases in energy expenditure of 0.34 and 0.83 kcal/min,
respectively. This could perhaps have been due to differ-
ences in the duration of the measurements. Speck and
Schmitz [63] measured energy expenditure for only 7 min,
whereas in the other studies it was measured for at least
45 min [52, 61].
Use of a walking workstation increased energy expen-
diture from an extra 100 to 405 kcal/h [37, 39, 54, 59, 62].
In some studies, decreased computer task performance was
reported [55, 56, 58]. Both typing and mouse clicking
performance were affected, although, according to Straker
et al. [58], mouse clicking was more affected than typing.
However, Thompson and Levine [59] did not find any
effect on the accuracy of transcription, perhaps because
their subjects were experienced medical transcriptionists.
Funk et al. [55] found decreased typing performance in
general but not when subjects walked at 2.2 km/h. Ohlin-
ger et al. [57] observed decreased performance of a simple
motor task (a digital finger tapping test) when it was
combined with walking. The latter decrease in performance
might be explained by the fact that acute performance was
measured. Probably, an adaptation period is needed for
users to be able to return to their initial level of
performance.
Three studies [
53, 56, 57] investigated the acute effect
of a walking workstation on cognitive tasks. They found no
effects on selective attention and processing speed (asses-
sed by a Stroop test and a modified flanker task) [53, 56,
57], divided attention and short-term auditory verbal
memory (assessed by an auditory consonant trigram test)
[57] and reading comprehension [53, 56]. John et al. [56]
reported that only mathematics tests were negatively
influenced by use of a walking workstation. So far, only the
acute effect of this so-called enriched environment has
been measured. It would thus be of interest to see whether
there would be a different, maybe more positive effect of
longitudinal use of active workstations.
The only study that evaluated a portable stepping device
reported increased energy expenditure (?289 kcal/h),
similar to treadmill walking [37]. The study that evaluated
an elliptical machine workstation also reported increased
energy expenditure [39]. With regard to cycling worksta-
tions, only one cross-sectional study was found. Straker
et al. [58] reported slightly decreased computer task per-
formance (mouse clicking was more affected than typing)
during cycling compared with sitting. However, this
decrease in performance was smaller than when walking.
With regard to the non-longitudinal studies as well, it is
not always easy to compare them because of their different
populations and measurement methods. For example, no
consistent methods for reporting age were used. Some
authors reported mean ages with standard deviations,
whereas others reported age ranges. Also, the detrimental
effects of using walking and cycling workstations on
computer task performance has to be interpreted cautiously
because in the aforementioned studies, acute effects rather
than chronic effects were examined.
5 Conclusion
Our aim was to review the existing knowledge of the
implementation of active workstations.
From this systematic literature study, we can conclude
that studies that have evaluated active workstations have
mainly been performed in adults. Only a few studies, using
standing workstations, have been performed in elementary
school children. In all longitudinal interventions, the sub-
jects had freedom of choice to use the workstation, and so
no minimum amount of time for using the workstation was
set. Nevertheless, behavioural changes were found, which
means that people are willing to use active workstations.
The main outcomes that were investigated in the
reviewed studies were the effects of introducing the active
workstation on sitting time, energy expenditure, several
health markers, cognitive function, computer task perfor-
mance and work performance (productivity). In the
Active Workstations 1271
123
longitudinal studies, positive influences of the introduction
of active workstations on sitting time, energy expenditure
and health were found. For work performance, which was
investigated only in studies of walking workstations, no
effect was found. In the non-longitudinal studies, the
effects on energy expenditure and computer task perfor-
mance depended on the type of workstation that was used.
There was no effect on cognitive function. Only perfor-
mance on a mathematics test was negatively influenced.
On the basis of the existing literature, we can conclude
that the implementation of active workstations has major
positive influences on health-related aspects, such as
energy expenditure, fat percentage, waist circumference,
HDL, etc., and thus could possibly contribute to improving
people’s health and physical activity levels and to
decreasing their time spent sitting. The effect of longitu-
dinal use of these active workstations on cognition and
applied work tasks, such as computer task performance,
needs further investigation before conclusions can be
drawn. Another aspect that needs further investigation is
the implementation of the different types of active work-
stations in all age groups.
Acknowledgments No sources of funding were used in the prepa-
ration of this review. The authors have no potential conflicts of
interest that are directly relevant to the content of this review.
References
1. World Health Organisation. Health topics: physical activity;
2014. http://www.who.int/topics/physical_activity/en/. Accessed
21 Feb 2014.
2. National Institutes of Health. What is physical activity? 2011.
http://www.nhlbi.nih.gov/health/health-topics/topics/phys/.Acces-
sed 28 Feb 2014.
3. Dishman RK, Berthoud H, Booth FW. Neurobiology of exercise.
Obesity. 2006;14(3):345–56.
4. World Health Organization. Global recommendations on physical
activity for health. 2010 contract no.: ISBN 978 92 4 159 997 9.
5. Pedersen SJ, Cooley PD, Mainsbridge C. An e-health intervention
designed to increase workday energy expenditure by reducing
prolonged occupational sitting habits. Work. 2013;. doi:10.3233/
WOR-131644.
6. van Praag H. Neurogenesis and exercise: past and future direc-
tions. Neuromol Med. 2008;10(2):128–40. doi:10.1007/s12017-
008-8028-z.
7. Donnelly JE, Lambourne K. Classroom-based physical activity,
cognition, and academic achievement. Prev Med. 2011;52(Suppl
1):S36–42. doi:10.1016/j.ypmed.2011.01.021.
8. van den Heuvel SG, Boshuizen HC, Hildebrandt VH, et al. Effect
of sporting activity on absenteeism in a working population. Br J
Sports Med. 2005;39(3):e15. doi:10.1136/bjsm.2004.013052.
9. Brown HE, Gilson ND, Burton NW. Does physical activity
impact on presenteeism and other indicators of workplace well-
being? Sports Med. 2011;41(3):249–62.
10. Laurin D, Verreault R, Lindsay J, et al. Physical activity and risk
of cognitive impairment and dementia in elderly persons. Arch
Neurol. 2001;58:498–504.
11. Tak E, Kuiper R, Chorus A, et al. Prevention of onset and pro-
gression of basic ADL disability by physical activity in com-
munity dwelling older adults: a meta-analysis. Ageing Res Rev.
2013;12(1):329–38. doi:10.1016/j.arr.2012.10.001.
12. World Health Organization. Prevalence of insufficient physical
activity; 2008. http://www.who.int/gho/ncd/risk_factors/physi
cal_activity/en/. Accessed 17 Oct 2013.
13. Cadilhac DA, Cumming TB, Sheppard L, et al. The economic
benefits of reducing physical inactivity: an Australian example.
Int J Behav Nutr Phys Act. 2011;8:99. doi:10.1186/1479-5868-8-
99.
14. Allender S, Foster C, Scarborough P, et al. The burden of
physical activity-related ill health in the UK. J Epidemiol Com-
munity Health. 2007;61(4):344–8. doi:10.1136/jech.2006.
050807.
15. Sedentary Behaviour Research Network. Standardized use of the
terms ‘‘sedentary’’ and ‘‘sedentary behaviours’’. Appl Physiol
Nutr Metab. 2012;37:540–2.
16. Marshall SJ, Ramirez E. Reducing sedentary behavior: a new
paradigm in physical activity promotion. Am J Lifestyle Med.
2011;5(6):518–30. doi:10.1177/1559827610395487.
17. Plotnikoff R, Karunamuni N. Reducing sitting time: the new
workplace health priority. Arch Environ Occup Health.
2012;67(3):125–7. doi:10.1080/19338244.2012.697407.
18. Eurobarometer. Sport and physical activity; 2010.
19. British Heart Foundation. Physical activity statistics 2012. Fac-
tors influencing physical activity, chap. 6; 2012.
20. Oja P, Bull FC, Fogelholm M, et al. Physical activity recom-
mendations for health: what should Europe do? BMC Public
Health. 2010;10:10. doi:10.1186/1471-2458-10-10.
21. de Geus B, Van Hoof E, Aerts I, et al. Cycling to work: influence
on indexes of health in untrained men and women in Flanders.
Coronary heart disease and quality of life. Scand J Med Sci
Sports. 2008;18(4):498–510.
22. Liberati A, Altman DG, Tetzlaff J. The PRISMA statement for
reporting systematic reviews and meta-analyses of studies that
evaluate health care interventions: explanation and elaboration.
PLoS Med. 2009;6(7).
23. Scottish Intercollegiate Guidelines Network. Critical appraisal:
notes and checklists. http://www.sign.ac.uk/methodology/check
lists.html. Accessed 23 Sept 2013.
24. Effective Public Health Practice Project. Quality assessment tool
for quantitative studies; 2010. http://www.ephpp.ca/PDF/Qual
ity%20Assessment%20Tool_2010_2.pdf. Accessed 8 Oct 2013.
25. Straker L, Abbott RA, Heiden M, et al. Sit-stand desks in call
centres: associations of use and ergonomics awareness with
sedentary behavior. Appl Ergon. 2013;44(4):517–22. doi:10.
1016/j.apergo.2012.11.001.
26. Wilks S, Mortimer M, Nylen P. The introduction of sit-stand
worktables; aspects of attitudes, compliance and satisfaction.
Appl Ergon. 2006;37(3):359–65. doi:
10.1016/j.apergo.2005.06.
007.
27. Burford EM, Botter J, Commissaris D. The effect of dynamic
workstations on the performance of various computer and office-
based tasks. In: Duffy VG, editor. Digital human modeling and
applications in health, safety, ergonomics, and risk management.
Human Body Modeling and Ergonomics, Lecture Notes in
Computer Science, vol. 8026. Berlin: Springer; 2013. p. 205–12.
28. Dunstan DW, Wiesner G, Eakin EG, et al. Reducing office
workers’ sitting time: rationale and study design for the Stand Up
Victoria cluster randomized trial. BMC Public Health.
2013;13:1057.
29. Cardon G, De Clercq D, De Bourdeaudhuij I, et al. Sitting habits
in elementary schoolchildren: a traditional versus a ‘‘Moving
school’’. Patient Educ Couns. 2004;54(2):133–42. doi:10.1016/
s0738-3991(03)00215-5.
1272 T. Torbeyns et al.
123
30. Robertson MM, Ciriello VM, Garabet AM. Office ergonomics
training and a sit-stand workstation: effects on musculoskeletal
and visual symptoms and performance of office workers. Appl
Ergon. 2013;44(1):73–85. doi:10.1016/j.apergo.2012.05.001.
31. Lytle TL, Wenos DL, Ritttenhouse MA. The effects of the
walking workstation on work productivity and selected physio-
logical variables; 2011.
32. Benden ME, Blake JJ, Wendel ML. The impact of stand-biased
desks in classrooms on calorie expenditure in children. Am J
Public Health. 2011;101(8):1433–6.
33. Blake JJ, Benden ME, Wendel ML. Using stand/sit workstations
in classrooms: lessons learned from a pilot study in Texas.
J Public Health Manag Pract. 2012;18(5):412–5. doi:10.1097/
PHH.0b013e3182215048.
34. Hinckson EA, Aminian S, Ikeda E, et al. Acceptability of
standing workstations in elementary schools: a pilot study. Prev
Med. 2013;56(1):82–5. doi:10.1016/j.ypmed.2012.10.014.
35. Lanningham-Foster L, Foster RC, McCrady SK, et al. Changing
the school environment to increase physical activity in children.
Obesity. 2008;16(8):1849–53. doi:10.1038/oby.2008.282.
36. Koepp GA, Snedden BJ, Flynn L, et al. Feasibility analysis of
standing desks for sixth graders. Infant Child Adolesc Nutr.
2012;4(2):89–92. doi:10.1177/1941406412439414.
37. McAlpine DA, Manohar CU, McCrady SK. An office-place
stepping device to promote workplace physical activity. Br J
Sports Med. 2007;41:903–7.
38. Carr LJ, Walaska KA, Marcus BH. Feasibility of a portable pedal
exercise machine for reducing sedentary time in the workplace.
Br J Sports Med. 2012;46(6):430–5. doi:10.1136/bjsm.2010.
079574.
39. Botter J, Burford EM, Commissaris D. The biomechanical and
physiological effect of two dynamic workstations. In: Duffy VG,
editor. Digital human modeling and applications in health, safety,
ergonomics, and risk management. Human body modeling and
ergonomics. Berlin: Springer; 2013. p. 196–204.
40. Ben-Ner A, Paulson DF, Koepp GA. Treadmill workstations: the
effects of walking while working on physical activity and work
performance. PLoS ONE. 2014;9(2):e88620.
41. Thompson WG, Koepp GA, Levine JA. Increasing physician
activity with treadmill desks. Work. 2013 (Epub ahead of print).
42. Alkhajah TA, Reeves MM, Eakin EG, et al. Sit-stand worksta-
tions: a pilot intervention to reduce office sitting time. Am J Prev
Med. 2012;43(3):298–303. doi:10.1016/j.amepre.2012.05.027.
43. Pronk NP, Katz AS, Lowry M. Reducing occupational sitting
time and improving worker health: the take-a-stand project, 2011.
Prev Chronic Dis. 2012;9:110323.
44. Thompson WG, Foster RC, Eide DS et al. Feasibility of a
walking workstation to increase daily walking. Br J Sports Med.
2008;42(3):225–8 (discussion 228). doi:10.1136/bjsm.2007.
039479.
45. Gilson ND, Suppini A, Ryde GC, et al. Does the use of standing
‘hot’ desks change sedentary work time in an open plan office?
Prev Med. 2012;54(1):65–7. doi:10.1016/j.ypmed.2011.10.012.
46. Grunseit AC, Chau JY, van der Ploeg HP. ‘‘Thinking on your
feet’’: a qualitative evaluation of sit-stand desks in an Australian
workplace. BMC Public Health. 2013;13:365–75.
47. John D, Thompson DL, Raynor H. Treadmill workstations: a
worksite physical activity intervention in overweight and obese
office workers. J Phys Act Health. 2011;8(8):1034–43.
48. Koepp GA, Manohar CU, McCrady-Spitzer SK, et al. Treadmill
desks: a 1-year prospective trial. Obesity. 2013;21(4):705–11.
doi:10.1002/oby.20121.
49. Chester MR, Rys MJ, Konz SA. Leg swelling, comfort and
fatigue when sitting, standing and sit/standing. Int J Ind Ergon.
2002;29:289–96.
50. Ebara T, Kubo T, Inoue T. Effects of adjustable sit-stand VDT
workstations on workers’ musculoskeletal discomfort, alertness
and performance. Ind Health. 2008;46:497–505.
51. Hedge A, Jagdeo J, Agarwal A, et al. Sitting or standing for
computer work—does a negative-tilt keyboard tray make a dif-
ference? Proc Hum Fact Ergon Soc Annu Meet.
2005;49(8):808–11. doi:10.1177/154193120504900804.
52. Reiff C, Marlatt K, Dengel DR. Difference in caloric expenditure
in sitting versus standing desks. J Phys Act Health.
2012;9:1009–11.
53. Alderman BL, Olson RL, Mattina DM. Cognitive function during
low intensity walking: a test of the treadmill workstation. J Phys
Act Health. 2013.
54. Cox RH, Guth J, Siekemeyer L. Metabolic cost and speech
quality while using an active workstation. J Phys Act Health.
2011;8(3):332–9.
55. Funk RE, Taylor ML, Creekmur CC. Effect of walking speed on
typing performance using an active workstation. Percept Motor
Skills. 2012;115(1):309–18.
56. John D, Bassett DR, Thompson DL, et al. Effect of using a
treadmill workstation on performance of simulated office work
tasks. J Phys Act Health. 2009;6(5):617–24.
57. Ohlinger SA, Horn TS, Berg WP, et al. The effect of active
workstation use on measures of cognition, attention, and motor
skill. J Phys Act Health. 2011;8(1):119–25.
58. Straker L, Levine J, Campbell A. The effects of walking and
cycling computer workstations on keyboard and mouse perfor-
mance. Hum Factors. 2009;51(6):44.
59. Thompson WG, Levine JA. Productivity of transcriptionists using
a treadmill desk. Work. 2011;40(4):473–7. doi:
10.3233/WOR-
2011-1258.
60. Hasegawa T, Inoue K, Tsutsue O. Effects of a sit-stand schedule
on a light repetitive task. Int J Ind Ergon. 2001;28:219–24.
61. Buckley JP, Mellor DD, Morris M, et al. Standing-based office
work shows encouraging signs of attenuating post-prandial gly-
caemic excursion. Occup Environ Med. 2014;71(2):109–11.
62. Levine JA, Miller JM. The energy expenditure of using a ‘‘walk-
and-work’’ desk for office workers with obesity. Br J Sports Med.
2007;41(9):558–61. doi:10.1136/bjsm.2006.032755.
63. Speck RM, Schmitz KH. Energy expenditure comparison: a pilot
study of standing instead of sitting at work for obesity prevention.
Prev Med. 2011;52(3–4):283–4. doi:10.1016/j.ypmed.2011.02.
002.
64. Hillman CH, Erickson KI, Kramer AF. Be smart, exercise your
heart: exercise effects on brain and cognition. Nat Rev Neurosci.
2008;9:58–65.
65. Hillman CH, Kamijo K, Scudder M. A review of chronic and
acute physical activity participation on neuroelectric measures of
brain health and cognition during childhood. Prev Med.
2011;52:521–8.
Active Workstations 1273
123
