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International Journal of
Environmental Research
and Public Health
Review
The Impact of Active Workstations on Workplace
Productivity and Performance: A Systematic Review
Samson O. Ojo 1, Daniel P. Bailey 2ID , Angel M. Chater 2and David J. Hewson 1 ,*ID
1
Institute for Health Research, University of Bedfordshire, Luton LU1 3JU, UK; samson.ojo@study.beds.ac.uk
2Institute for Sport and Physical Activity Research, School of Sport Science and Physical Activity,
University of Bedfordshire, Bedford MK41 9EA, UK; Daniel.Bailey@beds.ac.uk (D.P.B.);
Angel.chater@beds.ac.uk (A.M.C.)
*Correspondence: david.hewson@beds.ac.uk; Tel.: +44-7525-616-645
Received: 22 December 2017; Accepted: 21 February 2018; Published: 27 February 2018
Abstract:
Active workstations have been recommended for reducing sedentary behavior in the
workplace. It is important to understand if the use of these workstations has an impact on worker
productivity. The aim of this systematic review was to examine the effect of active workstations
on workplace productivity and performance. A total of 3303 articles were initially identified by a
systematic search and seven articles met eligibility criteria for inclusion. A quality appraisal was
conducted to assess risk of bias, confounding, internal and external validity, and reporting. Most of the
studies reported cognitive performance as opposed to productivity. Five studies assessed cognitive
performance during use of an active workstation, usually in a single session. Sit-stand desks had no
detrimental effect on performance, however, some studies with treadmill and cycling workstations
identified potential decreases in performance. Many of the studies lacked the power required to
achieve statistical significance. Three studies assessed workplace productivity after prolonged use of
an active workstation for between 12 and 52 weeks. These studies reported no significant effect on
productivity. Active workstations do not appear to decrease workplace performance.
Keywords:
sedentary behavior; physical activity; sit-stand; active workstation; treadmill desk;
productivity; performance
1. Introduction
Sedentary behavior can be defined as “any waking behavior characterized by an energy
expenditure
≤
1.5 metabolic equivalents (METs), while in a sitting, reclining or lying posture” ([
1
], p. 9).
Epidemiological studies have revealed that excessive time spent sitting can increase the likelihood of
many health outcomes, including type 2 diabetes, cardiovascular disease, cancer, obesity, and all-cause
mortality [
2
–
4
]. This is usually regardless of the amount of time spent in moderate-to-vigorous
physical activity [
2
,
5
]. Office workers are at increased risk as they spend more than half of their
workday sitting [
6
,
7
]. In one study, office based employees spent 82% of working hours and 69% of
non-work hours engaged in sedentary behavior [8].
Increasing evidence has shown that sedentary behavior in the workplace can be curtailed by
making changes to the work environment, such as the introduction of active workstations [
9
]. An active
workstation enables people to incorporate physical activity into a sedentary task, and can include
different types of activity such as walking on a treadmill, pedaling a stationary bicycle, using an
elliptical trainer, or simply standing at a height-adjustable desk [
10
]. For instance, a pilot study
replaced “stationary sitting desks” with “sit-stand workstations” to allow office workers the option
to alternate between sitting and standing [
11
]. After one week, the intervention group significantly
decreased their sitting time by 143 min per day compared with the control group [
11
]. A similar study
Int. J. Environ. Res. Public Health 2018,15, 417; doi:10.3390/ijerph15030417 www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2018,15, 417 2 of 14
using treadmill desks reported a significant 9% reduction in sedentary time by over 90 min at the
end of a six month intervention, but this effect declined to 43 min at 12 months post-intervention [
12
].
In contrast, during a two-week intervention, the adoption of standing ‘hot’ desks in an open plan
office in which office workers were encouraged to stand as often as possible whilst working did not
change employees’ sitting time [
13
]. Portable pedal machines have also been used to increase activity
while sitting, which is termed “active sitting” and one study reported a 60 min per day reduction in
sedentary time at the end of a three-month intervention [
14
]. These studies suggest that sitting time
can be reduced in the workplace using active workstations.
While the initiatives outlined above appear to be effective in reducing sitting time, there has
been limited research regarding the effect of active workstations on performance and productivity
variables [
15
]. There is a need, therefore, to investigate the effect of active workstations on productivity
and performance to identify their suitability for use in the workplace. The term performance, which is
often used interchangeably with productivity, is sometimes described as an umbrella terminology for
every concept that determines how successful companies are [
16
]. Performance can also be defined
as “the proficiency with which individuals perform the core substantive or technical tasks central
to their job” ([
17
], p. 610). In the present study, performance refers to the efficiency of employees
in tasks central to their office work including, but not limited to, data entry, reading and browsing.
The term productivity is defined in this review as the quality or state of yielding large result or yielding
abundantly, which is often determined by the ratio of output to input [
16
]. It is inherently complex to
determine the productivity of office workers as their activities vary widely, including both repetitive
tasks and creativity, depending on the job requirements. For the purposes of this review, worker
productivity will include evaluations of work output, as well as evaluations of cognitive function that
could be required to carry out office-related tasks [18].
The evidence regarding the effect of active workstations on productivity and performance is
equivocal [
19
]. For instance, in one study in which sit-stand workstations were used, office workers
were reported to feel more productive, energized, and focused [
7
]. In contrast, small non-significant
reductions in data entry efficiency and accuracy for a data entry task were found among male university
students while standing, when compared to sitting [
20
]. However, in such studies using simulated
workspaces, it is debatable whether the results are applicable to a real office environment. In other
studies involving the use of a treadmill desk, walking was identified as a hindrance to mouse-related
tasks such as typing, possibly due to such tasks requiring a steady posture and the use of hands for
precise execution [
21
,
22
]. Given the inconsistency in the current research findings, most managers
might be reluctant to implement active workstations in the workplace. It has been suggested in one
study that it would be very unlikely for organizational management to institute the use of treadmill
desks if productivity is harmed [
23
]. This uncertainty reinforces the need for further investigation of the
effect of active workstations on productivity and performance of workers. The aim of this systematic
review was therefore to examine literature investigating the effect of using active workstations on
productivity and workplace performance.
2. Materials and Methods
2.1. Data Sources and Study Selection
Ethical approval for the systematic review protocol was obtained from the Institute for Health
Research Ethics Committee at the University of Bedfordshire on the 28 April 2016 (IHREC611).
A systematic literature search was carried out to identify relevant studies. The searched databases were
PsycInfo, SPORTDiscus, Web of Science, and PubMed for studies published between January 2005 and
December 2016. The 2005 cut-off was chosen as very little literature on active workstations exists before
this date. The search terms included “active workstation,” “sit-stand desk” “treadmill workstation”,
“treadmill desk”, “workplace”, “work setting”, “productivity” and “performance”. Duplicates were
removed before two reviewers (SO and DH) independently screenedtitles and abstracts of all identified
Int. J. Environ. Res. Public Health 2018,15, 417 3 of 14
articles. Only studies that were published in peer-reviewed journals were included. Additional relevant
studies were sourced manually from the reference lists of the retrieved articles. Studies were eligible
for inclusion if they met the criteria stated in Table 1, using the PICO (T) framework [
24
]. The PRISMA
four-phased flow diagram was used in summarizing the study selection processes [25].
Table 1. Inclusion and exclusion criteria.
Term Inclusion Description Exclusion Description
Population Healthy, working age, adult
employees (≥18 years old) from
developed countries
Studies where recruited participants have specific
comorbidities or diseases (such as diabetes, arthritis, cancer,
stroke), special populations (pregnant, physical disability, or
cognitive disability), or targeted pain management or
musculoskeletal issues
Non-employees (students) in an office-simulated environment
Intervention
Use of workstations such as
sit-stand desk, treadmill desk;
cycling desk
Not office based, not workstations
Comparison
Any comparative study with
either baseline measures or
non-intervention group as control
for comparison.
No comparison measures
Outcomes
Productivity or work performance
No measure of productivity or work performance
Trial design Randomized controlled trials or
quasi-experimental trials Observational studies
2.2. Quality Appraisal
The methodological quality of the selected articles was independently assessed by two reviewers
(Samson Ojo and Daniel Bailey). Disagreements were resolved with scores from a third reviewer
(David Hewson). Eligible studies were assessed with a modified version of the Downs and Black
checklist [
26
] for reporting, internal validity-confounding, internal validity-bias and external validity.
The original checklist contains 27 questions, but four questions were considered inapplicable, three of
which related to blinding and concealment, which are not relevant in active workstation interventions.
A question related to determining power was also omitted. Downs and Black assign two point
compliance criteria, giving a maximal score of 24, with the cut-off for inclusion set to 12.
2.3. Extraction and Management of Data
Authors of included studies with missing or incomplete data were contacted by email to retrieve
further information. In studies where effect sizes were not provided, Cohen’s d, otherwise known as
the Standardized Mean Difference (SMD), was calculated to determine the effect of the intervention on
performance and productivity. The SMD is calculated by dividing the mean difference by the pooled
standard deviation [
27
]. The scale proposed by Hopkins and colleagues was used to describe the
magnitude of the SMD observed [
28
]. This scale describes effects as “trivial” (<0.2), “small” (
0.2 ≤0.6
),
“moderate” (0.6
≤
1.2), “large” (1.2
≤
2.0) or “very large” (
≥
2.0). Effect sizes were expressed as
negative to indicate decreased performance, irrespective of the direction of the effect. For instance, an
increased error rate for a task corresponded to a negative effect size, whereas an increased word count
when typing would have given a positive effect size. All reported effect sizes are in comparison with
the control or baseline condition.
3. Results
3.1. Article Selection
A flow chart of the selection process is shown in Figure 1. The initial search identified a total
of 3303 articles, which was reduced to 1826 after duplicates were removed. The titles and abstracts
Int. J. Environ. Res. Public Health 2018,15, 417 4 of 14
of the remaining articles were screened against the inclusion criteria, with 1796 articles excluded
for reasons including relevance, the population studied, and being an exercise or physical activity
intervention rather than an intervention targeting sedentary behavior. Twenty articles were identified
as potentially relevant and assessed for eligibility. Thirteen articles were rejected after full-text screening
as some of these studies did not report effect sizes or data to calculate effect size, and six studies
used students working in simulated office environments. The resulting sample consisted of seven
articles, with no additional studies identified following a search through the references of the included
articles [12,29–40].
3.2. Study Characteristics
All included studies used office workers as participants [
12
,
31
,
32
,
34
,
37
,
38
,
40
]. The articles contained
three different intervention types including treadmill desks [
12
,
37
], cycling workstations
[34,40]
, and
sit-stand workstations
[31,32,37,38]
. A total of 16 different productivity and work performance
outcomes were identified. To this end, it was deemed that a meta-analysis would not be appropriate
given the diversity of the outcome measures and study designs. Detailed characteristics of the selected
studies including quality appraisal scores are shown in Table 2. Six of the studies reported details of
ethical approval. The authors of the remaining study were contacted by email and confirmed details of
their ethical approval.
3.3. Cognitive Performance: A Measure of Productivity
The majority of studies presented cognitive performance as outcome measures for productivity.
Cognitive performance was assessed in five of seven studies using a variety of tests [
32
,
34
,
37
,
38
,
40
].
These tests have been classified into the following categories depending on the element of cognitive
function being assessed: attention, memory, and reasoning. All cognitive function changes were made
in comparison to a control condition of sitting.
3.3.1. Attention
Three studies assessed attention responses when using active workstations (either treadmill,
cycling or sit-stand desks) [
37
,
38
,
40
], with the results shown in Table 3. With respect to standing
workstations, all differences observed were trivial. When participants used a cycling workstation,
there were 12 different attention tests used, with most of these showing no difference in attention, or a
small improvement [
40
]. Only one test of attention was reported while walking using a treadmill desk
with a trivial increase in attention reported when compared with sitting [37].
3.3.2. Memory
Three studies examined memory performance in response to active workstation use with results
shown in Table 4[
37
,
38
,
40
]. In two studies, a trivial increase in memory performance was observed
using both a sit-stand workstation and treadmill desk [
37
,
38
]. However, in the remaining study,
memory performance was decreased when using a cycling workstation [40]. The decreases observed
in this study were trivial, regardless of the component of the auditory verbal learning test used, but
none of these differences were statistically significant.
3.3.3. Reasoning and Reaction Time
One study investigated reasoning responses [
34
] and another reaction times [
38
], with the results
of both studies shown in Table 5. None of the differences in reasoning responses between a cycling
workstation and sitting were significant. No significant differences in reaction time were found when
using a sit-stand workstation, compared to sitting.
Int. J. Environ. Res. Public Health 2018,15, 417 5 of 14
Int.J.Environ.Res.PublicHealth2017,14,xFORPEERREVIEW 5of15
Figure1.PreferredReportingItemsforSystematicReviewandMeta‐Analyses(PRISMA)flowchart
ofstudyselection[41].
3.4.Work‐RelatedPerformance
Twodifferenttypesofwork‐relatedperformance(typingandproofreadingtask)wereassessed.
Theresultsofusingactiveworkstationsonwork‐relatedperformancetestsareshowninTable6.Two
studiesexaminedtheeffectofusingacyclingworkstationontypingperformance[34,40]andone
studyevaluatedproofreadingperformancewhenusingasit‐standdesk[35].Withrespecttotyping,
theonlysignificantchangesreportedwereinthestudybyKorenetal.[34],inwhichasmalldecrease
inperformancewasobserved.However,onlyatrivialdecreaseinperformancewasreportedby
Torbynesetal.[40].Trivialincreaseswererecordedfortheproofreadingperformance,althoughno
significantdifferencewasobserved[38].
3.5.ProductivityafterProlongedUseofActiveWorkstations
Threestudiesassessedworkplaceproductivityafterprolongeduseofsit‐standworkstations
[12,31,32]throughtheuseoftheBrickencampd2testtoexamineconcentrationperformance[32],
monitoringaveragecallhandlingtime,holdtimeonacall,talktimeandwrapuptimeonacall[31],
andthroughemployee‐andsupervisor‐ratedperformance[12].InthestudybyDonathetal.[32],
participantsusedtheworkstationfor12weeks,whileChauetal.[31]assessedproductivityafter19
weeksofuse,andKoeppetal.[12]afteroneyear.Theresultsobtainedfromallthreestudiesare
showninTable7.Nosignificantdifferenceswereobservedinresponsetoanyoftheinterventions,
althoughsomeoftheoutcomesmeasureddidhavemoderatechangesinproductivity.
Figure 1.
Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) flow chart of
study selection [41].
3.4. Work-Related Performance
Two different types of work-related performance (typing and proof reading task) were assessed.
The results of using active workstations on work-related performance tests are shown in Table 6.
Two studies examined the effect of using a cycling workstation on typing performance [
34
,
40
] and
one study evaluated proofreading performance when using a sit-stand desk [
35
]. With respect to
typing, the only significant changes reported were in the study by Koren et al. [
34
], in which a small
decrease in performance was observed. However, only a trivial decrease in performance was reported
by Torbynes et al. [
40
]. Trivial increases were recorded for the proof reading performance, although no
significant difference was observed [38].
3.5. Productivity after Prolonged Use of Active Workstations
Three studies assessed workplace productivity after prolonged use of sit-stand workstations
[12,31,32]
through the use of the Brickencamp d2 test to examine concentration performance [
32
], monitoring
average call handling time, hold time on a call, talk time and wrap up time on a call [
31
], and through
employee- and supervisor-rated performance [
12
]. In the study by Donath et al. [
32
], participants
used the workstation for 12 weeks, while Chau et al. [31] assessed productivity after 19 weeks of use,
and Koepp et al. [
12
] after one year. The results obtained from all three studies are shown in Table 7.
No significant differences were observed in response to any of the interventions, although some of the
outcomes measured did have moderate changes in productivity.
Int. J. Environ. Res. Public Health 2018,15, 417 6 of 14
Table 2. Characteristics of the selected articles.
Authors Participants Study Design and Intervention Performance Measures Quality (Max 24)
Chau et al. (2016) [31]
Australia
Call center staff
14 females, 17 males
33.0 ±10.8 years,
unspecified health status
BMI 26.8 ±5.5 kg/m2
Quasi-experimental trial
19-week intervention
Sit-stand workstations
Work performance
Call handling time
Time on call
Hold time on call
Wrap up time on call
Customer rating
13
Donath et al. (2015) [32]
Switzerland
23 females, 8 males
42.4 ±11.0 years,
Healthy office workers
BMI 24.2 ±4.4 kg/m2
Single-blinded RCT
12-week intervention
Sit-stand workstation
Cognition performance:
Attention (Brickenkamp d2) 19
Koepp et al. (2013) [12]
USA
25 females, 11 males
42 ±10 years, Office workers able to walk
at 3 mph for 30 min, not pregnant
BMI 29 ±7 kg/m2
Prospective trial
1-year intervention
Treadmill desk
Work performance
Employee-rated performance
Supervisor-rated performance
15
Koren et al. (2016) [34]
Slovenia
13 participants but no. of females and
males not specified
30.6 ±3.8 years, healthy office workers
BMI 21.2 ±12.0 kg/m2
Crossover design
30-min intervention with two
exercise intensities
Cycling workstation
Cognitive performance
Reasoning (Wonderlic test)
Work performance
Typing speed and error rate
17
Ohlinger et al. (2011) [37]
USA
Unreported no of females and males
43.2 ±9.3 years, university ≤150 kg,
walk unaided
BMI 28.5 ±5.9 kg/m2
Quasi-experimental trial
75-min intervention
Treadmill desk
Sit-stand workstation
Cognitive performance
Attention (Stroop)
Memory (Auditory Consonant Trigram)
14
Russell et al. (2015) [38]
Australia
26 females, 10 males
40.1 ±11.9 years, university employees
unreported health status
Unreported BMI
RCT
Two-week intervention
Sit-stand workstation
Cognitive performance
Attention (Stroop)
Memory (Digit Span)
Reaction Time (Digit Symbol Coding)
Work performance
Proof reading (speed and error rate)
17
Torbeyns et al. (2016) [40]
Belgium
16 females, 7 males
35.7 ±10.3 years, Healthy office workers
BMI 23.2 ±3.0 kg/m2
Quasi-experimental trial
30-min intervention
Cycling workstation
Cognitive performance
Attention (Stroop, Rosvold)
Memory (Rey Auditory Verbal Learning)
Work performance
Typing speed and error rate
17
Quality measured using modified Downs and Black checklist; Data reported to 1 significant figure where authors included sufficient precision. BMI: Body Mass Index.
Int. J. Environ. Res. Public Health 2018,15, 417 7 of 14
Table 3. Effect of active workstation use on attention.
Condition Author Performance Test nSMD Effect Size Magnitude
Standing
Ohlinger et al. (2011) [37] Stroop colour word test (T-score—number of correct items) 50 0.02 Trivial decrease
Russell et al. (2015) [38]Choice Reaction Time (ms) 36 0.06 Trivial increase
Choice Reaction Time accuracy (%) 36 0.02 Trivial increase
Stroop incongrunet (s) 36 0.06 Trivial decrease
Cycling Torbeyns et al., 2016 [40]Rosvold continuous performance test reaction time (ms) 23 0.73 Moderate increase *
Rosvold continuous performance test accuracy (%) 23 1.00 Moderate decrease
Stroop accuracy color congruent stimuli (%) 23 0.00 Trivial—no change
Stroop accuracy color incongruent stimuli (%) 23 0.06 Trivial decrease
Stroop accuracy neutral stimuli (%) 23 0.03 Trivial decrease
Stroop accuracy word congruent stimuli (%) 23 0.06 Trivial increase
Stroop accuracy word incongruent stimuli (%) 23 0.02 Trivial increase
Stroop reaction time color congruent stimuli (ms) 23 0.20 Small increase
Stroop reaction time color incongruent stimuli (ms) 23 0.09 Trivial increase
Stroop reaction time neutral stimuli (ms) 23 0.18 Trivial increase
Stroop reaction time word congruent stimuli (ms) 23 0.21 Small increase
Stroop reaction time word incongruent stimuli (ms) 23 0.34 Small increase
Walking Ohlinger et al., 2011 [37] Stroop color word test (T-score—number of correct items) 50 0.03 Trivial increase
* Significantly different from sitting condition. SMD: Standardized Mean Difference.
Table 4. Effect of active workstation use on memory.
Condition Author Performance Test nSMD Effect Size Magnitude
Standing
Ohlinger et al., 2011 [37] Auditory consonant trigram test (number of correct consonants) 50 0.11 Trivial increase
Russell et al., 2015 [38]Digit Span subtest—number correct backwards 36 0.11 Trivial increase
Digit Span subtest—number correct forwards 36 0.13 Trivial increase
Letter number sequencing test 36 0.19 Trivial increase
Cycling Torbeyns et al., 2016 [40]
Rey Auditory Verbal Learning Test (Correctly recognized words) 23 0.15 Trivial decrease
Rey Auditory Verbal Learning Test (Incorrectly recognized words)
23 0.00 Trivial—no change
Rey Auditory Verbal Learning Test (Recalled words) 23 0.13 Trivial decrease
Rey Auditory Verbal Learning Test (Repeated words) 23 0.12 Trivial increase
Walking Ohlinger et al., 2011 [37] Auditory consonant trigram test (number of correct consonants) 50 0.06 Trivial increase
Int. J. Environ. Res. Public Health 2018,15, 417 8 of 14
Table 5. Effect of active workstation use on reasoning and reaction time.
Condition Author Performance Test nSMD Effect Size Magnitude
Cycling Koren et al., 2016 [34]
Reasoning: Wonderlic test score (40 W workload) 13 0.13 Trivial increase
Reasoning: Wonderlic test score (80 W workload) 13 0.25 Small decrease
Reasoning: Wonderlic test time (s) (40 W workload)
13 0.05 Trivial decrease
Reasoning: Wonderlic test time (s) (80 W workload)
13 0.52 Small increase
Standing Russell et al. (2015) [38]Reaction time: Digit Symbol Coding subtest (total) 36 0.02 Trivial decrease
Reaction time: Trail making test (s) 36 0.09 Trivial decrease
Table 6. Effect of active workstation use on work-related performance tasks.
Condition Author Performance Test nSMD Effect Size Magnitude
Standing Russell et al. (2015) [38]Proof reading task (errors identified) 36 0.03 Trivial increase
Proof reading task (time) 36 0.11 Trivial increase
Cycling
Torbeyns et al. (2016) [40]Typing test (net words per min) 23 0.05 Trivial decrease
Typing time (s) (40 W workload) 13 0.51 Small decrease *
Koren et al. (2016) [34]
Typing time (s) (80 W workload) 13 0.58 Small decrease *
Typing errors (number) (40 W workload)
13 1.66 Large decrease
Typing errors (number) (80 W workload)
13 1.81 Large decrease
* Significantly different from sitting condition.
Int. J. Environ. Res. Public Health 2018,15, 417 9 of 14
Table 7. Effect of active workstation use on work-related productivity tasks.
Condition Author Performance Test Trial Duration nSMD Effect Size Magnitude
Standing
Donath et al. (2015) [32]
Brickencamp d2 test (% correct, 3 prompts/day) 12 weeks 15 0.37 Small increase
Brickencamp d2 test (net performance, 3 prompts/day) 12 weeks 15 0.46 Small increase
Brickencamp d2 test (% correct, no prompt) 12 weeks 16 0.45 Small increase
Brickencamp d2 test (net performance, no prompt)) 12 weeks 16 0.69 Moderate increase
Chau et al. (2016) [31]
Average call handling time (min) 19 weeks 16 0.33 Small decrease
Customer rating 19 weeks 16 0.16 Trivial increase
Hold time on call (min) 19 weeks 16 0.60 Moderate decrease
Talk time on call (min) 19 weeks 16 0.05 Trivial increase
Wrap up time on call (min) 19 weeks 16 0.20 Small increase
Walking Koepp et al. (2013) [12]
Employee-rated performance (weekly survey)—overall 1 year 23 0.04 Trivial decrease
Employee-rated performance (weekly survey)—overall 1 year 13 0.22 Trivial decrease
Employee-rated performance (weekly survey)—quality 1 year 13 0.05 Trivial increase
Employee-rated performance (weekly survey)—quality 1 year 23 0.37 Small decrease
Employee-rated performance (weekly survey)—quantity 1 year 23 0.13 Trivial decrease
Employee-rated performance (weekly survey)—quantity 1 year 13 0.24 Small increase
Employee-rated performance (weekly survey)—interaction 1 year 13 0.04 Trivial decrease
Employee-rated performance (weekly survey)—interaction 1 year 23 0.33 Small decrease
Supervisor-rated performance (weekly survey)—overall 1 year 23 0.35 Small decrease
Supervisor-rated performance (weekly survey)—overall 1 year 13 0.60 Moderate decrease
Supervisor-rated performance (weekly survey)—quality 1 year 13 0.15 Trivial decrease
Supervisor-rated performance (weekly survey)—quality 1 year 23 0.31 Small decrease
Supervisor-rated performance (weekly survey)—quantity 1 year 13 0.18 Trivial decrease
Supervisor-rated performance (weekly survey)—quantity 1 year 23 0.26 Small decrease
Supervisor-rated performance (weekly survey)—interaction 1 year 23 0.05 Trivial decrease
Supervisor-rated performance (weekly survey)—interaction 1 year 13 0.15 Trivial decrease
Brickencamp d2 test evaluates concentration.
Int. J. Environ. Res. Public Health 2018,15, 417 10 of 14
4. Discussion
The aim of this review was to determine whether using an active workstation had any effect
on productivity or workplace performance. The seven studies reviewed fell into two distinct
categories with respect to the methods used to assess both productivity and performance. Most of the
studies estimated productivity based on cognitive performance tests using laboratory-based and/or
simulated-office tasks as outcome measures, while work performance was estimated by typing and
proofreading. Four studies evaluated productivity and work-related performance while using an
active workstation, whereas the other three studies assessed workplace productivity after prolonged
use of active workstations.
The studies examining cognitive performance as a measure of productivity used a range of tests
to assess different elements of cognition, including attention, memory, reasoning, and reaction time.
With respect to attention, both of the studies reported only trivial effects when using a sit-stand
workstation [
37
,
38
]. Similar results were reported in the studies in which attention was measured
while using a cycling or walking workstation, with most tests producing trivial differences [
37
,
40
].
The results of the studies in which memory was assessed while using an active workstation followed
the same pattern with use of three types of workstations leading to trivial increases in memory that
were non-significant [37,38,40].
It appears that using a sit-stand workstation has no effect on productivity when the person is
standing, indicating that alternating between standing and sitting may not have any detrimental effect
on the amount and quality of work being produced. A lack of significantly different results were
observed for both cycling and walking workstations, which could be an indication that these two
workstations may not pose any threat to the quality of work produced, although it is worth noting
that several effects that could be considered moderate using the Hopkins’ scale were not detected
as statistically significant, perhaps owing to low power in the studies [
28
]. It should also be noted
that participants lacked familiarity with the active workstations used in most of the studies, so work
productivity and performance could be expected to improve with habitual use. It is also possible
that any potentially beneficial effects of long-term use of active workstations would not have been
observed given the short time in which participants used the workstations. It has been suggested
that using an active workstation could influence long-term performance and workplace productivity.
Only three studies assessed workplace productivity after prolonged use of active workstations, with
the duration of these studies ranging from 12–52 weeks [
12
,
31
,
32
]. None of these studies reported any
change in productivity after long-term use of an active workstation. However, as with the short-term
studies assessing productivity responses, two studies [
34
,
40
] had relatively low power but with effect
sizes as large as 1.8. This indicates a large effect that was not found to be statistically significant [
28
].
Future research in this area needs to be carried out with sufficient power to investigate the exact impact
of short-term use of active workstations on productivity.
Based on the findings of this review, it appears that there is insufficient evidence regarding the
effect of active workstations on productivity and workplace performance. The studies reviewed fell
into two categories and either focused on cognitive performance while using an active workstation
that participants were not familiar with, or they were long-duration studies in which productivity was
measured using simple tools such as self-rated questionnaires and call handling time. Future research
should investigate the effect of active workstations on productivity, making sure to use non-subjective
measures of productivity.
The potential of active workstations to reduce the amount of sedentary behavior in the workplace
was the focus of another recent systematic review. In this review, Chu and colleagues [
42
] reported
that sit-stand workstations were effective in reducing sitting time, although not as effective as
multi-component interventions. However, this review did not examine whether the use of active
workstations had any effect on productivity or workplace performance. In another systematic review,
MacEwen and colleagues [
43
] looked at the effect of sit-stand and treadmill desks on both physiological
and psychological outcomes. The psychological outcomes included both typing and mouse clicking
Int. J. Environ. Res. Public Health 2018,15, 417 11 of 14
performance. They reported no change in work performance when using a standing workstation, but
a decrease in performance when using a treadmill desk that was proportional to the speed at which
the participants were walking. The results of this present review are consistent with the review of
MacEwen and colleagues [
43
], in which typing task performance had a large decrease when cycling [
34
].
The magnitude of the decrease in performance could be attributed to the intensity of the activity [44].
A similar systematic review by Cao and colleagues [
44
] examined the effect of active workstations on
both energy expenditure and work performance. They evaluated performance when using a treadmill
desk, with decreased performance in typing tasks, mouse clicking, and transcribing speed. However,
none of the articles included were longitudinal studies in which changes in performance were evaluated
over time. Likewise, Commissaris and colleagues [
45
] evaluated the effect of workplace interventions to
reduce sedentary behavior on physical activity levels and productive work. They reported conflicting
evidence for the effects of active workstations on work performance, however, most studies were of
short duration, with performance assessed using self-reported performance measures.
The key finding of the present study was that sit-stand workstations do not appear to significantly
decrease performance, which contradicts a potential concern of employers [
46
]. In fact, in some cases
active workstations might enhance employee performance and productivity. However, although
treadmill and cycling workstations might decrease both productivity and performance, inappropriate
study design, including small sample size and lack of familiarity with the workstations, meant that a
true reflection of their impact could not be determined. The articles included in this systematic review
were limited to those from peer-reviewed journals, thus excluding other studies such as unpublished
papers, dissertations and theses. Although this might have introduced selection bias, it also ensured
that the sources selected were of sufficient quality. In addition, further research is needed to identify
the most appropriate tools to quantify work productivity and workplace performance. It has been
suggested that the Work Limitations Questionnaire (WLQ) [
47
] is the most suitable for research use
when considering the effect of physical activity [
48
]. The WLQ provides subjective measures of
both productivity and presenteeism [
49
]. An alternative measure of productivity could be ecological
momentary assessment (EMA), which has been used in a variety of different contexts [
50
]. The EMA
technique involves participants being prompted in their normal working environment at random times
throughout the day to respond about their current behavior and symptoms, which has the advantage
of sampling as close as possible to the event, thus limiting recall bias [
51
]. This technique is being
increasingly used due to the availability of electronic devices such as smartphones, which can be used
to deliver the prompts at random time points throughout a working day, so can easily be adapted to
an office environment.
5. Conclusions
This systematic review was undertaken to identify whether active workstations had any
effect on productivity or workplace performance. Most studies evaluated productivity and work
performance during single-session trials with the evidence suggesting that sit-stand workstations have
no detrimental effect on these outcomes. Limited evidence was found to suggest that treadmill and
cycling workstations might decrease some aspects of productivity and performance, but this could be
due to a lack of familiarity with the workstations. In the remaining studies in which the long-term
use of active workstations was examined, the tools used to assess productivity and work performance
were inadequate. Future studies should investigate the impact of active workstations on employees’
productivity and work performance in the workplace.
Acknowledgments: No sources of funding were received for the study.
Author Contributions:
S.O.O., D.P.B., and D.J.H, conceived and designed the experiments; S.O.O. performed the
experiments; S.O.O., D.P.B., D.J.H. and A.M.C analyzed the data; S.O.O., D.P.B., D.J.H. and A.M.C wrote the paper.
Conflicts of Interest: The authors declare no conflict of interest.
Int. J. Environ. Res. Public Health 2018,15, 417 12 of 14
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