The effects of an office ergonomics training and chair intervention on worker knowledge, behavior and musculoskeletal risk
Abstract
A large-scale field intervention study was undertaken to examine the effects of office ergonomics training coupled with a highly adjustable chair on office workers' knowledge and musculoskeletal risks. Office workers were assigned to one of three study groups: a group receiving the training and adjustable chair (n=96), a training-only group (n=63), and a control group (n=57). The office ergonomics training program was created using an instructional systems design model. A pre/post-training knowledge test was administered to all those who attended the training. Body postures and workstation set-ups were observed before and after the intervention. Perceived control over the physical work environment was higher for both intervention groups as compared to workers in the control group. A significant increase in overall ergonomic knowledge was observed for the intervention groups. Both intervention groups exhibited higher level behavioral translation and had lower musculoskeletal risk than the control group.
4 Figures
Applied Ergonomics 40 (2009) 124–135
The effects of an office ergonomics training and chair intervention on
worker knowledge, behavior and musculoskeletal risk
Michelle Robertson
a,
, Benjamin C. Amick III
b
, Kelly DeRango
c
, Ted Rooney
d
,
Lianna Bazzani
d
, Ron Harrist
e
, Anne Moore
f
a
Liberty Mutual Research Institute for Safety, 71 Frankland Road, Hopkinton, MA 01748, USA
b
Institute for Work and Health, Toronto, Canada
c
Kalamazoo, MI, USA
d
Health and Work Outcomes, Brunswick, ME, USA
e
The University of Texas School of Public Health, Houston, TX, USA
f
York University, Toronto, Canada
Received 21 July 2007; accepted 21 December 2007
Abstract
A large-scale field intervention study was undertaken to examine the effects of office ergonomics training coupled with a highly
adjustable chair on office workers’ knowledge and musculoskeletal risks. Office workers were assigned to one of three study groups: a
group receiving the training and adjustable chair (n ¼ 96), a training-only group (n ¼ 63), and a control group (n ¼ 57). The office
ergonomics training program was created using an instructional systems design model. A pre/post-training knowledge test was
administered to all those who attended the training. Body postures and workstation set-ups were observed before and after the
intervention. Perceived control over the physical work environment was higher for both intervention groups as compared to workers in
the control group. A significant increase in overall ergonomic knowledge was observed for the intervention groups. Both intervention
groups exhibited higher level behavioral translation and had lower musculoskeletal risk than the control group.
r 2008 Elsevier Ltd. All rights reserved.
Keywords: Office ergonomics intervention; Training; Musculoskeletal risk
1. Introduction
Work-related musculoskeletal disorders (WMSDs) among
office workers ar e recei ving growing attention. With ove r
45,000,000 computers in US workplaces, concerns exist
about an escalation in the incidence of computer-related
WMSDs (Tittiranonda et al., 1999). Studies have revealed a
variety of contributing factors to musculoskeletal discomfort
including: increased job demands and more hours working
at a computer (e.g., Bernard et al., 1994; Faucett and
Rempel, 1994), increased levels of psychological stress (e.g.,
Bongersetal.,1993; Carayon and Smith, 2000; Marcus and
Gerr, 1996; Faucett and Rempel, 1994), and a lack of specific
ergonomic features in the workstations and office buildings
(e.g., Nelson and Silverstein, 1998; Sauter et al., 1990).
Typically these st udies are cr oss-sectional in design (Demure
et al., 2000). Although there is a growing interest amo ng
employers to improve office workpla ces, few longitudinal
field studies have examined the effects of office ergonomics
interventions on worker’s health and performance (Brewer et
al., 2006; Buckle, 1997; National Res earch Council Insti tute
of Medicine, 2001; Karsh et al., 2001). There is some
evidence, however that ergonomics training (Brisson et al.,
1999) in workstation and building design (e.g., Aar as et al.,
2001; Hagberg et al., 1995; Lewis et al., 2002; Nelson and
Silverstein, 1998; Rudakewych et al., 2001; Sauter et al.,
1990) can prevent or reduce musculoskeletal and visual
discomforts and symptoms in office environments.
One method for reducing the prevalence of musculoske-
letal and visual symptoms is to provide specialized
ARTICLE IN PRESS
www.elsevier.com/locate/apergo
0003-6870/$ - see front matter r 2008 Elsevier Ltd. All rights reserved.
doi:10.1016/j.apergo.2007.12.009
Corresponding author.
E-mail address: michelle.robertson@libertymutual.com
(M. Robertson).
ergonomics training and workstat ion changes. Office
ergonomics training helps employ ees to understand proper
workstation set-up and postures (e.g., Brisson et al.,
1999; Bohr, 2000; Ketola et al., 2002; Lewis et al., 2002;
Verbeek, 1991). Green and Briggs (1989) showed that
merely providing adjustable furniture alone may not
prevent the onset of overuse injury. Ho wever, a significant
decrease in WMSDs has been observed when workers
were given an adjustable/flexible work environment,
coupled with ergonomics training (Robertson and O’Neill,
1999). Further, the provision of control over the work
environment through adjustability and knowledge may
enhance worker effectiveness as well as he alth (M cLaney
and Hurrell, 1988; O’Neill, 1994; Robertson and Huang,
2006).
A large-scale longitudinal field intervention study was
implemented to examine the effe cts of office ergonomics
training coupled with a highly adjustable chair on office
worker’s ergonomics knowledge, computing behaviors and
postures, and health and performance compared to
training-only and control groups. Using the instructional
system design (ISD) (Knirk and Gustafson, 1986)asa
guide, we developed an office ergonomics train ing work-
shop with the goal of motivating workers to conduct self-
evaluations and to reorganize and adjust their workspace.
Fig. 1 shows a theory of change guiding our research model
and questions (Amick et al., 2003). Participants were
assigned to one of three study groups: a group receiving the
adjustable chair and ergonomics training (C+T), an
ergonomics training-only group (T-only), and a control
group. We proposed the following hypotheses:
Hypothesis 1. Office ergonomics knowledge and intent to
change office workstation set-ups will increase for the
C+T and T-only intervention groups on pre- vs. post-
intervention tests.
Hypothesis 2. Perceived control over the work environ-
ment will increase for the T-only group compared to a
control group, with a greater increase for the C+T group
as compared to the T-only and control groups.
Hypothesis 3. There will be a reduction in musculoskeletal
risk for the T-only group as compared to the control
group, with a greater reduction for the C+T groups
compared to the T-only and control groups.
Hypothesis 4. There will be an increase in workstation
rearrangement and trained computing behavior s and
postures for the T-only group as compared to a control
group with a greater increase for the C+T group as
compared to the T-only and control groups.
2. Methods
2.1. Study participants
All participants were employees from one public sector
department of revenue services whose jobs involv ed
collecting tax revenues. Participants had access to the
internet and worked in sedenta ry, computer-intensive jobs
requiring at least 4 h per day working at an office computer
and at least 6 h per day sitting in an office chair. Individuals
who filed a Workers’ Compensation claim in the past 6
months were excluded. Informed consent documentation
was transferred over the internet on a secure website. The
Liberty Mutual Research Institute Institutional Review
Board for the protection of human subjects approved the
study.
2.2. Workplace settings
The study took place at 11 remote office locations, some
being 200–300 miles away from the corporate office.
Overall the architectural design of the workplaces varied
but, in general, consisted of long hallways with private
offices in the center of the floor and system panel individual
workstations located around the perimeter. Natural lighting
ARTICLE IN PRESS
Training
Knowledge
Productivity
Health
Satisfaction
Postures &
Behaviors
Highly
Adjustable
Chair
Functional
Health
Fig. 1. Theory of change. This model depicts the expectation that when an office ergonomics training program is implemented, an increase in ergonomics
knowledge will motivate workers to modify working postures and behaviors (e.g., break patterns, workstation set-up). The training, coupled with the
chair, is expected to improve postures and behaviors that reduce musculoskeletal loads, thereby decreasing musculoskeletal symptoms and improving
health. A decrease in symptoms influences job functioning and ultimately contributes to performance.
M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135 125
was limited for those situated closer to the center of floor
and better for those near the windows. Direct glare from
the windows could be controlled by window shades. The
individual workstations were ‘‘L’’-shaped work surfaces,
with non-adjustable stora ge, fixed work surface heights and
monitors, and minimally adjustable chairs. Some work-
stations had adjustable keyboard trays, mouse surfaces,
and document holders.
2.3. Study design
A quasi-experimental, longitudinal field study design was
employed consisting of two pre-intervention and three
post-intervention measures (Campbell and Stanley, 1966).
Pre-intervention measures of both outcomes and covariates
of theoretical importance were assessed to control for any
between-groups differences at baseline. Attempts were
made to balance workload requirements and job descrip-
tions as much as possible across the three groups. Workers
were not randomly assigned to the study groups; our intent
was to minimize the potential for the control group to
obtain ergonomic knowledge from the other two study
groups. Participants were therefore assigned to groups
based on geographic separation by different supervisory
units, floors, and buildings.
Over a 16-month period, participants were asked to
complete five online surveys: 2 months and 1 month prior
to intervention and 2, 6, and 12 months following
intervention. Individual workstation assessments and body
postures were observed (1 pre- and 1 post-intervention)
along with two training know ledge tests (pre- and
immediate post-training). Fig. 2 details the specific out-
come measures that will be reported and when they were
taken.
2.4. Office ergonomics training intervention: instructional
system design
The ISDs approach includes six phases: analysis, design,
develop, implement, evaluate, and feedback. Each of these
steps are discussed below and their applicability to the
design of the ergonomic training intervention for the
specified study sites.
2.4.1. Analysis
Needs assessment included two steps. First , interviews
were conducted by one of the authors (MMR) with the
company’s corporate ergonomi st, nurse practitioner, and
facility manager to identify existing related office health,
safety and ergonomics training programs, and to review
who had been trained in the study workforce. The semi-
structured interviews lasted approximately 1 h and were
guided by open-ended questions that focused on identify-
ing the training and ergonomic organizational practices,
policies and procedures, the existing ergonomic and safety
training programs (content, design, delivery), and the
perception of employee’s knowledge level regarding office
ergonomics. Second, the corporate facility manager pro-
vided a facility walk-through for one researcher (MMR) to
view the company’s office spaces, workstation configura-
tions, layout, and furniture.
2.4.2. Design
Based on the needs assessment and previous work in
office ergonomics training (Robertson and O’Neill, 1999),
the training goals, objectives, and procedures were defined.
The training goals were to: (1) understand office ergo-
nomic principles, (2) perform ergonomic self-evaluation of
ARTICLE IN PRESS
Study timeline and measurements
Pre-Intervention
Intervention# Post-Intervention
-2 -1 0 +2 +6 +12
Measures
Employee surveys
(WEH)*; Perceived control
Observations: OEA**
and RULA***
Ergonomics knowledge
Pre-post training tests
*Work Environment and Health (WEH) survey
** Office Ergonomics Assessment (OEA)
*** Rapid Upper Limb Assessment (RULA)
#Office ergonomics intervention consisting of ergonomics training and highly adjustable chair;
3 Grou
p
s: Grou
p
1 = Chair + Trainin
g
, Grou
p
2 = Trainin
g
-Onl
y
, Grou
p
3 = control
Fig. 2. Study timeline and measurement periods.
M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135126
workspaces, and (3) adjust and rearrange one’s own
workspace. Nine instructional objectives wer e specified:
recognizing WMSDs and risk factors,
understanding the importance of varying work postures,
knowing how to rearrange the workstation to maximize
the ‘‘comfort zone’’,
recognizing and understanding visual issues in the office
environment,
reducing visual discomfort,
understanding computing habits (rest breaks),
knowing how to change work–rest patterns,
being aware of the company’s existing health and
ergonomic programs,
knowing how to obtain ergonomic accessories through
the company’s programs.
For each objective, appropriate presentation strategies
and media were determined. Active adult learning models,
which allow for a high level of interaction among the
trainers and trainees (Gordon, 1994), were specified for use
in the training.
2.4.3. Develop
Multi-media presentation provided for various learning
modalities for the trainees. The primary media presentation
included power point sli des, an ‘‘Office Ergonomics
Today’’ video, demonstrations, and pictures of various
trainees’ computer workspaces. Practice sessions, perfor-
mance feedback, group discussion, and problem solving
activities were all used to facilitate the learning process.
Each trainee used their own office chair and learne d
appropriate adjustments. Group exercises and breakouts
were designed and consisted of having the trainees condu ct
ergonomic assessments of several computer workspaces
and provide recommendations. Debriefing and feedback
were provided by the co-facilitators. Participants were
provided with an opportunity to share real-life examples
and experiences related to their computer workspaces.
These active learning exercises were designed to instill
desired attitudes toward healthy computing, skills of how
to use their workspaces, as well as transference of these
skills to behaviors when the trainee returned to their
workspace. We developed several training materials
including: a facilitators handbook, and a computer
ergonomic guidelines (‘‘Ergo-Guidelines’’) handout with
recommendations and solutions. These ergonomic hand-
outs were intended for the trainees to use for future
reference.
2.4.4. Implement
The training and evaluation mate rials, including the pre/
post-knowledge tests, were piloted with 25 office workers at
another worksite. The training materials and the instruc-
tional sequence were modified to meet the training time
limit of 90 min. For consistency, the same two co-
facilitators, using the same training materials, delivered
the training at each of the 11 participating company sites
using the same training materials. Facilitators were trained
ergonomists and health experts. Training lasted for 1.5 h
and was introduced by a supervi sor. All supervisors
attended the training. Each participant was either provided
with the newly adjustable chair at the workshop (group 1;
Chair+Training) or came to the training with his or her
existing chair (group 2: Training-only). Group 3, the
control group, was trained after the study was completed as
an obligation and benefit to the participating worksite.
2.4.5. Evaluate
Training’s effectiveness was evaluated based on a five
level training evaluation framework (Knirk and Gustafson,
1986; Kirkpatrick, 1979): (1) baseline assessment, prior to
training, (2) trainee reaction, (3) learni ng, (4) performance,
and (5) organizational results. In Level 4, behavioral and
symptom measures may be included as they are relevant to
measures of effectiveness regardi ng ergonomic training
interventions. Evaluation results for Levels 1–3, and part of
Level 4 are presented. Symptom reporting and productivity
results of this ergonomic intervention study are reported in
Amick et al. (2003) and DeRango et al. (2003), respectively.
The training effectiveness measur es included: Level 1: pre-
training office ergonomics knowledge tests; Level 2:
trainees’ reaction to the ergonomics workshop (usefulness,
value, and relevance); Level 3: pre–post office ergonomics
knowledge tests; and Level 4: observed behavioral changes.
All of these measures and instruments are described below.
2.4.6. Feedback
E-mail messages provided feedback to the trainees on the
results of the knowledge tests and served as reminders of
the office ergonomics principles. Messages were sent at 1
and 3 months post-training. These communications were
coordinated by the company’s facilities manager, who
spearheaded the research project. The 1-month post-
training e-mail notified the trainees of the results of the
course evaluation and knowledge tests highlighting the
item(s) with the greatest improvements and the item(s) with
the least improvement. The 3-month post-training e-mail
included selected results from the post-training observed
behaviors and contained reminders about working pos-
tures and tips on healthy computing habits and exercises.
Also, reminders about corporate resources concerning
ergonomics were given at 1 and 3 months following the
training.
2.5. Office ergonomic chair
The ergonomic chair chosen for the intervention has
highly adjustable design features including width telescop-
ing armrests, dynamic back support, gliding seat depth,
plus the standard ANSI VDT(1998) ergonomic chair
requirements (e.g., lumbar support, seat height adjustment,
waterfall seat pan front, and five-coaster base). The intent
of these adjustable features is to support the ergonomic
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M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135 127
goal of improving the worker fit to his or her office
workspace (Bush and Hubbard, 1999). For a detailed
description of the chair design features and functions see
Amick et al. (2003).
2.6. Instrument and outcome measures
Several instruments were used in the study including: (1)
Work Environment and Health (WEH) survey (Amick et
al., 2003), which asks workers to report comfort, satisfac-
tion, health, computer use, performance, and basic
demographic information, (2) two observational tools;
Office Environment Assessment (OEA), and Rapid Upper
Limb Assessment (RULA), (3) office ergonomics knowl-
edge tests, and (4) office ergonomics workshop evaluation.
2.6.1. Work Environment and Health (WEH) survey
Perceived control over their work environment and
knowledge was measured by an objective, 18-item checklist
to determine: (a) the number of adjustable features within
the workspace and chair (availability of control), (b) the
number of features that employees knew how to adjust
(knowledge of control) within a workstation and chair, and
(c) whether they had adjusted the items (exercise of control)
for both the workstation and chair. Response categories
were ‘‘yes’’, ‘‘no’’, or ‘‘don’t know’’. The knowledge of
adjustability score was determined by the number of
features the worker knew how to adjust divided by the
number of adjustable features in the works pace. The
exercise adjustability score was determined by the number
of features the workers had adjusted divided by the number
of adjustable features in the workspace. The result was four
indices representing the degree of the workers’ percept ion
of control over their physical environment: (1) chair
knowledge of adjustability, (2) chair exercise of adjust-
ability, (3) workstation knowl edge of adjustability, and (4)
workstation exercise of adjustability. The total score is the
summative average where a higher score indicates more
knowledge and exercise of adjustability.
2.6.2. Rapid Upper Limb Assessment (RULA)
observational tool
RULA was used to assess working postures and the
associated muscular effort and exerting forces of computer
users (McAtamney and Corlett, 1993; Lueder and Corlett,
1996). A computerized version of RULA was developed
based on the RULA illustrations and scoring tables
reported in Lueder and Corlett (1996) (McGorry and
Chang, 2002). Four scores were generated for both the left
and the right sides of the body: Score A: upper arm/wrist/
wrist twist, Score B: neck, trunk, legs, Score C: Score
A+muscle and force scores, Score D: Score B+muscle and
force scores, Grand score: combination of Score C and
Score D+weig hted combination of the four subscores. The
grand score is based upon the estimated risk of injury due
to musculoskeletal loading. The scales range from 0 to 5
where a higher score represents more of postural load,
muscular effort, and musculoskeletal risk.
2.6.3. Office Environment Assessment observational tool
The OEA is a ne w observational tool intended to
evaluate the ergonomic configuration of the overall work-
space and items within the worker’s control to change. This
39-item instrument allows for observing the impact of the
ergonomic training program on the behaviors of office
workers. There are 7 categorical areas: (1) work surface
configuration (2 items), comfort zone and accessories
(10 items), keyboard and mouse (13 items), monitor
(7 items), lighting and glare (6 items), and chair features
(9 items). The OEA generates two scores. First, the overall
Appropriate Ergonomic Configuration (AEC) score is
calculated as the percent of all items correctly configured,
regardless of their adjustability. This score reflects how
many items within the workspace were appropriately
positioned or adjusted relative to the worker’s needs—
irrespective of whet her the items could be manipulated in
any way by the worker. Second, the Training Outcome
(TO) score is calculated as the percent of all items that
could be changed and were correctly configured within the
worker’s workspace. The total score is the mean percent,
ranging from 0 to 1, where higher AEC and TO scores
represent more appropriately adjusted/or moved items.
Trained raters decided whether or not something was
adjustable, moveable, or properly configured. Each parti-
cipant was unobtrusively observed while they were
performing representative computing postures such as
keying and mousing.
2.7. Inter-rater reliability procedure
Four observers, all with backgrounds in ergonomics,
were trained on the OEA and RULA observational
instruments. Observers were trained by one of the authors
(MMR). Training consisted of a 3.5 h workshop, including
a review of the purpose, the instruments, the operational
definition of terms, the basic observational techniques, and
the procedural use of the instruments. First, observers
individually practiced rating on a series of selected pictures
of office workers in class , followed by interactive practice
sessions with paired trainees in the field. Immediate
performance feedback was given by the instructor. Each
observer then conducted a series of assessments on the
same individuals until there was 90% agreement across
items and the gold standard (the instructor). This process
required 5 practi ce assessments with the whole group of
observers before the 90% agreement was reached.
After the training was completed, each observer parti-
cipated in an inter-rater reliability study. Sixteen parti ci-
pants were randomly selected and simultaneously eva-
luated. Intraclass Correlation Coefficients (ICC), with
observers treated as a random factor, were determined
for the RULA subscores and grand scores and the
OEA scores (AEC and TO). A second study was conducted
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M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135128
post-intervention. An ICC score of 0.70 was considered
appropriate for an adequate reliability among observers.
2.8. Office ergonomics knowledge pre–post-tests
Pre- and post-training office ergonomics knowledge tests
were distributed to the training intervention groups while
they were assembled in the training room. These tests
consisted of 17 questions assessing seven knowledge areas
of office ergonomics: (1) work-related risk factors (2 items),
(2) physical ergonomic features (2 items), (3) body posture
(6 items), (4) workstation layout and configuration
(4 items), (6) rest breaks (1 item), and (7) ergonomic
practices and resources (2 items). The total number of
correct items was summed for each participant, ranging
from 0 to 17, with 17 being a perfect score.
The post-training knowledge test had one additional
open-ended question: ‘‘What immediate changes are you
going to make to your computer workstation as a result of
this office ergonomics training?’’ Responses were content
coded by two raters who first reviewed all of the comments
together, identified specific themes, and then coded the
responses until 100% agreement was met between them.
2.9. Office ergonomics training workshop evaluation
Workshop ratings provided by participants consisted of
17 items assessing satisfaction with the training format and
objectives (6 items), the facilitators (4 items), and course
materials (7 items). Responses were provided on a 4-point
Likert scale from ‘‘1’’ (strongly agree) to ‘‘4’’ (strongly
disagree) for 14 items and ‘‘1’’ (very useful) to ‘‘4’’ (not
useful) for 3 items.
2.10. Statistical analyses
To test the pre–post-differences in mean scores for the
four perceived control indices, a simple multivariate model
in STATA was conducted. Multilevel analyses were
completed using MLwiN 1.1 (2001) and all other analyses
using STATA 7 (2000). Differences in correct responses
pre-test vs. post-test ov erall, and between knowledge areas
were tested using paired t-tests (i.e., design layout vs. body
posture).
3. Results
3.1. Participation rates
For the overall study, 316 workers were invited to
participate and 219 provided informed consent for a
participation rate of 69.3%. Study participant demo-
graphic and workplace characteristics have been described
previously: the mean age was 47; 60% of the participants
were female; and nearly all participants were white or
Caucasian (Amick et al., 2003). Average time spent in an
office chair and computing was 5–6 h per day. Table 1
presents the breakdown by group for those who partici-
pated, completed the WEH surveys, attended the training,
and were observed. The sample size for the control group
was n ¼ 57, chair+training (C+T) n ¼ 96 and training-
only (T-only) n ¼ 63. There was no significant difference
regarding the drop out rates among the groups, and
there was a high level of retention (88%) (see Amick et al.,
2003).
3.2. Inter-rater reliability for RULA and OEA
Tables 2 and 3 presents the calculated ICCs for each
RULA subscores an d grand scores, and the two OEA
subscores, AEC and TO scores, respectively. The differ-
ences in the ICCs between Time 1 and Time 2 were due
to the additional practice time and feedback given to
the evaluators on understanding the instrument and
operational definitions of items in the observational
measures.
ARTICLE IN PRESS
Table 1
Number of participants by group and measurement period, who completed work environment and health surveys, training knowledge tests, and
observations
Study groups Study time measurement period
Time 1 Time 2
Pre-intervention Post-intervention
WEH
a
Trained experimental
groups
Observed
OEA
b
Observed
RULA
c
WEH Observed
OEA
Observed
RULA
Training and chair
n ¼ 96
85 86 62 51 79 57 69
Training-only n ¼ 63 51 59 45 37 48 29 38
Control n ¼ 57 53 45 44 43 24 44
a
WEH: Work Environment and Health Questionnaire (perceived control over environment questions).
b
OEA: Office Ergonomics Assessment.
c
RULA: Rapid Upper Limb Assessment.
M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135 129
3.3. Office ergonomic knowledge
3.3.1. Trainee’s reaction
Participants in the two intervention groups found the
training to be beneficial as reported on the post-training
evaluation questionnaire by either strongly agreeing (64%)
or agreeing (36%). Trainees’ responses to the question ,
‘‘Will they be able to apply this information to their job’’
yielded 63% strongly agreeing and 37% agreeing.
3.3.2. Trainee’s learning
Results of the pre/post-knowledge test revealed signifi-
cant increases in knowledge about: overall office ergo-
nomics (t(143)=13.7, po0.001), the use of ergonomic
workstation and chair features (t(143)=7.8, po0.001),
improvement of body postures (t(143)=8.9, po0.001),
company ergonomic practices and company resources
(t(143)=12.4, po0.001) (see Fig. 3).
3.4. Self-reported intended behavior changes: post-training
test
Pertaining to self-reported intended behaviors, over 93%
of the trainees responded to the open-ended question:
‘‘yWhat immediate changes are you going to make to
your computer workstation as a result of this office
ergonomics training?’’ Of those that responded (n ¼ 124),
45% indicated at least two or more changes with changes
to the chair, appropriate workstation adjustments,
and monitor placement the most frequently provided
responses. Similarly, these responses were observed for
the control group after the intervention. Fig. 4 presents
trainees’ self-report of immediate workstation changes
following training.
3.5. Perceived control over the work environment
Responses to the knowledge and exercise of chair
adjustability questions showed a positive change for the
groups receiving the training as compared to the control
group, though not statistically significant (p40.05). An
observed positive change was noted in the responses to the
knowledge of workstation adjustability questions for the
chair+training (pre-intervention M ¼ 0.70; post-interven-
tion M ¼ 0.76) and training-only groups (pre-intervention
M ¼ 0.81; post-intervention M ¼ 0.90) as compared to the
control group (pre-intervention M ¼ 0.85; post-interven-
tion M ¼ 0.82). However, no significant change was found
for the knowledge and exercise workstation adjustability
questions.
3.6. Observed postural and behavioral changes
Selection of confounders followed a statistical analysis
protocol described in Amick et al. (2003). Of the 30
covariates measured through the WEH, 10 were identified
as potentially relevant to the OEA and RULA observa-
tional outcomes. These 10 were: hours spent working at
office computer, repetitive hand and wrist activity, decision
latitude, social support, body mass index categorization,
general health, wearing of eyeglasses, age, and gender.
A separate confounder selec tion process was conducted for
each outcome modeled.
Through the covariate selection process, only repetitive-
ness of hand/wrist activity (0 ¼ no repetiti veness and
6 ¼ highly repetitive) remained in the models predicting
the OEA outcomes, and no covariates remained in the
models predicting the RULA grand scores.
3.6.1. Postural changes: RULA
Table 4 presents the multilevel model results. The models
show that both trained intervention groups significantly
improved their observed computing body postures (lower
RULA scores) compared to the control group, for both the
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Table 2
RULA intraclass correlation coefficients
ICC—right side of body score ICC—left side of body score
Time 1
a
Time 2 Time 1 Time 2
Score A (upper arm/wrist/wrist twist) 0.66 0.93 0.40 0.85
Score B (Neck, trunk, legs) 0.37 0.99 0.40 0.99
Score C (Score A+muscle and force) 0.58 0.93 0.32 0.90
Score D (Score B+muscle and force) 0.40 0.99 0.37 0.99
Grand score (Score C and Score D) 0.42 0.65 0.44 0.86
a
Time 1 is pre-intervention with 16 observations and 4 observers. Time 2 is post-intervention with 27 observations and 4 observers.
Table 3
OEA intraclass correlation coefficients
ICC
Time 1
a
Time 2
AEC score (Appropriate Ergonomic Configuration) 0.60 0.91
TO score (Training Outcome) 0.61 0.92
a
Time 1 is pre-intervention with 16 observations and 4 observers. Time
2 is post-intervention with 27 observations and 4 observers.
M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135130
right and left side of the body . The C+T intervention
group experienced a significant improvement in computing
postures post-intervention compared to the control group
for the left side of the body (b ¼2.25; z ¼7.77;
po0.05) and for the right side of the body (b ¼1.94;
z ¼6.23; po0.05). The T-only group experienced a
statistically significant improvement in computing posture
post-intervention compared to the control group for the
left side of the body (b ¼1.88; z ¼5.77; p ¼ 0.00) and
for the right side of the body (b ¼1.98; z ¼5.73;
p ¼ 0.00). The difference between C+T and the T-only
groups for both the left and right side of the body were
not statistically significant. Changes in the RULA
scores for the left and right side of the body are depicted
in Fig. 5.
3.6.2. Behavioral changes: Office Ergonomics
Assessment (OEA)
The results of the multilevel model for the OEA show
that the chair with training group did not experience post-
intervention improvements in workstation changes for
either TO (b ¼ 0.034; z ¼ 1.35; p ¼ 0.176) or AEC
(b ¼ 0.045; z ¼ 1.9; p ¼ 0.057) as compared to the control
group (see Table 4). The training-only group experienced a
statistically significant improvement post-intervention in
workstation changes (TO) (b ¼ 0.71; z ¼ 2.49; p ¼ 0.01)
and AEC (b ¼ 0.079; z ¼ 2.97; p ¼ 0.003) as compared to
the control group. Post hoc analysis revealed that with the
removal of the covariate hand/wrist repetitiveness, the
chair with training group model for TO approaches
significance p ¼ 0.075 compared to the control group.
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0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Overall* WMSD risk
Factors
Physical
ergonomic
features*
Body
posture*
Work-
station
Layout
Rest Breaks Ergonomic
practices,
resources*
Pre
Post
Percent Correct
Fig. 3. Percentage of correct responses on the pre–post office ergonomic knowledge questions (n ¼ 145; experimental groups; chair+training and
training-only), *po0.001.
0
5
10
15
20
25
30
35
40
45
Types of Changes
Percent
Monitor
Chair
Comfort zone
Keyboard/keyboard tray
Documents/document holder
Mouse
Glare
Footrest
Laptop
Review whole set-up
Posture
Take "micro" breaks
Furniture
Fig. 4. Percentage of intended types of workstation changes as reported by the trainees ( n ¼ 124 responses).
M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135 131
The difference between chair with training group and the
training-only groups for the TO and AEC scores were not
statistically significant (p40.05). The percent improve-
ments for the OEA regarding observed behavioral changes
are depicted in Fig. 6.
4. Discussion
This study examined the effects of an office ergonomics
intervention, consisting of office ergonomics training and a
highly adjustable chair, on workers knowledge, computing
behaviors, postures, and risk of musculoskeletal and visual
discomfort. Due to the knowledge gained following an
office ergonomics intervention improved postures and
computing behaviors may be observed. The trainees
reported that the office ergonomics training was beneficial
and that they could apply the informat ion to their work
environment. Additionally, there was an increa se in office
ergonomics knowledge and skills of the participants from
pre- to post-intervention. Participants exhibited a large,
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Table 4
Multi-level models for Rapid Upper Limb Assessment (RULA) and Office Environment Assessment (OEA)
Variable name RULA models:
Grand score, left side Grand score, right side
Coefficient (Std. error) Coefficient (Std. error)
Chair with training 0.15 (0.24) 0.43 (0.24)
Training-only 0.21 (0.26) 0.21 (0.26)
Intervention phase 0.53 (0.22)
0.54 (0.23)
Chair+trainingintervention (interaction
term)
2.25 (0.29)
1.94 (0.31)
Training-onlyintervention (interaction
term)
1.88 (0.33)
1.98 (0.35)
Intercept term 4.31 (0.17)
4.63 (0.18)
Level 1 variance 0.98 (0.07)
1.07 (0.07)
Level 2 variance 0.59 (0.11)
0.50 (0.13)
Variable name OEA models:
Training Outcome (TO) model Appropriate Ergonomic Configuration
(AEC) model
Coefficient (Std. error) Coefficient (Std. error)
Chair with training 0.041 (0.018)
0.051 (0.017)
Training-only 0.039 (0.020) 0.042 (0.019)
Intervention phase 0.088 (0.021)
0.091 (0.019)
Chair+trainingintervention (interaction
term)
0.034 (0.025) 0.045 (0.024)
Training-only
intervention (interaction
term)
0.071 (0.028)
0.079 (0.027)
Repetitive hand/wrist activity 0.016 (0.004)
0.013 (0.004)
Intercept term 0.580 (0.022)
0.600 (0.021)
Level 1 variance 0.068 (0.006)
0.064 (0.005)
Level 2 variance 0.058 (0.008)
0.056 (0.007)
po0.05.
-2
-1.5
-1
-0.5
0
0.5
1
Change in RULA Grand Score
Chair With Training Training Only Control
Left Side
Right Side
Fig. 5. Changes in RULA grand score for postural changes on the left and right side of body for each study group after intervention. Changes in RULA
scores (postural changes) are calculated from the predicated model values pre- and post-intervention.
M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135132
significant increase in knowledge about body postures,
ergonomic design features, and corporate resources.
Through training, these employees were encouraged to
use corporate resources to achieve an ergonomic fit with
their new chair as well as setting up and arranging their
workstations components. Participants gained a high level
of knowledge and awareness of where to go and who to
contact concerning the use of corporate ergonomic
resources and facility adjustments and changes. At the
end of the study, the control group was trained an d it is
noted that the three groups did not differ significantly from
one another in their average level of knowledge pre- and
post-intervention (p’s40.05).
The lack of significant results on the environmental
control and adjustability control questions was surprising.
However, positive changes were observed for both trained
groups for all four perceived control indices. There may
have been an issue of statistical power due to the varying
number of adjustable items in the workstation. In some
instances, participants only needed to adjust one thing in
their workstation or chair.
Observational results indicate that the two trained
groups exhibited a higher level of behavioral translation
leading to less awkward postures and musculoskeletal
loading. Trained participants were more likely to make
appropriate behavioral changes to their workstation than
the control group. With the participant’s increased knowl-
edge and skills of office ergonomics, workers were more
likely to ergonomically adjust their workstation, chair set-
up and other ergonomic accessories, thereby reducing non-
neutral postures and muscular effort, as was indicated by
lower RULA grand scores and improved OEA scores.
The marginal non- significant findings for the OEA for
the chair with training group may be due to several issues.
One is it may be due to the fact that the hand/wrist
repetitiveness covariate is acting as an outcome as it
showed improvement post-intervention. Second, it appears
that the chair with training group started at higher OEA
scores than the other two groups, thus minimizing the
amount of potential change. How ever, the chair and
training group had positive changes in the workstation
arrangement and reduction in hand/wrist activity post-
intervention. Moreover, this group appears to be applying
the training and making appropriate changes, which may
have possibly influenced the movement patterns of the
hand and wrist, thus reducing the repetitive motions. These
results are consistent with those of Ketola et al. (2002)
showing that trained groups in office ergonomics demon-
strated less musculoskeletal discomfort than the reference
group. Bohr (2000) found that those who received office
ergonomics education reported less pain/discomfort and
psychosocial work stress following the intervention than
those who did not receive education, however it was
unclear whether the diff erences in reported pain/di scomfort
or psychosocial work stress were related to better work
area configuration or improved worker postures.
The study results suggest that with the increased knowl-
edge in ergonomics, positive changes in workstation
configuration are associated with behavioral changes.
However, this was only in the training-only intervention
group, whereas the C+T group only showed significant
improvements in computing work postures. These changes
were translated into improved working postures, thus
potentially reducing musculoskeletal risks. Furthermore, as
reported elsewhere, we have observed a reduction in
musculoskeletal symptom growth over the workday and
visual symptoms (Mene
´
ndez et al., 2006) for the C+T
group, and a reduction in average pain levels over the
workday (Amick et al., 2003) for both C+T and T-only
intervention groups. Given these changed computer work-
ing postures, there is the potential to reduce musculoske-
letal loading which may lead to impr oved performance and
positive return on investment (shown in our earlier work;
DeRango et al., 2003).
4.1. Study limitations and strengths
Limitations of the study are: the degree to which threats
to internal and external validity can be addressed given the
study field design, the lack of randomizatio n (however, a
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0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
Training Outcome
Change in Mean Scores
Chair With Training Training Only Control
Appropriate Ergonomic Configuration
Fig. 6. Mean changes in Office Ergonomics Assessment (OEA) scores (Training Outcome) and Appropriate Ergonomic Configuration (AEC) for each
study group pre- and post-intervention.
M. Robertson et al. / Applied Ergonomics 40 (2009) 124–135 133
range of covariates was measured and the risk of
contamination was reduced), and the limited postural
information co llected due to cost, time, and intrusiveness.
Also, the pre-intervention ICC’s for the observational
measures were marginal. Strengths of this study are: its
systematic process for training program development,
‘‘presence of a control group, high participation rate,
limited loss to follow-up’’ the full participation of the
managers and supervisors, including strong support of
senior management, and its study design being longitudinal
in nature with individual level measures.
5. Conclusion
Overall, our study findings suggest that due to the
knowledge gained from office ergonomics training and an
adjustable chair, workers were able to appropriately
change and adjust their workstation and chair set-up more
ergonomically and effectively. Further field intervention
research is needed to support these findings and to replicate
them with different office workplace designs and training
programs. These findings would contribute to a knowledge
base on how to optimally design workplace interventions
to help create injury-free environments for office workers.
Acknowledgments
The authors would like to acknowledge and thank the
following Liberty Mutual colleagues who served as
reviewers for this paper: Drs. William Horrey and Mary
Lesch, as well as Steelcase, Inc. and Noe Palacios and Paul
Allie who contributed to data collection.
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- CitationsCitations86
- ReferencesReferences38
- fiziksel ve psikososyal riskler ?zerinde durmu?lar ve ilgili literat?r? g?zden ge?irmi?lerdir. Robertson ve ark.[5], ofis ?al??anlar?n? 3 grupta ele alm??lard?r. Birinci gruba ayarlanabilir sandalyeler da??t?lm?? ve ergonomik ?nlemler hakk?nda e?itim verilmi?tir.
- Whilst the only real way to eliminate the appearance of musculoskeletal disorders is by eliminating manual lifting, this is only possible with an extremely advanced layout or with the use of forklifts, which for SMEs in a local context is not always feasible. As for employees who have to be seated all day or have to be in the same spot, a reliable measure is to teach them proper postures that help avoid back pain and providing them adjustable chairs with an ergonomic design which reduces musculoskeletal disorder risk [10].
[Show abstract] [Hide abstract] ABSTRACT: A group of 22 companies from different sectors was selected in order to carry a diagnosis related to work conditions in the city of Barranquilla. In order to do such, an instrument was designed so that the relevant information was collected. With such information, the weak points were detected mostly related to climatic conditions, physical strain, noise and social welfare and low cost measures were discussed to be implemented in order to improve work conditions. Such measures are expected to generate an increase in productivity and an enhancement in the operatives’ attitude.- At baseline, at the conclusion of primary training, and then at six and 12 months post-primary training (follow-up), participants will also complete health questionnaires (musculoskeletal symptoms and general health perceptions) as well as training content questionnaires. Similar measurement intervals have been used by other investigators to assess durability of training [33, 38]. All training groups (intervention and control) will be measured at the same intervals with the same study instruments.
[Show abstract] [Hide abstract] ABSTRACT: Background Masons have the highest rate of overexertion injuries among all construction trades and rank second for occupational back injuries in the United States. Identified ergonomic solutions are the primary method of reducing exposure to risk factors associated with musculoskeletal disorders. However, many construction workers lack knowledge about these solutions, as well as basic ergonomic principles. Construction apprentices, as they embark on their careers, are greatly in need of ergonomics training to minimize the cumulative exposure that leads to musculoskeletal disorders. Apprentices receive safety training; however, ergonomics training is often limited or non-existent. In addition, apprenticeship programs often lack “soft skills” training on how to appropriately respond to work environments and practices that are unsafe. The SAVE program – SAfety Voice for Ergonomics – strives to integrate evidence-based health and safety training strategies into masonry apprenticeship skills training to teach ergonomics, problem solving, and speaking up to communicate solutions that reduce musculoskeletal injury risk. The central hypothesis is that the combination of ergonomics training and safety voice promotion will be more effective than no training or either ergonomics training alone or safety voice training alone. Methods/design Following the development and pilot testing of the SAVE intervention, SAVE will be evaluated in a cluster-randomized controlled trial at 12 masonry training centers across the U.S. Clusters of apprentices within centers will be assigned at random to one of four intervention groups (n = 24 per group): (1) ergonomics training only, (2) safety voice training only, (3) combined ergonomics and safety voice training, or (4) control group with no additional training intervention. Outcomes assessed at baseline, at the conclusion of training, and then at six and 12 months post training will include: musculoskeletal symptoms, general health perceptions, knowledge of ergonomic and safety voice principles, and perception and attitudes about ergonomic and safety voice issues. Discussion Masons continue to have a high rate of musculoskeletal disorders. The trade has an expected increase of 40 % in the number of workers by 2020. Therefore, a vetted intervention for apprentices entering the trade, such as SAVE, could reduce the burden of musculoskeletal disorders currently plaguing the trade. Trial registration ClinicalTrials.gov Identifier: NCT02676635, 2 February 2016- Although McAtamney and Corlett (1993) claimed the method to be reliable, statistical calculations were not published and this method suffered from the same biases as other observational methods would. Indeed, only a fair inter-rater reliability of the RULA grand score (ICC < 0.5) was found for observers with a common background in ergonomics (Robertson et al., 2009). The observers need to be trained to accurately fill in the RULA assessment grid (Dockrell et al., 2012).
[Show abstract] [Hide abstract] ABSTRACT: Evaluating potential musculoskeletal disorders risks in real workstations is challenging as the environment is cluttered, which makes it difficult to accurately assess workers' postures. Being marker-free and calibration-free, Microsoft Kinect is a promising device although it may be sensitive to occlusions. We propose and evaluate a RULA ergonomic assessment in real work conditions using recently published occlusion-resistant Kinect skeleton data correction. First, we compared postures estimated with this method to ground-truth data, in standardized laboratory conditions. Second, we compared RULA scores to those provided by two professional experts, in a non-laboratory cluttered workplace condition. The results show that the corrected Kinect data can provide more accurate RULA grand scores, even under sub-optimal conditions induced by the workplace environment. This study opens new perspectives in musculoskeletal risk assessment as it provides the ergonomists with 30 Hz continuous information that could be analyzed offline and in a real-time framework.- Given Dr. Robertson's experience, she will address how training is an important component of effective multicomponent/multi-level occupational health and safety prevention strategies (Robson et al., 2012; Robertson, 2002; 2009; Kennedy et al, 2008). Training alone may not reduce MSD outcomes if the workplace hazards are not changed and there are limited affordances provided in the work environment (e.g., Brewer et al., 2006; Robertson et al., 2009). Clearly, there is a need for more intervention research to effectively design training programs that link knowledge about workstation adjustments to the actual practice changes reducing MSD risks.
[Show abstract] [Hide abstract] ABSTRACT: Increasingly, individuals are using more blended, hybrid, and online deliver formats in education and training. Although research exists about how the physical and social environment impact learning and training in traditional face-to-face settings, we have limited knowledge about how the environment affects learners when they are interacting with technology in their learning situations. In particular, concerns arise about levels of engagement, whether learning is enhanced, the impact or helpfulness of robotics, and how the social dynamics change. These five panelists bring expertise in education at the undergraduate and graduate levels, training within industry and the military, and the use of various teaching and training methods. The panelists will present their perspectives to several questions relative to how the environment can (or cannot) accommodate enhanced learning in education and training when technology is involved. Ample time will remain for audience participation.- Johansson's (1995) research into psychosocial work factors, physical work load, and associated musculoskeletal symptoms among home care workers concluded that the highest relative risk factors were a combination of a poor psychosocial work environment and high physical workload [17,32]. Alireza et al. (2011) [28] noted that some psychological factors, including physical job demands, physical exertion and physical isometric load, were significantly associated with musculoskeletal symptoms in different body regions. Additionally, De Jonge and Kompier (1997) [33] stated that the size of the research population could have important implications for the results of a study [33].
[Show abstract] [Hide abstract] ABSTRACT: (1) Background: Musculoskeletal disorders have a multifactorial etiology that is not only associated with physical risk factors, but also psychosocial risk factors; (2) Objective: This study evaluated the effects of an ergonomic intervention on musculoskeletal disorders and psychosocial risk factors; (3) Material and Methods: This study took a participatory ergonomic (PE) approach with a randomized controlled trial (RCT) conducted at tertiary care hospitals during July to December 2014. A group of hospital orderlies in Thailand were randomly selected for examination. Fifty orderlies were placed in a case group and another 50 orderlies were placed in the control group. The Nordic Musculoskeletal Disorders Questionnaire (NMQ) and the Copenhagen Psychosocial Questionnaire (COPSOQ) were used for data collection before and after the intervention program; (4) Results: The most commonly reported problem among hospital orderlies was found to be lower back symptoms (82%). The study found significant differences in prevalence rates of reported musculoskeletal conditions in the arm, upper back, and lower back regions before and after intervention. Findings showed that psychosocial risk factors were affected by the intervention. COPSOQ psychosocial risk factors were significantly different pre/post intervention. These variables included: work pace, influence at work, meaning of work, predictability, rewards, role conflicts, and social support from supervisors. No other psychosocial risk factors were found to be significant; (5) Conclusions: Positive results were observed following the intervention in the work environment, particularly in terms of reducing physical work environment risk factors for musculoskeletal disorders and increasing promotion factors of the psychosocial work environment.
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