37th Annual Conference
Ergonomics Society of Australia Inc.
KEYNOTE PAPERS
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Learning from Experts: How the Study of Expertise Might
Help Design More Effective Training
Bruce Abernethy
School of Human Movement Studies, The University of Queensland
Keywords: Expertise, Skill Acquisition, Practice, Learning, Ergonomics
ABSTRACT
There is now a significant body of literature, drawn from a diverse range of
cognitive, occupational and sporting tasks, that identifies factors that discriminate
expert from lesser skilled performers and that demonstrates systematic differences
in the task information picked up and used by people of different skill levels. This
paper provides a brief overview of what the existing expertise literature has
revealed with respect to limiting factors to skilled performance, with respect to
skill-related differences in information usage, and with respect to how learning to
be an expert takes place. Specific implications are drawn as to how knowledge
about the distinguishing attributes of expert performance might be used, in a
targeted way, to develop training programs to accelerate the acquisition of
expertise, to improve workplace and task designs, and to facilitate expert systems
development.
1. EXPERTISE AND ERGONOMICS
Expertise is highly sought and valued in the workplace, just as it is in a wide range of other
settings. Expertise is not easily acquired; indeed in most domains in which expertise has
been systematically studied the attainment of expert performance is typically only seen after
at least 10 years, 10,000 hours, or literally millions of trials of daily, effortful practice
(Ericsson et al., 1993). Consequently, finding means of facilitating the rate of acquisition of
expertise is particularly desirable.
The scholarly study of expertise is concerned with describing and understanding the nature of
the control processes that fundamentally differentiate the expert performer from the lesser
skilled and the processes through which expertise is acquired. Because of the time scales
involved, studying experts in natural tasks, like work tasks, provides a window into learning
and skill optimisation that conventional, laboratory-based learning studies of untrained
participants simply cannot replicate. However, despite concerted research efforts particularly
over the past three decades, and the development of a solid descriptive base of expert
performance characteristics, the underlying basis of expert performance and its acquisition
remains quite poorly understood.
An important focus for ergonomics is discovering superior training procedures, task designs
or systems that can enhance productivity, efficiency and/or safety in the work setting. Such
discovery is dependent upon the integration of information and approaches from a number of
disciplines and otherwise discrete bodies of knowledge. The principal purpose of this paper is
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to highlight, by way of example, some of the important contributions the expanding body of
knowledge on expertise can potentially make to contemporary ergonomics practice.
There are a number of ways in which the study of expertise has the potential to provide benefits
within the field of ergonomics. First, the comparison of the perceptual-motor skill and skill
components of experts and novices in specific tasks can help identify the limiting factors to
performance in the task of interest. Knowing those factors that do, and equally importantly do
not, discriminate expert and novice performers can provide a principled basis for guiding
emphasis within a practice/training schedule aimed at improving skill. Second, comparison of
the information sources utilised by experts and novices can help determine what specific
information must be learned in order to become an expert on a given task. Such knowledge has
the potential to provide direct implications for the structure of instruction and the provision of
feedback. Third, studying the life histories and practice experiences of experts can aid
identification of factors critical to becoming an expert. Isolating these factors also has the
potential to provide information of both theoretical and practical significance regarding skill
learning (Abernethy, in press).
Understanding gained about the limiting factors to task performance, about the distinguishing
patterns of information usage by experts, and about factors necessary but not sufficient for the
attainment of expertise can be potentially help not only in the design of training but also in the
design of superior workspaces and task configurations (e.g., Noyes et al., 1996) and, through
cognitive emulation (Slatter, 1987), in the development of expert systems. [Expert systems are
artificially intelligent computer programs that use a body of knowledge to substitute for human
operators in the performance of difficult or dangerous tasks (Hoc et al., 1995; Leibowitz, 1990).]
Examples also exist of how identification and understanding of discrete stages in the transition
from novice to expert can be used to directly guide decisions about career structuring and
continuing education in professional workgroups such as nurses (Benner, 1984; Dreyfus &
Dreyfus, 1986).
Reciprocally, research in the workplace has much to potentially offer those interested in
enhancing generic understanding of expertise. Given the experience that workers accrue over the
duration of a career, the study of workplace skills offers researchers access to experts with levels
of practice that may be greater than those found amongst performers in some of the other
domains (chess, music and sport in particular) that have, to date, attracted substantially more
research attention. It is germane, in this context, to recognise that some of the more influential,
early studies on practice and learning (e.g., Bryan & Harter, 1899; Crossman, 1964) indeed came
from the study of workplace skills.
2. ELEMENTS OF EXPERTISE
The remainder of this paper provides a brief overview of what is known currently about
expert-novice differences in some of the key processes underpinning the production of skilled
actions of the type needed in the workplace. The overview is organised in terms of the major
processing components of sensation, perception, cognition, action, attention and feedback,
typically represented in traditional information-processing/stage models of human
performance (e.g., Kantowitz, 1989; Stelmach, 1982). Such stage models form a useful
heuristic for the organisation of the body of knowledge although there is considerable debate
as to how well such approaches actually represent perception and action in practice (Carello et
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al., 1984) or indeed how well they assist in forward conception of expertise (Abernethy,
Burgess-Limerick & Parks, 1994). Within each of the sections that follow consideration is
given to key findings on the nature of expert-novice differences (if any) within each of the
performance components, key methodologies used to elucidate the differences, and the
possible ramifications of this knowledge for practicing ergonomists.
Expert-Novice Differences in Sensory Information Processing: The sensory receptors
within the human body (e.g., sophisticated receptors such as the retina in the eyes) are
responsible for transducing selected physical signals in our surrounding environment (e.g.,
light waves) into nerve impulses that may be processed and interpreted by our brain and
nervous system. Given that there are significant individual differences in the acuity of
different sensory receptors, and that it is obviously impossible to respond adequately to
signals that cannot be reliably sensed, there has been considerable research interest in
documenting the range of human sensory capabilities and in examining whether individual
variability in these capabilities is, in any way, systematically related to task performance.
Such research typically involves the examination of basic sensory properties using
standardised test protocols and generic stimuli such as the letter recognition tasks and
checkerboard resolution tasks used in the optometric assessment of static visual acuity.
The research to date on sensory information processing supports two conclusions, each of
which has significant implications for the ergonomist. The first, unsurprising, conclusion is
that poor sensory reception can limit performance - people with visual defects perform poorly
on tasks that require high visual resolution; people with impaired vestibular sensation perform
poorly on tasks (such as flying) that require precise and rapid adjustments of whole-body
orientation. Such an observation clearly suggests an important place for occupational
screening of essential sensory properties and, where defects are observed, a place for
correction (as in the case of hearing aids for auditory deficits). If occupational screening is to
be undertaken however it would appear imperative that the screening protocols used be
carefully selected in relation to the task to be undertaken. For example, using static visual
acuity screening tests for tasks, like car driving, that require dynamic visual information pickup may be of limited utility, especially when the correlation between individual differences in
dynamic and static visual acuity is poor.
A second, perhaps less obvious, conclusion from the research to date on basic sensory
properties is that experts are not systematically characterised by supra-normal sensory skills.
In the main, the basic sensory properties of the expert, when assessed using standardised
means, are indistinguishable from that of the remainder of the population. Consequently
approaches that attempt to improve task performance through generalised sensory training
(such as the generalised visual training approaches advocated by many behavioural
optometrists) are unlikely to be effective because they address a facet of performance that is
not typically the limiting factor. Controlled studies of generalised visual training in sport, for
instance, support the contention that while it is possible to enhance some aspects of basic
sensory functioning through repetitive practice this does not then translate to enhanced sports
performance (Abernethy et al., 2001; Wood et al., 1997). The same is likely to hold true for
most work tasks.
Expert-Novice Differences in Perception: Perception is the active interpretation of raw
sensory information for the purposes of decision-making and responding. Perception is taskspecific and measures of perception that are task-relevant reveal significant individual
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differences that are systematically related to the level of expertise. Experts across a range of
domains, including ergonomics, show, relative to lesser skilled individuals, superior capacity
to discriminate different perceptual events (Blignaut, 1979), superior capacity to recognise
patterns from within but not beyond their domain of expertise (Chase & Simon, 1973; Fiore et
al., 2000; Howard & Kerst, 1981), and a superior capacity to anticipate forthcoming events on
the basis of limited preview information (Abernethy, Wann & Parks, 1998). Approaches
combining visual simulations with methodologies such as temporal and spatial occlusion of
selective display features have demonstrated that these differences in pattern recognition and
anticipation are due to the capacity of the experts to utilise different, and additional, sources
of information to that which novices are able to use (Abernethy, 1999; Abernethy et al.,
2001).
The findings from studies measuring eye movement behaviour (visual search patterns) are
less systematic. A number of studies demonstrate significant expert-novice differences in
both the location and duration of the ocular fixations made while undertaking domain-specific
tasks (e.g., Bellenkes et al., 1997; Kundel & LaFollette, 1972); others however fail to
demonstrate systematic expertise-related differences or demonstrate differences in
information pick-up that are not matched by differences in visual search strategy (Abernethy,
1988, 1990; Helsen & Pauwels, 1993). This latter observation suggests that it is seeing (the
active processing and interpretation of visual information) rather than looking (the orientation
of the eyes to different parts of the display) that is the limiting factor to expert perception.
The evidence available makes a strong case for the potential to enhance the acquisition of
expertise through systematic and strategic training of pattern recognition and through
instructional approaches directing selective attention to key information sources. There is
some promising preliminary evidence, primarily from sports tasks, that key perceptual
attributes can indeed be trained, with particular evidence for the beneficial role of video-based
training in hastening the acquisition of anticipatory skill (Starkes & Lindley, 1994; Williams
& Grant, 1999). A major challenge to the acceleration of perceptual skill development,
however, lies with the fact that perceptual expertise appears to be largely acquired implicitly,
without the direct conscious (or verbalisable) knowledge of the performer (Magill, 1998;
Merikle, 1992).
Traditional approaches, relying heavily on verbal instruction and
concentrated explicit attention to key learning features, may therefore be contraindicated and
alternative approaches will need to be developed. There is a less compelling case at this time
for attempting to have lesser skilled performers learn by modelling the visual search patterns
of experts and indeed the few studies which have attempted to do so have reported only very
modest success (e.g., Papin, 1984).
Expert-Novice Differences in Cognition: Studies of expertise in cognition have utilised a
variety of paradigms from cognitive psychology, including think aloud protocols,
categorisation and re-sequencing tasks, and direct tests of knowledge. Across this body of
work a number of systematic expert-novice differences have emerged. Experts are typically
faster at problem-solving, display superior short-term and long-term memory for material,
have superior knowledge of relevant facts (declarative knowledge) and procedures
(procedural knowledge), see and represent problems at a deeper, more principled, level, and
spend a considerable period of time analysing problems qualitatively before arriving at a
solution (Gilhooly & Green, 1988; Glaser & Chi, 1988; Ye & Salvendy, 1996). The expert’s
advantage is almost always confined to their particular domain of expertise and not
generalisable to other domains.
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There have been some suggestions that the acquisition of skill may be hastened by providing
learners with exposure to the cognitions of experts as they perform the same task or by having
the learners adopt the mental models (procedural knowledge structures) of experts but the
evidence for such approaches being advantageous is scant (but see Bellenkes, 2000). In
practical terms information regarding the knowledge structures of experts is more frequently
used in system’s design. Systems may be configured in such ways as to either facilitate all
users following the decision-making path of the experts (Hanisch et al., 1991) or to remove,
as much as possible, the need for specialist knowledge.
Expert-Novice Differences in Action Production: In tasks that are time constrained and
rapid responding is important, systematic expert-novice differences are generally evident.
Where classical choice reaction time situations are involved (i.e., multiple event options each
with a unique associated correct response) experts typically show faster decision-making
(information-processing) rates although their speed of responding in situations where there is
no uncertainty (simple reaction time) is generally indistinguishable from that of the novice.
The faster information processing rates of experts are likely attributable to superior utilisation
of event probabilities – any advance knowledge of one event being more or less probable than
a competing event reducing the processing load.
Importantly, in both choice reaction time tasks and in tasks that require rapid serial
responding, experts are constrained in the same fundamental way as novices. The essential
relationships between uncertainty and reaction time (the so-called Hick-Hyman Law) and
between inter-signal interval and reaction time (the phenomenon known as psychological
refractory period) are equally robust in experts as they are in novices. The superior
performance of experts in these situations is simply a function of operating more efficiently
within the limits of these inherent processing constraints. The most effective means of
combating these inherent constraints, of course, is through task modification. The use of
highly compatible display configurations and task designs that minimise spatial and temporal
uncertainty are effective, and now commonplace, means of eliminating performance
impairments associated with choice reaction time and psychological refractory period delays
(Proctor & Zandt, 1994; Wickens, 1992).
In terms of actual movement production, both the kinematics (patterns) and kinetics
(underlying forces) of the movements performed by experts display a greater consistency than
is typically evident in the movements of novices. Experts, moreover, more effectively utilise
the external forces (such as gravitational and reactional forces) available within some
movements. This allows experts to restrict their use of muscular force to only those phases in
the movement where it is needed and can be provided effectively (Fowler & Turvey, 1978).
Novices, in contrast, tend to supply muscular force more or less continuously throughout a
movement, often in opposition to, or as an unnecessary supplement to, external forces. With
practice, the underlying neuromuscular recruitment patterns become more discrete as
muscular effort is recruited more efficiently. This efficiency underpins the greater fatigue
resistance and ease of movement often described in relation to expert performance.
Concomitantly, the acquisition of expertise is also frequently accompanied by a transition from
initial freezing of many joints, through co-contraction of antagonist muscle groups, to a state of
increasingly independent control over joints distant from the prime movement (Vereijken et al.,
1992). This progressive freeing of degrees of freedom in movement control permits the subtlety
of movement control inevitably associated with the motor performance of the expert. Expertnovice differences in movement control are frequently explicable in terms of the expert’s
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movement pattern being more biomechanically efficient and this holds true for ergonomic tasks
as fundamental as those involved in manual lifting and materials handling (Gagnon, 1997;
Gagnon et al., 1996). Some attempts have been made to provide feedback on selected movement
kinematics, kinetics or neuromuscular recruitment patterns as a means of accelerating the
learning of expert movement patterns but as yet there is limited evidence to demonstrate that this
is effective (Schmidt & Lee, 1999).
Expert-Novice Differences in Attention: It is well documented that one of the defining
characteristics of experts is their increased automatisation of actions and their corresponding
capacity to apparently handle two or more tasks concurrently with relative ease (Schneider &
Fisk, 1983). In the workplace the automatisation of action is best demonstrated through the
use of dual-task methodologies. As the name implies, the dual-task method requires people to
undertake two tasks simultaneously – a primary task, which is typically the fundamental work
task of interest, and a secondary task, which may be a reaction time task, a verbal-cognitive
task or another motor task. The dual-task method requires that performance on the primary
task be given priority (such that primary task performance remains at the same level in the
dual condition as it does when performed alone). If this instructional condition is followed
then performance on the secondary task can be used to measure (i) the overall attentional
demand of the primary task (more difficult tasks will be associated with poorer secondary task
performance), (ii) temporal variation in the attentional demands of the primary task (peak
attention demands in the primary task are more or less contemporaneous with troughs in
performance on the secondary task), and (iii) the relative attentional demands that common
primary tasks place upon different people (Abernethy, Summers & Ford, 1998).
Dual-task methods have been used extensively in ergonomics (Wickens, 1992) with
consistent demonstration of superior dual-task performance by experts (e.g., Brouwer et al.,
1991). Increased automatisation of primary task movement control by experts creates a
significant functional advantage for them in being able to attend simultaneously to other
surrounding events or concurrent tasks. Automatisation of action is not without its drawbacks
however – among these are a greater propensity for automised errors, a reduced conscious
awareness of control, and greater resistance to skill modification or correction of ‘in-grained’
movement patterns (Reason, 1990). Interestingly, attempts to reduce task workload by
mechanical automation (e.g., by the inclusion of automated aids and decision support tools in
aircraft cockpits; Mosier et al., 1997) are also not unproblematic.
Expert-Novice Differences in Feedback Utilisation: There is some evidence (Glaser & Chi,
1988) that experts are superior at self-monitoring i.e., they are highly skilled in detecting (and
correcting) errors in their own skill production. Novices, in contrast, are highly dependent
upon external feedback as the principal basis for error detection and correction. In many
ergonomic settings, tasks and machinery are configured so as to provide feedback signals
(e.g., warning signals when particular bandwidths of error tolerance have been infringed),
thereby removing the demand for human feedback monitoring and, in large part, negating the
expert advantage. However, in situations where such feedback provision is not built into the
task design, facilitating the development of expert-like self-monitoring may be important.
While the existing training dogma is that feedback is essential for learning and the more
feedback the better, the regular inclusion of no-feedback practice trials within the skill
learning schedule may well be important as a means of fostering skilled capabilities to utilise
intrinsic forms of feedback information.
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3. SOME CONCLUDING COMMENTS
While much is now known about the characteristics that distinguish expert performers from
lesser skilled ones, knowledge about how to possibly facilitate the transition from novice to
expert is still largely based upon inference. In an era where evidence-based practice is
rightfully increasingly seen as important, there is a clear need (and opportunity) for
systematically examining the efficacy of the kind of interventions to training, task design and
systems development that an expertise model might suggest. There are many compelling
reasons for practicing ergonomists to remain conversant with advances in the expertise field,
just as there are for expertise researchers to look increasingly at the workplace as an attractive
venue for advancing both practical and theoretical understanding of expert performance.
4. ACKNOWLEDGMENTS
The ideas presented here have been shaped by discussions (both formal and informal) over
many years with colleagues and postgraduate students – although any errors in interpretation
are mine not theirs. The funding support of the Australian Research Council, Worksafe
Australia, and the Australian Sports Commission is greatly appreciated.
5. REFERENCES
Abernethy, B. 1988. Visual search in sport and ergonomics: Its relationship to selective attention
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Abernethy, B. 1990. Expertise, visual search and information pick-up in squash. Perception 19:
63-77.
Abernethy, B. 1993. Searching for the minimal essential information for skilled perception and
action. Psychological Research 55: 131-138.
Abernethy, B. 1999. The 1997 Coleman Roberts Griffith Address. Movement expertise: A
juncture between psychology theory and practice. Journal of Applied Sport Psychology 11:
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Abernethy, B. in press. Sports as expertise, psychology of. In N.J. Smelser, and P.B. Bates
(Eds.), International Encyclopedia of the Social & Behavioral Sciences. Oxford, UK: Elsevier.
Abernethy, B., Burgess-Limerick, R.J. and Parks, S. 1994. Contrasting approaches to the study
of motor expertise. Quest 46: 186-198.
Abernethy, B., Gill, D., Parks, S.L., and Packer, S.T. 2001. Expertise and the perception of
kinematic and situational probability information. Perception 30: 233-252.
Abernethy, B., Summers, J.J. and Ford, S. 1998. Issues in the measurement of attention. In J.L.
Duda (Ed.), Advancements in sport and exercise psychology measurement. Morgantown, WV:
FIT Press. pp. 173-193.
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Abernethy, B., Wann, J.P., and Parks, S. 1998. Training perceptual-motor skills for sport. In
B.C. Elliott (Ed.), Training in sport: applying sport science. Chichester: Wiley. pp.1-68.
Abernethy, B. and Wood, J.M. 2001. Do generalised visual training programs for sport really
work? An experimental investigation. Journal of Sports Sciences 19: 203-222.
Bellenkes, A.H. 2000. The use of expert pilot performance models to facilitate cockpit visual
scanning training. Unpublished doctoral dissertation, University of Illinois at Urbana,
Champaign.
Bellenkes, A.H., Wickens, C.D., and Kramer, A.F. 1997. Visual scanning and pilot expertise:
the role of attentional flexibility and mental model development. Aviation Space and
Environmental Medicine 68: 569-579.
Benner, P. 1984. From novice to expert: excellence and power in clinical nursing practice.
Addison-Wesley, Menlo Park, CA.
Blignaut, C.J.H. 1979. The perception of hazard. II. The contribution of signal detection to
hazard perception. Ergonomics 22: 1177-1185.
Brouwer,W.H., Waterink, W., van-Wolffelaar, P.C., and Rothengatter, T. 1991. Divided
attention in experienced young and older drivers: Lane tracking and visual analysis in a
dynamic driving simulator. Human-Factors 33: 573-582.
Bryan, W.L. and Harter, N. 1989. Studies on the telegraphic language: The acquisition of a
hierarchy of habits. Psychological Review 6: 345-375.
Carello, C., Turvey, M.T., Kugler, P.N., and Shaw, R.E. (1984). Inadequacies in the computer
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Crossman, E.R.F.W. 1964. Information processes in human skill. British Medical Bulletin
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Dreyfus, H.L., and Dreyfus, S.E. 1986. Mind over machine: The power of human intuition and
expertise in the era of the computer. New York: Free Press.
Ericsson, K.A., Krampe, R.T. and Tesch-Romer, C. 1993. The role of deliberate practice in
the acquisition of expert performance. Psychological Review 100: 363-406.
Fiore, S.M., Jentsch, F., Oser, R.L. and Cannon-Bowers, J.A. 2001. Perceptual and conceptual
processing in expert/novice cue pattern recognition. International Journal of Cognitive
Technology 5: 17-26.
Fowler, C.A. and Turvey, M.T. 1978. Skill acquisition: An event approach with special reference
to searching for the optimum of a function of several variables. In G.E. Stelmach (Ed.),
Information processing in motor control and learning. New York: Academic Press. pp. 1-40.
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Gagnon, M. 1997. Box tilt and knee motions in manual lifting: two differential factors in expert
and novice workers. Clinical Biomechanics 12: 419-428.
Gagnon, M., Plamondon, A., Gravel, D. and Lortie, M. 1996. Knee movement strategies
differentiate expert from novice workers in asymmetrical manual materials handling.
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Gilhooly, K.J. and Green, A.J.K. 1988. The use of memory by experts and novices. In A.M.
Colley, & J.R. Beech (Eds.), Cognition and action in skilled behaviour. Amsterdam: NorthHolland. pp. 379-395.
Glaser, R.and Chi, M.T.H. 1988. Overview. In M.T.H. Chi, R. Glaser and M.J. Farr (Eds.), The
nature of expertise. Hillsdale, NJ: Erlbaum. pp. xv-xxviii.
Hanisch, K.A., Kramer, A.F., and Hulin, C.L. 1991. Cognitive representations, control, and
understanding of control systems: a field study focusing on components of users’ mental
models and expert/novice differences. Ergonomics 34: 1129-1145.
Helsen, W. and Pauwels, J.M. 1993. The relationship between expertise and visual
information processing in sport. In J.L. Starkes and F. Allard (Eds.) Cognitive issues in motor
expertise. Amsterdam: Elsevier. pp. 109-134.
Hoc, J-M., Cacciabue, P-C. and Hollnagel, E. (eds). 1995. Expertise and technology:
Cognition and human-computer interaction. Hillsdale, NJ: Erlbaum.
Howard, J.H. and Kerst, S.M. 1981. Memory and perception of cartographic information on
familiar and unfamiliar environments. Human Factors 23: 495-504.
Leibowitz, J. 1990. The dynamics of decision support systems and expert systems. Chicago:
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Kantowitz, B.H. 1989. The role of human information processing models in system
development. Proceedings of the Human Factors Society 33rd Annual Meeting, pp. 979-983.
Kundel, H.L. and La Follette, P.S. 1972. Visual search patterns and experience with
radiological images. Radiology 103: 523-528.
Magill, R.A. 1998. Knowledge is more than we can talk about: Implicit learning in motor
skill acquisition. Research Quarterly for Exercise and Sport 69: 104-110.
Merikle, P. 1992. Perception without awareness: Critical issues. American Psychologist 47:
792-795.
Mosier, K.L., Skitka, L.J., Heers, S., and Burdick, M. 1997. Automation bias: decision
making and performance in high-tech cockpits. International Journal of Aviation Psychology
8: 47-63.
Noyes, J.M., Starr, A.F., and Frankish, C.R. 1996. User involvement in the early stages of the
development of an aircraft warning system. Behaviour & Information Technology 15: 67-75.
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Papin, J-P. 1984. Use of the NAC Eye Mark by radiologists. In A.G. Gale and F. Johnson
(Eds.). Theoretical and applied aspects of eye movement research. Amsterdam: NorthHolland.
Proctor, R.W. and Van Zandt, T. 1994. Human factors in simple and complex systems.
Boston, MA: Allyn and Bacon.
Reason, J.T. 1990. Human error. Cambridge, UK: Cambridge University Press.
Schmidt, R.A. and Lee, T.D. 1998. Motor control and learning: A behavioral emphasis. (3rd
ed.). Champaign, IL: Human Kinetics.
Schneider, W. and Fisk, A.D. 1983. Attention theory and mechanisms of skilled performance.
In R.A. Magill (Ed.). Memory and control of action. Amsterdam: North-Holland. pp. 119143.
Slatter, P.E. 1987. Building expert systems: Cognitive emulation. Chichester, UK: Ellis
Horwood.
Starkes, J.L. and Lindley, S. 1994. Can we hasten expertise by video simulations? Quest 46:
211-222.
Stelmach, G.E. 1982. Information-processing framework for understanding human motor
behavior. In J.A.S. Kelso (Ed), Human motor behavior: An introduction. Hillsdale, NJ:
Erlbaum, pp. 63-91.
Vereijken, B., Emmerik, R.E.A. van, Whiting, H.T.A., and Newell, K.M. 1992. Free(z)ing
degrees of freedom in skill acquisition. Journal of Motor Behavior 24: 133-142.
Wickens, C.D. 1992. Engineering psychology and human performance (2nd ed.). New York:
Harper Collins.
Williams, A.M. and Grant, A. 1999. Training perceptual skill in sport. International Journal
of Sport Psychology 30: 194-220.
Wood, J. and Abernethy, B. 1997. An assessment of the efficacy of sports vision training
programs. Optometry and Vision Science 74: 646-659.
Ye, N. and Salvendy, G. 1996. Expert-novice knowledge of computer programming at different
levels of abstraction. Ergonomics 39: 461-481.
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Ron Cumming Memorial Lecture
Are Ergonomics, Economics and Ethics Mutually Exclusive?
Maurice Oxenburgh
Consultant and Guest Research Scientist at the National Institute for Working Life
(Sweden)
ABSTRACT
As ergonomists we need to be aware of our clients’ economy – will our
recommendations improve working conditions and be cost effective? We need
also to be aware of ethics – are we improving the health of workers or just
pleasing the client (we need to eat too)?
In Dr Oxenburgh’s first book that dealt with cost effectiveness in ergonomics
interventions the question arose that if the intervention is not cost effective, do we
not do it? In his forthcoming book (written in collaboration with Pepe Marlow
and Andrew Oxenburgh) and the subject of his lecture, he deals with this apparent
conundrum.
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Getting to Zero-Lift in Washington State Nursing Homes:
Researching an Intervention
Kathleen A. Rockefeller
SHARP, Washington State Department of Labor & Industries, Olympia WA
Barbara A. Silverstein
SHARP, Washington State Department of Labor & Industries, Olympia WA
Keywords: nursing homes, resident handling, ergonomics, intervention research
ABSTRACT
Researchers in occupational safety and health strive to identify and quantify risks
for people at work, while practitioners try to bring about changes in the work
environment to improve working conditions. What appears efficacious in the lab
or in theory may not always be effective in practice. Careful intervention research
plays an important role in attempts to understand this gap. Yet the opportunity to
study industry wide interventions is all too rare. This paper describes an
intervention study in Washington State that took advantage of a unique
opportunity for government and industry to work together in an attempt to address
an important health and safety problem. The goal of the study was to assess the
implementation of zero-lift programs in nursing homes across the state and to
evaluate changes in the incidence and severity of injuries to employees,
particularly nursing assistants (NACs). Sources of data and methods of collection
will be described, along with a discussion of the process and initial results.
1. INTRODUCTION
As knowledge about exposure to risk factors for work-related musculoskeletal disorders
increases, occupational safety and health practitioners should try use this information to
design and implement effective interventions in order to decrease exposure. Indeed, the
National Occupational Research Agenda (NORA) musculoskeletal group identified
intervention studies of engineering controls and work organization improvements as a high
priority. Yet, intervention research is difficult to do and presents numerous potential problems
and pitfalls. Schulte et al (1996) suggest that the challenge inherent in intervention research is
to conduct studies that remain credible where rigorous experimental research methods are not
feasible. Some of these methodological problems include: lack of a contemporaneous control
or comparison group; lack of randomization; lack of a placebo intervention; low statistical
power; concerns about reliability and validity of measures; secular trends not accounted for;
and traditionally low participation and/or follow up rates.
A few additional concerns should be mentioned. Ideally, evidence of intervention efficacy
exists prior to studying its effectiveness. There should be a logical mechanism by which the
intervention is proposed to work. There should also be an explicit model outlining the
proposed process by which the intervention might work. Without a model based on theory and
evidence of efficacy, understanding about how an intervention works (or, perhaps more
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importantly, does not work) is limited. Working with a model helps to target an intervention
to specific problems and specific audiences and to suggest what data is needed and methods
for data collection.
The intervention described here was designed to target the high rates of injury reported by
personnel in nursing home facilities. Caring for others is important and demanding work.
Among nursing personnel, high rates of musculoskeletal injuries have consistently been
reported. These injuries, in turn, appear to be related to patient (resident) handling activities.
Biomechanical research presents strong evidence that the physical act of patient handling
results in forces the on lumbar spine of the handler that are capable of causing tissue damage.
There is additional evidence that reducing these loads on the low back would decrease the risk
of injury. To this end, the use of mechanical lifting devices has been encouraged as one means
to decrease exposure to these potentially injurious loads. The philosophy of using equipment
to minimize the lifting of patients has been termed “zero-lift.”
Long-term care facilities, or nursing homes, in Washington State have reported a high
incidence and severity of work-related musculoskeletal disorders among their employees. The
Department of Labor & Industries (L&I), a Washington State agency, manages the State’s
exclusive workers’ compensation system. All employers pay into a state fund, with the
exception of those who have qualified for self-insured status. The Department also manages
the OSHA plan for the State. The Safety and Health Assessment & Research for
Prevention (SHARP) group is located within Labor & Industries, and is charged with
researching occupational safety and health concerns, as well as serving as a knowledge
resource for the agency.
In keeping with its stated goal of reducing work-related hazards, illnesses, and injuries, Labor
& Industries developed the Hazard Impact Partnership (HIP) to work with employer
groups on strategies to decrease hazards in the workplace and to reduce injuries. Agency data
was used to help set priorities by identifying industries with high rates of workers’
compensation claims. Since nursing homes had very high rates and counts for work-related
musculoskeletal disorders, the industry became the first target for a HIP initiative.
The initiative was composed of several strategies. The primary strategy was a financial
incentive to encourage nursing homes to invest in better lifting equipment and to implement
zero-lift programs. Labor & Industries offered a one-time, up-front, 15% discount on workers’
compensation premiums to nursing homes that applied for the discount and agreed to its
requirements. In return, the facilities would use the funds saved to purchase equipment and to
implement related policies, procedures, and training.
The study thus took advantage of a unique opportunity for government and industry to work
together in an attempt to address an important health and safety problem. The short-term
goal of the intervention was to encourage nursing home facilities to invest in equipment for
resident handling as well as to implement the components of zero-lift programs. The desired
long-term outcome was a reduction in the incidence and severity of work-related
musculoskeletal disorders among employees in nursing homes, particularly nursing assistants
(NACs). The underlying model for the intervention is illustrated in Figure 1. Table 1
describes the five hypothesized primary components of a successful zero-lift environment,
and with their key elements. Data collection sought to obtain information on these
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components, in order to study the importance of their respective contributions to the outcomes
of the intervention.
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TABLE 1: ZERO-LIFT: FIVE PRIMARY COMPONENTS AND KEY ELEMENTS
1. EQUIPMENT

Have an adequate # of total lifts, sit-to-stand lifts, and other
devices to suit the resident population and staff AND/OR have
defined and approved plans to obtain such equipment

Have an adequate # of repositioning devices (e.g., low-friction
“slipp” sheets, etc.)

Processes in place for:
o
Keeping equipment easily accessible to
staff
o
Keeping equipment charged & in good
working condition
o
Sling cleaning and inspection
o
Equipment maintenance
2. TRAINING

Training on equipment is developed and integrated into overall
training and staff development plan

Training includes “hands on” practice with
opportunities for feedback and coaching

Training on equipment is part of orientation AND regular on-going
sessions

Regular skills check are conducted

ALL nursing staff know how to use equipment (not just NACs)

Strategies for managing difficult residents
offered

Assessment of resident function takes into
account availability of equipment

Up-to-date information on transfer status
easily available to NACs
3. POLICIES, PROCEDURES, ENFORCEMENT

Have policies and procedures for resident handling, including
expected use of equipment
o
All employees aware of policies
o
Employees follow policies and procedures
o
System is in place for correction and coaching; progressive
discipline as appropriate
4. INJURY INVESTIGATIONS AND MEDICAL CASE MANAGEMENT
o
Accidents are investigated to better understand how they
occurred
o Facility actively involved with the medical
case management of workers who are injured
o
If a third party administrator (TPA) is involved, they know about
the equipment available at facility
o Alternative “light” duty work available
o
Physicians know about the equipment available at facility
5. MANAGEMENT COMMITMENT AND EMPLOYEE INVOLVEMENT

Funds allocated in the budget for zero-lift program, both for
start-up and on-going

Employees, especially NACs, are involved with
design and implementation of zero-lift

Management team understands and supports concept of
zero-lift

Employees, especially NACs, are involved with
selection of equipment

Someone is accountable for zero-lift program

Employees understand and support concept of
zero-lift
2. METHODS
The primary sources of data for the study are listed below:
1. Written surveys were developed in order to assess the degree of implementation of
zero-lift programs in Washington State. Surveys were mailed to all long-term care
facilities in the state meeting the study definition (n=257, 252, and 245 for Years 1, 2,
and 3, respectively). The Year 1 survey was considered the baseline survey. Both
quantitative and qualitative data were obtained from responses to the surveys.
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2. Site visits to facilities were conducted at baseline and one year follow-up to assess the
reliability of survey responses and to obtain more in-depth information about resident
handling policies, procedures, and programs. Visits were conducted at the facilities
receiving the financial incentive (“premium discount” n=34) and at a group of
facilities not targeted for the incentive (“comparison” n=20). Interviews were
conducted with a number of employees (administrator or director of nursing services,
staff development coordinator, members of the safety committee, and nursing
assistants). Interviews were focused on obtaining information about resident handling
practices at the facilities; however, interviewers also probed for additional information
about the overall environment at the facility. Again, both quantitative and qualitative
data were obtained, with the interviews providing a particularly rich source of
qualitative data.
3. Work sampling observations, using the PATH (Posture, Activity, Tools, Handling)
method of work analysis, were recorded at sub-samples of both premium discount
(n=8) and comparison facilities (n=8). This was done to learn more about the exposure
to postures and tasks during normal work activities.
4. Since nursing assistants are the targeted “end users” for using equipment to handle the
residents in their care, we wanted to learn more from the nursing assistants themselves
about their feelings and beliefs regarding the use of mechanical transfer equipment.
The theory of planned behavior, as suggested by Ajzen (1980), supplied a feasible
model to investigate the perceptions of the nursing assistants, and a survey was
designed utilizing a framework derived from the model. Although the low response
was disappointing, this part of the evaluation provided some intriguing information
and ideas for further research.
5. Finally, data about the incidence and severity of work-related musculoskeletal
disorders among nursing home employees were obtained from the workers’
compensation database at Labor & Industries.
3. RESULTS
The response rates for the surveys were 85%, 96%, and 91%, respectively. From the surveys,
a picture of zero-lift environments across the state was obtained.
A. EQUIPMENT
Over the three-year period of the study, there was an overall marked increase in the amount of
mechanical equipment available for handling residents in nursing home facilities in
Washington State. As expected, the amount of older manually operated equipment decreased
over the same time frame.
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TABLE 2: DESCRIPTIVE STATISTICS OF NUMBER OF PIECES OF EQUIPMENT
REPORTED IN THREE STATEWIDE SURVEYS
1998
1999
2000
MEANS & STD DEV
mean
sd
mean
sd
mean
sd
1.39
1.42
1.28
1.53
0.93
1.30
Hand operated total lifts
1.09
1.52
1.71
1.76
1.95
1.70
Mechanical total lifts
0.34
0.81
0.83
1.41
1.22
1.57
Sit-to-stand lifts
When the facilities in the premium discount group were compared to all other facilities, the
reported changes were more marked in the discount group, and the difference between the two
groups was statistically significant.
TABLE 3: MEAN NUMBER OF PIECES OF EQUIPMENT IN THREE ANNUAL
SURVEYS REPORTED BY THE TWO STUDY GROUPS
hand operated total lifts mechanical total lifts
sit-to-stand lifts
S1
S2
S3
S1
S2
S3
S1
S2
S3
1.47
0.94
0.58
0.87
1.88
premium discount
2.48 0.17
1.91
2.73
1.38
1.34
0.99
1.13
1.68
all others
1.86 0.37
0.65
0.96
B. POLICIES
The presence of policies and procedures is part of standard operations in long-term care
facilities, and is required for licensure. In our surveys and visits, there may have been some
definitional uncertainly over what constituted a “policy” versus a “procedure” – often, this
was defined differently at different facilities, and by different ownership. ALL facilities
reported some sort of “standard practice” with respect to handling residents, whether or not
this was also termed a policy or procedure. All facilities also reported mechanisms for dealing
with unsafe or undesirable actions of employees. Over time, it was seen that as the types of
pieces of equipment increased, so did the tendency to state that there were “policies” covering
its usage; e.g., if a facility had no sit-to-stand lifts, it would not report having a policy
addressing this type of equipment. Once equipment was obtained, then policies were
developed and implemented. By Survey 3, the majority of facilities rated themselves as
having most of the elements of the policy component.
C. TRAINING
Like policies and procedures, training of employees is required and is basically built into
standard operating procedures. As practices change (e.g., a new piece of equipment is
obtained, new regulations introduced), it is expected that employers will train employees. In
Survey 3, the majority of the facilities rated themselves as having most of the elements of the
training component.
D. MANAGEMENT COMMITMENT AND EMPLOYEE INVOLVEMENT
This component continued to be an elusive one to capture in measures. Over the three years of
the study, it became increasingly apparent that the turnover of management personnel
(particularly the administrator, director of nursing services, and staff development
coordinator) was related to an atmosphere of stability versus turmoil at a given facility.
Management turnover tended to have a destabilizing effect on programs at a facility,
including zero lift. Anecdotally, this was expressed by the risk manager for a chain of
facilities with seven nursing homes in the premium discount group. He stated that every time
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there was a change in personnel, he needed to visit the facility to build up support (again) for
the zero-lift program.
E. WORK SAMPLING OBSERVATIONS
The primary task of interest was resident handling. Activities related to this task were defined
as “hands on” activities occurring while transferring and repositioning residents, changing
their clothes, or administering peri-care. At baseline, for all facilities combined, resident
handling accounted for 22.8% of the task observations. Other activities related to caring for
residents accounted for another 45.1% of the observations. Clearly, the majority of the
nursing assistant’s time is spent in direct care of residents.
Postures of the back and shoulder were more likely to be non-neutral during resident handling
than any other category of task. With respect to exposure to multiple risk factors at once,
postures while handling loads were examined. When nursing assistants were handling loads of
more than 23 kgs, back postures were likely to be non-neutral, and this exposure was more
likely to occur during resident handling than during any other task.
F. NAC SURVEY
According to the theory of planned behavior, a person’s beliefs about the outcomes of a
behavior will have an effect on the likelihood of the behavior occurring. Nursing assistants
were asked about the likelihood of the following outcomes associated with the use of
equipment to handle residents in their care.
TABLE 4: LIKELIHOOD OF BEHAVIORAL BELIEFS OF NURSING ASSISTANTS
How likely or unlikely is it that
very
somewhat somewhat
very
using mechanical transfer
likely likely likely
equipment to move residents will: unlikely unlikely unlikely
take more time? 5.6
7.5
8.8
24.4
30.0
23.8
be uncomfortable for resident? 5.7
17.2
14.6
40.8
14.0
7.6
decrease chance of hurting my back? 5.0
6.9
2.5
8.1
18.8
58.8
be noticed by my supervisor? 8.6
15.2
14.6
16.6
27.2
17.9
require help from my coworkers? 8.9
21.0
12.7
18.5
19.1
19.7
Frequency of responses in category
It has been suggested that feelings of self-efficacy, or beliefs about one’s ability to perform a
given behavior, are also important determinants of behavior. The nursing assistants were
asked a numbers of questions about their perceived abilities to handle situations associated
with the use of equipment to handle residents in their care. Overall, they indicated feeling
quite confident when the situation required their own personal knowledge and skills (knowing
how to use the equipment and being able to explain to residents what they were doing), but
were less confident when the situation involved factors more out their immediate control,
such as being able to find the equipment when needed.
So, while the low response limits the ability to generalize, the results of this survey contain
some intriguing clues and avenues for further investigation. For example, the data suggested
that supervisors and coworkers might not provide as important motivation for the use of
equipment as is sometimes suggested. In addition, it appears that barriers to use of the
equipment as perceived by the nursing assistants differ from those perceived by management
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personnel; for example, while the issue of requiring more help is frequently suggested as a
problem by management, a good 43% of the nursing assistants felt the use of lifting
equipment would be unlikely to require more help from coworkers.
G. WORKERS’ COMPENSATION DATA
Data on injury claims filed by workers in nursing homes were extracted from the workers’
compensation database at Labor & Industries. Trends for incidence and severity were
analyzed and compared. Initial results were encouraging and further analysis is currently
underway.
The risk manager for a chain of nursing homes that had facilities in the premium discount
group shared information about their individual results. Payback on their investment in
appeared to take place within 6-12 months after receipt of the funds.
4. DISCUSSION
Implementation of a zero-lift environment requires both the requisite equipment and an
atmosphere where its use is expected and facilitated. If the presence of equipment is to have a
chance at affecting risks of injury, the equipment must be used correctly and consistently.
It is important to consider environmental barriers to the implementation of health and safety
programs. The long-term care industry is currently in a state of constant pressure and change.
Maintaining adequate staffing is a severe challenge. High rates of turnover of both
management and staff make it difficult for programs to achieve stability. Residents are sicker
and reimbursement levels are less.
Individuals in the industry perceive a number of critical barriers to decreasing injuries related
to resident handling. Researchers and practitioners need to understand these views from the
perspective of those in the industry if efforts to improve working conditions are to be
successful. Attempting to address these barriers will take creativity along with relevant data
and participation of employees.
This study attempted to address and minimize some of the problems that can plague
intervention research.
“GETTING TO ZERO” STUDY
Had a comparison group
No randomization
Two other interventions offered & studied
Job modification
Distribution of information on zero-lift (video package)
Low statistical power
Adequate statistical power
Reliability and validity of measures Mixed; some stronger than others
Secular trends not accounted for
Workers’ compensation data available for analysis of trends
Low participation and follow-up Excellent response rates for surveys
rates
Minimal loss for follow-up site visits
Confounding variables
Controlled in analysis: size of facility, baseline claims rates and
amount of equipment, staffing, geographic region
POTENTIAL PROBLEM
No control or comparison group
No randomization
No placebo intervention
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5. CONCLUSIONS
Nursing home facilities in Washington State did take advantage of a financial incentive to
purchase additional lifting equipment and to implement components of a zero-lift
environment. In theory, the use of these devices should decrease exposure to potentially
injurious forces inherent in resident handling and hopefully decrease injuries to workers in
nursing homes. Although the claims data on injuries need to be followed for a longer period
of time, initial results are encouraging.
The use of qualitative techniques provided insights that would not have been available by the
sole use of quantitative methods. The integration of both quantitative and qualitative
techniques should be encouraged in future studies. Learning more about what key decision
makers consider convincing and adequate evidence would be invaluable to occupational
safety and health practitioners.
Researchers should consider theories of health and safety behaviors as another means to
understanding outcomes in intervention research. In this study, it was people who bought
equipment, enforced policies, conducted training, and used equipment. A better understanding
of the roles of individuals in interventions could improve the ability to design and implement
effective interventions that reach the desired goals.
6. ACKNOWLEDGMENTS
Washington Health Care Association
National Institute for Occupational Safety and Health
Department of Work Environment, University of Massachusetts Lowell
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