Understanding the role of visual cues on human decision making
Anthony Williams, Maya Guest, Leman Figen Gül
Abstract
Injuries associated with manual materials handling (MMH) have increased
considerably and are currently estimated to run to several billion dollars annually
in Australia (Aus$9.5 billion). The aim of the study, reported in this paper, is to
measure and analyse the effectiveness of visual cue and training in manual
handling. This study was undertaken through the application of protocol analysis
which is novel in the Occupational Health and Safety (OH&S) field. An additional
aim of this study was to assess the value of the methodology in OH&S studies
relating to behavioural change. We report on work in progress involving the pilot
study, lifting tasks, the outline of the experimental setting and handling behaviour
coding scheme and initial phase observations.
Introduction
Injuries associated with manual materials handling (MMH) have increased
considerably and are currently estimated to run to several billion dollars annually
in Australia (Aus$9.5 billion). MMH injuries can result from lifting, lowering,
pushing, pulling, or carrying objects, as well as interactions with the environment
(e.g., slipping and falling on a wet floor) while performing activities [1] in many
occupations it is difficult to avoid heavy loads on the back (e.g. lifting, moving
objects).
Whilst most researchers would acknowledge that safe work design is likely to be
the most effective strategy [2], it is not surprising therefore that emphasis has been
given to optimising lifting techniques and ways to manually handle objects to
prevent back pain and injuries [3, 4]. There is a need to reduce the hazards to
which workers are exposed and as such workplace design needs to be optimized.
One such strategy is the use of warning labels. Much research has been conducted
assessing various aspects of warning design and how they affect subjective
evaluation, memory, comprehension and behavioural compliance by human
factor/ergonomic researchers over the past two decades.
According to the warning signal needed, different techniques in the design are
used to capture attention including the use of text, bolding, borders and addition
of colour. Adding colour to a warning can increase its ability to attract attention;
warnings printed in red (compared to black) led to improved notice-ability [5]. In
fact Braun et al [17] found that red conveyed the highest level of perceived hazard
followed by orange, black, green and blue; in an experimental study of
undergraduates using red, green and black warning labels found that the
prevalence of behavioural compliance with the given warning instructions was
highest for the warning printed in red.
A recent strategy by an Australian hardware chain has been to place markers and
visual cues on loads to warn workers and consumers the weight of a heavy object
or a recommendation that a load should be lifted by two persons. Whilst the
intentions of the store are to be applauded to date no empirical studies have been
reported in the peer reviewed literature on the effects of markers or warnings on
the worker or consumer lifting technique in taking the advise provided by the
markers or warnings, i.e behavioural compliance. Therefore, we are undertaking
an experimental study which aims to determine the decision making process prior
to undertaking a manual handling task including the effect of visual cues on
manual handling behaviour using protocol analysis. Protocol analysis, which was
first adopted by Eastman [6] to study design cognition, has been accepted as a
research technique allowing for the clarification of designers’ cognitive abilities [7].
The most common method is the ‘think aloud’ approach which sees participants
being trained to voice their thoughts as they attempt to solve a problem. These
thoughts are transcribed, segmented and coded, then graphs created which chart
the progress of possible cognitive processes through the problem space [8, 9]. The
technique which allows researchers to infer cognitive processes through analysis
of the verbal behaviour of participants [8].
The use of protocol analysis is novel in the Occupational Health and Safety field;
therefore an additional aim of this study is to assess its use in OH&S studies
relating to behavioural change. The aim of this paper is to report on development
work undertaken for a recently conducted pilot study, including the design of the
visual cues, the lifting tasks, experimental setting, handling behaviour coding
scheme and discuss some of our observations.
Design issues for safety in manual handling
Designing for safety is one of the most significant concepts which recognizes the
value of health and safety information in the reduction and prevention of jobrelated injuries, illnesses, and fatalities. Some of the safety design issues are
summarised as follows:
• Lifting Handles
Many studies have been performed using psychophysical methodologies to define
safe load limits for lifting or the maximum acceptable loads of lifts (MAWLs ) [10].
Researchers have reported greater perceived exertion and body discomfort for
lifting boxes without handles than for lifting boxes with handles [11]. Davis et al
[12] conducted an experimental study to accurately evaluate 3-D spine loading as a
function of presence of handles on cases commonly found in an industrial
palletising task and to evaluate handle coupling as a function of the various
positions on the pallet. The results indicated that cases with handles significantly
reduced spinal loading and the importance was particularly relevant for the lower
levels of the pallet where the participants appeared to change the nature of the lift
under the no-handle conditions.
• Box Weights
For manual handling to be cost effective and most efficient a worker must lift as
much weight as physically possible but remain below the tolerance limit of the
lower back. Higher weights would be expected to correlate to higher external
trunk moments. Research has found increases in trunk moments to be associated
with increases in muscle activity and subsequent increases in 3-D spinal loads [13].
Another factor found to affect the external moment is the horizontal moment arm,
which is the distance between the centre of the load and the spine [14]. Marras et al
[15] also found that the combination of moment arm distance (static trunk
moment) and weight was the single most predictive variable of high-risk jobs and
remained an important factor in the multivariate model.
• Centre of Mass
Lifting with and without load knowledge has been well examined for both
symmetrical and asymmetrical lift [16, 17]. If the load characteristics are not known
or incorrectly judged, lifts are likely to be performed more rapidly resulting in
higher moments on the lumbar spine and loss of balance [16, 18]. In a study that
varied the load of centre of mass (CoM) across the frontal plane, both left and
right back extensor muscles were equally active when the CoM was not known
but when the CoM was known the response was specific to the CoM location [17].
It follows that incorrect load knowledge may predispose a lifter to additional risk.
Whereas van Dieen and de Looze [12] found that in the absence of load
knowledge, the trunk muscles show bilateral anticipatory activation. When lifting
a bin (with handles) with varied CoM, highest electromyographic activity for the
upper and lower erector spinae occurred when the load was closest to the body,
regardless of load knowledge. Meyers and Keir [19] concluded that based on their
findings with asymmetrical loads moments acting on the wrist play an important
role in spinal loading.
• Designing Warning Labels
Much research has been conducted assessing various aspects of warning design
and how they affect subjective evaluation, memory, comprehension and
behavioural compliance by human factor/ergonomic researchers over the past
two decades. Wogalter et al [20] highlight the need for a systems approach in the
development, this involves:
• the end-users (e.g. employees);
• organisations who will deploy the warnings and provide the context for use;
and
• product manufacturers who develop the products to which warning labels will
be applied.
For warnings to be perceived as effective they should include the following
components:
• attract attention;
• alert persons to the specific hazard and its degree of seriousness;
• the probable consequence of the hazard; and,
• to the way in which the hazard can be avoided [20, 21].
According to the warning signal needed, different techniques in the design are
used to capture attention including the use of text, bolding, borders and addition
of colour. Adding colour to a warning can increase its ability to attract attention;
warnings printed in red (compared to black) led to improved notice-ability [5]. In
fact Braun et al [17] found that red conveyed the highest level of perceived hazard
followed by orange, black, green and blue; in an experimental study of
undergraduates using red, green and black warning labels found that the
prevalence of behavioural compliance with the given warning instructions was
highest for the warning printed in red.
Methodology
In this pilot of an experimental study the participants are asked to perform a set of
handling tasks whilst “talking-aloud” or verbalising their thoughts on the task
and what is informing their behaviour. It was conducted at the University of
Newcastle, Australia with three research higher degree students. Ethical approval
of the study was granted by the University’s Human Research Ethics Committee.
There were three types of lifting tasks. The first consisted of a large square box
with no natural handles, the second a long thin box which was heavier at one end,
and the third a 17” computer monitor. The objects were located on a hip height
bench with the participants asked to move the objects to an adjacent bench of the
same height.
The two types of interventions and control in the experiments were:
• Manual handling when there is not any visual cue (markers) to act as a control
(NVC),
• Manual handling when there is a visual cue (VC) and
• Manual handling when there are the visual cue and a training intervention
(VCI).
Whilst undertaking a set of lifting and handling tasks the participants were asked
to communicate their impressions and thoughts by talking aloud. Their actions
and verbalisations are video-taped from four as shown in Figure 1.
Following the control lifts the visual cues were placed on the objects. Labels (a) and
(b) were placed on the long thin box of unequal loads. Labels (c) and (d) were
placed on the large box on the top left corner and the right rear corner. Label (a)
was placed on the computer screen.
The visual cues to be used in the experiments are show in Figure 2 below.
[insert figure 1 here]
[insert figure 2 here]
Following the experiments the video files were transferred to two secure
computers for protocol analysis using Noldus Observer software. Each task was
coded independently by two coders. The coding was subsequently compared for
agreement. Where disagreement occurred a process of arbitration is undertaken
for the final protocol. Table 1 shows the process of the protocol analysis.
Table 1. The process of protocol analysis
Development of the coding scheme
Conducting the experiments, having backup copies, obtaining the audio files, and transcriptions
Segmentation and recording the segmentation timings
Encoding: the number of segmentation affects the timing (coder 1-2)
Encoding (second run): The second run in coding has to be conducted by a different coder (coder 1-2)
Comparing the two coding results and performing a process of self arbitration
Statistical analysis: the average time interval, standard deviation …etc.
Inter- Links: recording the links between segments, classifying types of links, represent the density of the links
through time.
Exploring the patterns in the protocols, searching for new models, phenomenon and methods for interpreting the
data that is a continuous process.
The basis for the development of the coding scheme is a consideration of the
expected results of the study. The expected result of the study is that the effective
use of markers on loads would change manual handling behaviour. Thus
measuring the changes in the perception of the workers, handling actions and
problem solving are necessary. A thorough search did not locate any study which
examines the impact of visual cues on manual handling behaviour. Thus we
looked at the theories and other experimental studies of manual handling to
develop the initial coding scheme, as shown in Table 2.
The initial coding scheme that classifies the verbal and the visual information into
three main categories is developed:
• perception,
• the handling action, and
• decision making/ problem solving, as shown in
Table 2. Initial manual handling behaviour coding scheme
Category
Perception
Handling action
Decision making/
problem solving
Colour
Size
Description
Talking about colour of the markers
Talking about size of the markers
Location
Talking about the location of markers
Recall
Semantic
Inspecting
Approaching
Talking about previous knowledge/symbol
Talking about what the markers means
Inspecting/looking at the load
Moving around the load
Pre-testing/ checking
Lifting
Transferring
Pausing
Analyse
Checking the load by lifting
Lifting the load
Pushing the load
Pausing
Analysing handling problem
Propose
Introducing a handling solution
Synthesis
Evaluate
Synthesising the handling solution
Evaluating the handling actions/decision
Observations
Here we report on the methodological aspects of the experimental set-up, the
visual cues and the verbalisations of the study participants. The protocol analysis
using Noldus Observer of the pilot data collected is ongoing at the time of
publication.
The experimental design of camera and microphone placement produced excellent
images and sound suitable for full protocol analysis. The study participants could
be observed clearly from all four angles, especially their handling of the loads. The
markers on the other hand require redesign as the message conveyed by (c) and
(d) were not clearly understood by all the participants. The lifting tasks also
require some modification. The two boxes used were too light and presented no
challenge to the male participants, one of who determined that after checking the
weight that they were so light he did not need to worry about the markers.
Conclusions
In this paper we report on work in progress to measure and analyse the
effectiveness of visual cue and training in manual handling. Our observations
support Braun et al [17], that is, the layout and placement of the warning should be
embedded within the context of the use and is dependent on the task being
performed as well as the task environment. In addition, warnings are most
effective when they are presented proximate (in time and space) to the hazard.
Funding
This research has been funded by the WorkCover Authority of NSW, Australia.
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Authors:
Associate Professor, PhD,
[email protected]
University Drive,
School of Architecture and Built Environment,
University of Newcastle, Callaghan, 2308
Australia
Fax:+61 2 4921 7408
Maya Guest
Lecturer,
[email protected]
University Drive,
School of Health Science,
University of Newcastle, Callaghan, 2308
Australia
Fax:+61 2 4921 7479
Leman Figen Gül
Research Fellow, PhD,
[email protected]
School of Architecture and Built Environment,
University of Newcastle, Callaghan, 2308
Australia
Fax:+61 2 4921 7408