Expecting people
to behave contrary to innate predisposition is futile. The
better approach is to fit the design to likely behavior.
by Marc Green
In theory,
warnings are an important means for accident prevention. They
reveal hidden hazards so the user of a product or facility
can avoid injury. Unfortunately, warnings frequently, and
some would say usually, fail to affect behavior.
The
analysis of warning failure should provide insight for warning
improvement. Some have examined deficiencies of the warnings
themselves. For example, much research has tested the effects
of format, shapes, colors, signal words, layout, etc. Laboratory
testing of warning format is probably a popular focus, in
part, because it is easy to do. Moreover, an effective, standard
format would be the engineer's prized "silver bullet,"
the simple comprehensive answer to a complex problem. However,
the search for this particular silver bullet has proved illusive.
While there are shelves of laboratory research recommending
various format attributes, the data are conflicting and have
questionable empirical validity1.
Moreover, there is little real-world evidence2
that following guidelines for a standard format is important.
Of course,
warnings should be legible, intelligible, and complete (based
on thorough hazard analysis). Beyond this, however, the lack
of compelling data suggests format and even content are likely
minor variables and that the real causes of warning failure
lie elsewhere. After all, if the user fails to notice the
warning, does not consider risk at all, or thinks it not worth
the trouble to read or comply with a warning, then its precise
rendering is unlikely to affect the outcome. Even "good"
warnings can be ineffective.
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real causes of warning failures are the same as those that determine
any other behavior: human mental limitations and predispositions
and the extraordinary ability of humans to adapt. Below, I discuss
how these factors can induce warning failure. I divide the discussion
into three general categories: perceived utility, adaptation,
and risk underestimation/nonestimation |
Even
"good" warnings can be ineffective.
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Perceived
Utility
Likelihood of a behavior usually depends on perceived utility.
Users perform a mental arithmetic, determining net gain by
subtracting the cost from the benefit. When confronted with
a warning, users apply this calculation to two decisions.
1. The
user decides whether to invest the effort into reading the
warning. Mental costs increase when fonts are small, low contrast,
and/or italicized, and when there is lateral masking because
of insufficient white space. Ironically, warnings are often
rendered in all capitals to make them more conspicuous. In
fact, all-capital text has very poor legibility and discourages
users from reading.
Users
also are unlikely to read long messages. Warnings should be
as brief as possible, but length depends partially on the
audience. If the person reading the warning is an experienced
user, he probably already knows about the hazard and need
merely be reminded. For novice users, the warning may require
more detailed information. Lastly, likelihood of reading the
warning increases with greater credibility and higher perceived
risk, issues that I discuss below.
2. Warning
compliance will probably block easy attainment of a desired
goal, so the user must decide whether the cost of goal loss
or increased effort is worth the gain in safety. The user
is likely to consider whether there is an alternative means
for reaching the goal. The lower the cost of switching to
an alternative, the more probable the compliance.
For example,
a nearby library displays "Do Not Use Cell Phone"
signs scattered about, but it also sets aside a small room
on each floor where cell phones may be used. The arithmetic
favors compliance because cost is cheap--the user can achieve
his aims by walking a short distance. Conversely, costs would
be greater, and compliance lower, if the user had to leave
the building to use the cell phone. Warning effectiveness
generally can be increased by understanding the user's goals
and by proving a safer, alternative means for achieving that
goal, or by providing an alternative goal.
Risk
Underestimation and Nonestimation
Even without the benefit of a Professional Safety subscription,
Shakespeare was able to observe that, "Best safety lies
in fear." Research has proven the Bard correct, demonstrating
users are more likely to both read and to comply with a warning
if they perceive significant risk. However, risk perception
is highly fallible. People may underestimate risk or, more
commonly, simply fail to estimate risk at all.
1. Users
rely on their direct observations. If a product contains an
obvious hazard (sharp edges; flame; moving, mechanical parts,
etc.), then users probably will behave self-protectively even
when no warning is present. They also will be more likely
to seek and to read warnings and instructions for avoiding
the hazard. Conversely, users who fail to perceive a hazard
directly are less likely to notice the warning. Because the
common purpose of warnings is to inform the user of hazards
that are not open and obvious, the situation is a classic
Catch-22: Warnings are least effective when most needed.
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2. Users fail to consider the risks. When performing routine
tasks, people do not usually consider possible risks. For example,
one study3 found that 74 percent
of accident victims had believed they were running no risk.
Another study4 surveyed non-prescription
drug users and concluded that "consumers portrayed their
non-prescription use as a routine, taken for granted activity,
relatively divorced from active consideration of risk." |
Warning
effectiveness generally can be increased by understanding the
user's goals and by proving a safer, alternative means for achieving
that goal, or by providing an alternative goal.
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Users
learn that warnings are frequent but accidents are few. People
who have repeatedly performed a task soon learn the contingencies,
a behaviorist term meaning the relationship between response
and outcome. Users are bombarded by warnings concerning hazards
that never occur. People speed, ignore "no parking"
and "no diving" signs, don't wear seatbelts, and
take medications, etc. with impunity. Highways are frequently
signed "Slow--Work Zone" followed by miles of orange
and black barrels but with no sign of construction. Moreover,
people often assume that the product contains a very large
built-in safety margin.
One rule
of behavioral contingencies is that immediate and certain
consequences are more powerful in changing behavior than are
delayed and uncertain ones. This likely explains why Out of
Order signs, "road closed," "use other door,"
etc., are among the most effective warnings. They signal negative
consequences that are both immediate and certain. On the other
hand, cigarette packages contain warnings about a far greater
hazard, but one which is both delayed and uncertain. Writer
Dave Barry has suggested cigarette smoking would end overnight
if the package warnings said, "WARNING: cigarettes contain
fat!" This quip might be good for a laugh but makes a
valid point: Users comply more where the risk (gaining weight)
contingency is immediate and likely.
The correlation
between non-compliant behavior and actual hazard is often
highly uncertain, so people become skeptical about warnings
as a class of information. Moreover, warnings often have low
credibility because users believe they may exist, not to promote
safety, but from fear of litigation or from some "do-gooder"
mentality that is simply trying to control them.
It is
sometimes difficult to convince people in authority that more
warning is not necessarily more effective warning. Users become
less likely to read ever-increasing lists of warnings rendered
in ever-decreasing print size. Further, frequent warnings
for low probability hazards cause a "boy who cried wolf
syndrome" that destroys credibility.
Overwarning
also can mask contingencies and confuse the user about real
and unlikely hazards. One diving accident occurred at a lake
that had a pier marked with many "No Diving" signs.
In fact, the water surrounding the pier was deep enough for
safe diving in most places, as the people who regularly used
the pier had discovered. They had routinely dived into the
water with no difficulties and had learned there was no negative
contingency between behavior and outcome. Unfortunately, a
regular user dived at the one shallow location and suffered
spinal injuries. He had misperceived the true risk because
of his experience and because the signs had masked the true
risks. There was no distinction between the warnings of significant
risk at the shallow locations and of minimal risk at deeper
locations.
3. Experienced
users develop a sense of control. They consequently perceive
less risk because they believe the risk is controllable. If
a sign says "No Diving," for example, the person
least likely to comply is an experienced diver5
who believes he can control dive angle for safe entry into
the water and avoid the hazard. The belief that the outcome
is controllable translates to less fear of consequences.
4. The
things that scare us and the things that kill us differ significantly.
Even when considering risk, people often make inaccurate assessments.
Human reasoning has several "cognitive shortcuts"
that affect decision-making. One is "confirmation bias,"
the tendency to seek information that confirms preconceived
belief and to avoid contrary evidence. Once a user believes
there is little risk, he will tune out warnings.
The "availability
heuristic," the tendency to make judgments based on the
information most readily in mind, also impairs risk estimation.
Because most people have little direct experience with significant
accidents, they gain much of their risk estimation knowledge
second-hand. The media focus on rare, dramatic, and exotic
risks--new Asian and African diseases, terrorist bombings,
nuclear power plant explosions, etc.--while largely ignoring
the more mundane but significant hazards, such as driving.
The avalanche of scary stories distorts the perception of
risk that most people face in everyday life.
Adaptation
Perhaps the most important cause of warning failure is adaptation.
Experience both removes risk as a consideration and makes
the warning invisible. Learning the contingencies is one example
of the way users change with repeated exposure to a product
or environment. In addition, there are several other adaptation
effects: visual routines, "inattentional blindness,"
and automatic/scripted behavior.
1. Experienced
users develop "visual routines"--preprogrammed eye
movement sequences. Experienced users become very precise
at narrowly directing attention to task-relevant information
from moment to moment as the task evolves. Attention usually
moves in lockstep with the fovea, so information that is not
located at or near a fixation point will fall in peripheral
vision and away from the center of attention. The user is
oblivious to information that is not located at precisely
the right location at precisely the correct time. Warnings
will be more effective if they are somehow integrated into
the normal task operations6.
2. Users
become "inattentionally blind." Even information
located at the fixation point may go undetected. Failures
to see information at the fixation point are so common that
they have their own name: "look but fail to see"
(LBFS) errors. By one account7, LBFS errors cause of 11 percent
of all automobile accidents.
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errors occur because humans receive far more sensory information
than they can cognitively process. In order to perform efficiently,
they learn to attend relevant information and to filter the
rest away. Users develop expectation and confirmation bias so
they become "inattentionally blind"8
to information that they have categorized as unimportant. Warnings
are not generally relevant to task completion, especially after
the user has learned the contingencies. |
The situation is a classic Catch-22: Warnings are least effective
when most needed.
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3. People
adapt by switching from "controlled" to "automatic"
behavioral modes. Beginners typically operate in a controlled
mode, one that requires conscious thought and focused attention.
Their behavior is slow and inefficient because decisions consume
significant attention and effort. The user is an information-seeking
mode, searching for input that can help perform the task.
With experience,
the user switches to automatic mode, where little conscious
thought occurs. They have learned to efficiently filter away
irrelevant sensory input and often fail to notice new or unexpected
information. Automatic behaviors may be very rigid, as when
a factory worker performs a repetitious manual task or a computer
operator performs data entry. The behavior is often said to
rely on "muscle memory" because responses are linked
into a chain, where the movement for one response triggers
the next. Once initiated, the response chain simply runs off
without conscious supervision, as if it were a mental servant
sent to carry out a task autonomously.
Automaticity
is not an all-or none phenomenon but rather has gradations.
Most routine tasks are "scripted," containing a
standard sequence of actions and "props." For example,
starting a car is scripted as: "take key from pocket,
open door, sit in driver's seat, put key in starter,"
etc. Although less rigid and relying less on muscle memory,
this scripted behavior is also routine and limits attention
to relevant information.
Once in
automatic mode, users are unlikely to notice warnings. The
obvious solution is to prevent automatic behavior from developing,
but this would come at a high cost. Automatic behavior is
needed for skilled and productive behavior, so any interference
lowers productivity. As frequently happens, there is a trade-off
between safety and efficiency.
Conclusion
There are limits to what warnings can do, even under the best
conditions. Some users will consciously perceive the warnings,
accurately assess risk and still fail to change behavior.
They may enjoy risk, operate under time or cost pressures,
believe the risk doesn't apply to them, or be overly optimistic
in their sense of control.
Given
this constraint, however, warnings can be improved by learning
from failures. Format may play a role, but it is doubtful
many accidents occur because a warning is yellow rather than
red or says "Caution" instead of "Warning."
The more likely scenario is that users simply do not notice
the warning and/or do not consider the risk. Users learn warnings
contain little useful information and it is more useful to
direct attention elsewhere. They learn to develop automatic
behavior. They learn warnings have little credibility and
risk can be better judged by employing their own senses. They
learn that, given the low probability of real harm, the cost
of compliance is too high.
The view
that warning failures arise from normal human psychology has
an important corollary: Any safety intervention must accept
of people for what they, not what we wish they were. The mental
processes that control behavior operate largely outside of
conscious awareness, and people cannot readily change them
even if they try. Ironically, this is fortunate because the
same processes of adaptation that cause warning failure are
also necessary for producing efficient and skilled performance9.
Perhaps
the ultimate cause of warning failure is wishful thinking.
Designers of warnings and other artifacts often assume people
should and will respond in some idealized and prescribed manner.
It would be very convenient if users would approach a task
but look for possible hazards, carefully scrutinize warnings
and instruction, and then adhere to rules and regulations.
Unfortunately, this is not how people are likely to act. Expecting
people to behave contrary to innate predisposition is futile
and is usually a failed strategy. The better approach is to
fit the design to likely behavior. As psychologist Harry Kay10
said, "We shall understand accidents when we understand
human nature."
References
1. Green, M. (2001), Caution! Warning Literature May Be
Misguided, Occupational Health & Safety, 16-18, December.
2. Young, S., Frantz, P., Rhodes, T. & Darnell, K. (2002).
Safety signs & labels: Does compliance with ANSI Z535
increase compliance with warnings. Professional Safety.
3. Weegels, M., & Kanis, H. (1998). Misconceptions of
everyday accidents. Ergonomics in Design, October, 11-17.
4. Bissell, P., Ward, P. & Noyce, R. (2000). Mapping the
contours of risk: Consumer perception of non-prescription
medicines, Journal of Social and Administrative Pharmacy,
17, 136-142.
5. Goldhaber, G., & deTurck, M. (1988). Effectiveness
of warning signs: Gender and familiarity effects. Journal
of Product Safety, 11, 271-284.
6. Frantz, P. & Rhodes, T. (1993) A task-analytic approach
to the temporal and spatial placement of product warnings,
Human Factors, 35, 719-730.
7. Brown, I. (2001) A review of the "look but fail to
see" accident causation factor, Proceedings of the Eleventh
Seminar on Behavioural Research in Road Safety, 145-144. London:
Department of the Environment, Transport and the Regions.
8. Green, M. (2002). Inattentional Blindness, OHS Canada,
23-29, Jan/Feb.
9. Green, M. (2003) Skewed View: Accident Investigation, OHS
Canada, 24-29, June.
10. Kay, H. (1971). Accidents: Some facts and theories. P.
Warr Psychology at Work (pp. 121-145). Baltimore: Penguin.
Marc Green, Ph.D., is a cognitive psychologist who consults
on accidents and safety. Head of Visual Expert Human Factors,
he can be reached at vexpert@visualexpert.com.
(Reprinted,
with permission from Occupational,
Health & Safety Magazine, Marchj 2004 issue, copyright
2004, Stevens Publishing Corporation)
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