Reliability and Validity
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Psychological Science
2016, Vol. 27(2) 289 294
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DOI: 10.1177/0956797615620784
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Research Report
Peoples perceptions of safety influence their risk taking.
This phenomenon, studied under such rubrics as risk
compensation (Adams & Hillman, 2001), risk homeosta-
sis (Wilde, 1998), and risk allostasis (Lewis-Evans &
Rothengatter, 2009), is typified by people taking increased
risks when using protective equipment (Adams, 1982) or
at least reducing their risk taking when protective equip-
ment is absent (Fyhri & Phillips, 2013; Phillips, Fyhri, &
Sagberg, 2011). Behavioral adaptation in response to
safety equipment has been reported in studies examining
drivers operating a vehicle with and without built-in
safety devices (Sagberg, Fosser, & Stermo, 1997), chil-
dren running obstacle courses with and without safety
gear (Morrongiello, Walpole, & Lassenby, 2007), and
bicyclists descending a steep hill with and without hel-
mets (Phillips etal., 2011). Work to date has been based
on the assumption that people respond only to safety
measures of which they are awarean idea encapsulated
in Hedlunds first rule of risk compensation: If I dont
know its there, I wont compensate for a safety measure
(Hedlund, 2000, p. 87). Moreover, in research to date, the
risk-taking behavior has been in the same domain as the
safety measure (e.g., studies of seat-belt use in driving
speed; Janssen, 1994).
Here, we changed both these approaches. First, we
induced people to wear a helmet without their necessar-
ily being aware they were wearing safety equipment:
Participants were (falsely) told they were taking part in
an eye-tracking study so we could exploit the fact that
the head-mounted eye-tracking device we employed
comes with both a bicycle helmet and a baseball cap as
its standard mounting solutions. At random, participants
were assigned to wear one mount or the other and were
simply told it was the anchor for the eye tracker. Second,
we divorced risk-taking behavior from the safety device
by using a computerized laboratory measure called the
Balloon Analogue Risk Task (BART; Lejuez etal., 2002),
620784 PSSXXX10.1177/0956797615620784Gamble, WalkerHelmets, Risk Taking, and Sensation Seeking
research-article2016
Corresponding Author:
Tim Gamble, Department of Psychology, University of Bath, Bath
BA2 7AY, United Kingdom
E-mail: [emailprotected]
Wearing a Bicycle Helmet Can Increase
Risk Taking and Sensation Seeking
in Adults
Tim Gamble and Ian Walker
Department of Psychology, University of Bath
Abstract
Humans adapt their risk-taking behavior on the basis of perceptions of safety; this risk-compensation phenomenon
is typified by people taking increased risks when using protective equipment. Existing studies have looked at people
who know they are using safety equipment and have specifically focused on changes in behaviors for which that
equipment might reduce risk. Here, we demonstrated that risk taking increases in people who are not explicitly aware
they are wearing protective equipment; furthermore, this happens for behaviors that could not be made safer by that
equipment. In a controlled study in which a helmet, compared with a baseball cap, was used as the head mount for an
eye tracker, participants scored significantly higher on laboratory measures of both risk taking and sensation seeking.
This happened despite there being no risk for the helmet to ameliorate and despite it being introduced purely as an
eye tracker. The results suggest that unconscious activation of safety-related concepts primes globally increased risk
propensity.
Keywords
risk taking, sensation seeking, social priming, bicycling, protective equipment, behavior change, open data
Received 9/8/15; Revision accepted 11/12/15
http://crossmark.crossref.org/dialog/?doi=10.1177%2F0956797615620784&domain=pdf&date_stamp=2016-01-06
290 Gamble, Walker
in which the helmet could do nothing to change risk. We
also measured sensation seeking and anxiety as possible
explanatory variables for any effect.
Method
Participants
Eighty participants (15 male and 24 female in the helmet
condition, 19 male and 22 female in the cap condition)
between the ages of 17 and 56 years (M = 25.26, SD =
6.59) took part in the study; no monetary reward was
offered for participation. An a priori power analysis
showed that 40 participants per condition should have
80% power to detect an effect size (Cohens d) of 0.63.
This was deemed sufficient, as we hoped to see relatively
substantial effects of the helmet manipulation.
Materials
State anxiety was measured using the State-Trait Anxiety
Inventory (STAI) Form Y-1 (Spielberger, 1983). This form
contains 40 questions, 20 that measure a persons feelings
of anxiety right at the moment of response and 20 that
measure his or her chronic levels of anxiety. Participants
here answered the former set. In the BART (Lejuez etal.,
2002), which we programmed in Real Studio (Xojo, 2011),
participants pressed a button to inflate an animated bal-
loon on a computer screen. Each button press inflated
the balloon more and increased the amount of fictional
currency earned. If the balloon burst (which it would at
a random point between 1 and 128 inflations), all
earnings for that trial were lost. At any point, participants
could choose to stop pumping and bank their accrued
money. After the balloon burst, or after a decision to
bank, the next trial began. Each participant completed 30
trials, and his or her risk-taking score was the mean num-
ber of pumps made on trials on which the balloon did
not burst. This score would be higher when participants
risked losses by trying to maximize their score and lower
when participants avoided risk and played more
conservatively.
Sensation seeking was measured using the Sensation-
Seeking Scale Form V (Zuckerman, Eysenck, & Eysenck,
1978). This scale measures four dimensions (10 self-
report items each) of sensation-seeking behavior: thrill
and adventure seeking, disinhibition, experience seek-
ing, and boredom susceptibility. Bicycling frequency was
measured using a Likert scale ranging from 1 (never) to 6
(five times a week or more). If a person selected anything
other than never on this instrument, helmet-wearing
frequency was measured using a Likert scale ranging
from 1 (never) to 6 (always).
Either an Abus (Phoenix, AZ) HS-10 S-Force peak
bicycle helmet or a Beechfield (Bury, United Kingdom)
B15 five-panel baseball cap was used to support the
SensoMotoric (Teltow, Germany) head-mounted iView X
HED-4.5 eye-tracking device (with its delicate 45 mirror
removed; see Fig. 1). Participants responded to the scales
using the Bristol Online Surveys Web site. All measures
and the BART were completed on a 19-in. 4:3 LCD moni-
tor. The experimenter operated an Applied Science
Laboratories (Bedford, MA) Eye-Trac 6 desk-mounted
optics system with Eye-Trac PC. A fake nine-point
Fig. 1. Photos showing how the eye tracker was mounted in each of the two conditions: to a baseball cap (left) and a bicycle helmet (right).
Helmets, Risk Taking, and Sensation Seeking 291
eye-tracking calibration program was written in Real
Studio to increase the verisimilitude of the eye-tracking
procedure.
Procedure
This study was conducted in the University of Bath
Department of Psychologys eye-tracking laboratory.
Participants were brought into the laboratory and told
that they would complete a number of computer-based
risk-taking measures while their point of gaze was mea-
sured using a head-mounted eye tracker. After reading
information about the study on the computer screen and
agreeing to participate, they entered their age and gender
and completed the STAI Y-1. A screen then appeared say-
ing that the eye tracker would now be set up; the experi-
menter placed the cap- or helmet-mounted eye tracker
on the participants head, making a show of carefully
aligning everything as in a real eye-tracking procedure.
The experimenter then moved to the eye-tracking com-
puter, where he or she ran the fake calibration software
and conspicuously adjusted the eye-tracking controls to
make it appear to participants that their eye movements
were really being tracked. Participants then completed
the Sensation-Seeking Scale, the BART, and the STAI Y-1
again. Afterward, a screen appeared saying that the eye
tracker was to be turned off, and the experimenter
removed the apparatus from participants heads.
Participants then completed the final STAI Y-1 before
being debriefed, at which point they were informed of
the deception and asked not to share details of the exper-
iment with anyone else. They then reported their bicy-
cling frequency and, if they did cycle, their helmet-wearing
frequency.
Results
Wearing a helmet was associated with higher risk-taking
scores (M = 40.40, SD = 18.18) than wearing a cap (M =
31.06, SD = 13.29), t(78) = 2.63, p = .01, d = 0.59 (Fig. 2a).
Similarly, participants who wore a helmet reported higher
sensation-seeking scores (M = 23.23, SD = 7.00) than par-
ticipants who wore a cap (M = 18.78, SD = 5.09), Welchs
t(69.19) = 3.24, p = .002, d = 0.73 (Fig. 2b). These effects
cannot be explained by the helmet affecting anxiety, as
anxiety did not change significantly as a function of con-
dition, F(1, 78) = 0.19, p = .66, time of measurement, F(2,
156) = 2.37, p = .10, or an interaction between the two,
F(2, 156) = 1.18, p = .31 (Fig. 2c). Note that we used the
square roots of the anxiety scores for analyses because of
the skew seen in Figure 2c. There was no relationship
between risk taking and gender, t(78) = 0.45, p = .66, bicy-
cling experience ( = .12, p = .27), and extent of helmet
use when bicycling ( = .06, p = .60), nor, in regression
modeling, interactions of any of these variables (e.g., the
Condition Bicycling Experience interaction was not sig-
nificant; t = 0.39, p = .70). Prior research has shown that
helmets do not affect cognitive performance in demand-
ing laboratory tasks (Bogerd, Walker, Brhwiler, & Rossi,
2014), which means the results cannot be attributed to
this factor either.
Discussion
Laboratory measures showed greater risk taking and sen-
sation seeking when participants wore a helmet, rather
than a baseball cap, during testing. These effects arose
even though the helmet was introduced as a mount for
an eye-tracking apparatus and not as safety equipment,
and even though it could do nothing to alter participants
level of risk on the experimental task. Notably, the effect
was an immediate shift in both risk taking and sensation
seeking. This finding contrasts with those of previous
work on unconscious influence, such as experiments on
the persuasive effects of head movements (Wells & Petty,
1980) and environmental cues on consumer behavior
(Berger & Fitzsimons, 2008), which looked instead at
longer-term attitudinal changes from more overt signals.
Our findings are plausibly related to social priming,
wherein social behaviors are cued by exposure to stereo-
types or concepts (Bargh, 2006). However, whereas social
priming is generally understood in terms of behavior
directed toward another person, the effects in this study
were individual, focused on the risk-taking propensity of
a person acting alone during exposure to a safety-related
prime. Schrder and Thagard (2013) produced computa-
tional models of social priming in which primes activate
shared cultural concepts in peoples minds, which in turn
are associated with actions; through these links, the
actions become available to the behavioral selection pro-
cess. Speculatively, if what we saw in this study were to
be understood through such mechanisms, with the hel-
met invoking concepts of protection from risk and thereby
subconsciously shaping behaviors, our findings might
suggest that Schrder and Thagards social-priming frame-
work operates even when its interaction target compo-
nent (another person with whom to interact) is absent.
Our findings initially appear different from those of
some other studies. Fyhri and Phillips (2013; Phillips
et al., 2011) found that risk taking in downhill bicy-
cling, measured through riding speed, did not simply
increase when a helmet was worn; rather, the people
who normally cycled with a helmet took fewer risks
when riding without one. Why did the participants in
Fyhri and Phillipss study who were not habitual helmet
users not react to wearing a helmet with increased risk
taking, as our experiment might suggest they would?
Clearly more work is needed to definitively pin down
292 Gamble, Walker
Helmet
Cap
a
Score
10 20 30 40
Helmet
Cap
b
Score
Helmet
(Time 1)
Helmet
(Time 2)
Helmet
(Time 3)
Cap
(Time 1)
Cap
(Time 2)
Cap
(Time 3)
c
Score
20 0 20 40 60 80 100
20 0 20 40 60 80 100
10 20 30 40
20 30 40 50 60
20 30 40 50 60
20 30 40 50 60
20 30 40 50 60
20 30 40 50 60
20 30 40 50 60
Fig. 2. Distribution of scores for the helmet and cap conditions on (a) the Balloon Analogue Risk Task (BART), (b) the
Sensation-Seeking Scale, and (c) state anxiety, measured using the State-Trait Anxiety Inventory (STAI). For anxiety, scores
are shown separately for time points before donning the eye tracker (Time 1), while wearing the eye tracker (Time 2), and
after removing the eye tracker (Time 3). For each measure, the mean score across conditions is indicated by a vertical dotted
line, and the mean score for each condition separately is indicated by a thick vertical line. Individual participants scores are
shown as thin vertical lines (rug points; stacked when more than 1 participant obtained the same score). Overlaid on the
rug-point plots are kernel-density curves (with arbitrary scaling) that illustrate the overall distribution of scores within each
condition.
Helmets, Risk Taking, and Sensation Seeking 293
all the mechanisms here, but for now, we speculate that
the difference might be related to considerable varia-
tions between the two studies procedures. Fyhri and
Phillips greatly emphasized the physicality of their task
(to increase the difference in measures between the
helmet-on and -off conditions, all participants were
instructed to cycle using one-hand in both conditions;
p. 60), which provides a direct link between the action
(bicycling) and the condition (helmet wearing) that was
absent in our study. Moreover, that study used a
repeated measures design, in which participants were
aware they were riding a bicycle both with and without
a helmet. This could have meant that behavior changed
through mechanisms different from those seen here,
where participants took part only in one condition and
were not aware of any manipulation, nor even that they
were specifically wearing a safety device.
The practical implication of our findings, in which risk
taking changed in a global way when the helmet was worn,
might be to suggest more extreme unintended conse-
quences of safety equipment in hazardous situations than
has previously been thought. The idea that people might
take more risks when wearing safety equipment designed
to protect against those risks has a considerable (Adams,
1982, 1995; Adams & Hillman, 2001; Hedlund, 2000),
although not uncontroversial (McKenna, 1988), history. If
this laboratory demonstration of globally increased risk
taking arising from localized protection were to be repli-
cated in real settings, this could suggest that people using
protective equipment against specific hazards might also
be unduly inclined to take risks that such protective equip-
ment cannot reasonably be expected to guard against. This
is not to suggest that the safety equipment will necessarily
have its specific utility nullified, but rather that there could
be changes in behavior wider than previously envisaged.
Author Contributions
T. Gamble and I. Walker developed and designed the study,
analyzed and interpreted the data, and drafted the manuscript.
Acknowledgments
The authors thank A. Laketa and R. Posner for their work in
recruiting and testing participants.
Declaration of Conflicting Interests
The authors declared that they had no conflicts of interest with
respect to their authorship or the publication of this article.
Open Practices
All data have been made publicly available via Open Science
Framework and can be accessed at https://osf.io/eky4s/. The
complete Open Practices Disclosure for this article can be found
at http://pss.sagepub.com/content/by/supplemental-data. This
article has received a badge for Open Data. More information
about the Open Practices badges can be found at https://osf
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References
Adams, J. (1982). The efficacy of seat belt legislation. In
Transactions of the Society of Automotive Engineers (Vol.
91, pp. 28242838). Warrendale, PA: Society of Automotive
Engineers. doi:10.4271/820819
Adams, J. (1995). Risk. London, England: UCL Press.
Adams, J., & Hillman, M. (2001). The risk compensation the-
ory and bicycle helmets. Injury Prevention, 7, 8991.
doi:10.1136/ip.7.2.89
Bargh, J. A. (2006). What have we been priming all these years?
On the development, mechanisms, and ecology of non-
conscious social behavior. Journal of Social Psychology, 36,
147168. doi:10.1002/ejsp.336
Berger, J., & Fitzsimons, G. (2008). Dogs on the street, pumas
on your feet: How cues in the environment influence prod-
uct evaluation and choice. Journal of Marketing Research,
45, 114. doi:10.1509/jmkr.45.1.1
Bogerd, C. P., Walker, I., Brhwiler, P. A., & Rossi, R. M.
(2014). The effect of a helmet on cognitive performance is,
at worst, marginal: A controlled laboratory study. Applied
Ergonomics, 45, 671676. doi:10.1016/j.apergo.2013.09.009
Fyhri, A., & Phillips, R. O. (2013). Emotional reactions to cycle
helmet use. Accident Analysis & Prevention, 50, 5963.
doi:10.1016/j.aap.2012.03.027
Hedlund, J. (2000). Risky business: Safety regulations, risk com-
pensation, and individual behavior. Injury Prevention, 6,
8290. doi:10.1136/ip.6.2.82
Janssen, W. (1994). Seat-belt wearing and driving behavior: An
instrumented-vehicle study. Accident Analysis & Prevention,
26, 249261. doi:10.1016/0001-4575(94)90095-7
Lejuez, C. W., Read, J. P., Kahler, C. W., Richards, J. B., Ramsey,
S. E., Stuart, G. L., . . . Brown, R. A. (2002). Evaluation of a
behavioral measure of risk taking: The Balloon Analogue
Risk Task (BART). Journal of Experimental Psychology:
Applied, 8, 7584. doi:10.1037/1076-898X.8.2.75
Lewis-Evans, B., & Rothengatter, T. (2009). Task difficulty, risk,
effort and comfort in a simulated driving taskimplications
for Risk Allostasis Theory. Accident Analysis & Prevention,
41, 10531063. doi:10.1016/j.aap.2009.06.011
McKenna, F. (1988). What role should the concept of risk play
in theories of accident involvement? Ergonomics, 31, 469
484. doi:10.1080/00140138808966692
Morrongiello, B. A., Walpole, B., & Lassenby, J. (2007). Under-
standing childrens injury-risk behavior: Wearing safety
gear can lead to increased risk taking. Accident Analysis &
Prevention, 39, 618623. doi:10.1016/j.aap.2006.10.006
Phillips, R. O., Fyhri, A., & Sagberg, F. (2011). Risk compen-
sation and bicycle helmets. Risk Analysis, 31, 11871195.
doi:10.1111/j.1539-6924.2011.01589.x
Sagberg, F., Fosser, S., & Stermo, I. F. (1997). An investigation
of behavioural adaptation to airbags and antilock brakes
https://osf.io/tvyxz/wiki/1.%20View%20the%20Badges/
https://osf.io/tvyxz/wiki/1.%20View%20the%20Badges/
http://pss.sagepub.com/content/25/1/3.full
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294 Gamble, Walker
among taxi drivers. Accident Analysis & Prevention, 29,
293302. doi:10.1016/S0001-4575(96)00083-8
Schrder, T., & Thagard, P. (2013). The affective meanings of
automatic social behaviors: Three mechanisms that explain
priming. Psychological Review, 120, 255280. doi:10.1037/
a0030972
Spielberger, C. D. (1983). Manual for the State-Trait Inventory
STAI (Form Y). Palo Alto, CA: Mind Garden.
Wells, G. L., & Petty, R. E. (1980). The effects of overt head move-
ments on persuasion: Compatibility and incompatibility
of responses. Basic and Applied Social Psychology, 1, 219
230. doi:10.1207/s15324834basp0103_2
Wilde, G. J. S. (1998). Risk homeostasis theory: An overview.
Injury Prevention, 4, 8991. doi:10.1136/ip.4.2.89
Xojo. (2011). Real Studio (Version 4.3) [Computer software].
Austin, TX: Author.
Zuckerman, M., Eysenck, S. B. J., & Eysenck, H. J. (1978). Sen-
sation seeking in England and America: Cross-cultural, age,
and sex comparisons. Journal of Consulting and Clinical
Psychology, 46, 139149. doi:10.1037/0022-006X.46.1.139
