URGENT 7 QUESTIONS!

620784 research-article2016 Research Report Psychological Science 2016, Vol. 27(2) 289–294 Wearing a Bicycle Helmet Can Increase © The Author(s) 2016 Reprints and permissions: Risk Taking and Sensation Seeking sagepub.com/journalsPermissions.nav DOI: 10.1177/0956797615620784 pss.sagepub.com 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 People’s perceptions of safety influence their risk taking. risk-taking behavior has been in the same domain as the This phenomenon, studied under such rubrics as risk safety measure (e.g., studies of seat-belt use in driving compensation (Adams & Hillman, 2001), risk homeosta- speed; Janssen, 1994). sis (Wilde, 1998), and risk allostasis (Lewis-Evans & Here, we changed both these approaches. First, we Rothengatter, 2009), is typified by people taking increased induced people to wear a helmet without their necessar- risks when using protective equipment (Adams, 1982) or ily being aware they were wearing safety equipment: at least reducing their risk taking when protective equip- Participants were (falsely) told they were taking part in ment is absent (Fyhri & Phillips, 2013; Phillips, Fyhri, & an eye-tracking study so we could exploit the fact that Sagberg, 2011). Behavioral adaptation in response to the head-mounted eye-tracking device we employed safety equipment has been reported in studies examining comes with both a bicycle helmet and a baseball cap as drivers operating a vehicle with and without built-in its standard mounting solutions. At random, participants safety devices (Sagberg, Fosser, & Sætermo, 1997), chil- were assigned to wear one mount or the other and were dren running obstacle courses with and without safety simply told it was the anchor for the eye tracker. Second, gear (Morrongiello, Walpole, & Lassenby, 2007), and we divorced risk-taking behavior from the safety device bicyclists descending a steep hill with and without hel- by using a computerized laboratory measure called the mets (Phillips et al., 2011). Work to date has been based Balloon Analogue Risk Task (BART; Lejuez et al., 2002), on the assumption that people respond only to safety measures of which they are aware—an idea encapsulated Corresponding Author: in Hedlund’s first rule of risk compensation: “If I don’t Tim Gamble, Department of Psychology, University of Bath, Bath know it’s there, I won’t compensate for a safety measure” BA2 7AY, United Kingdom (Hedlund, 2000, p. 87). Moreover, in research to date, the E-mail: [email protected] 290 Gamble, Walker in which the helmet could do nothing to change risk. We earnings for that trial were lost. At any point, participants also measured sensation seeking and anxiety as possible could choose to stop pumping and “bank” their accrued explanatory variables for any effect. 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- Method ber of pumps made on trials on which the balloon did not burst. This score would be higher when participants Participants risked losses by trying to maximize their score and lower Eighty participants (15 male and 24 female in the helmet when participants avoided risk and played more condition, 19 male and 22 female in the cap condition) conservatively. between the ages of 17 and 56 years (M = 25.26, SD = Sensation seeking was measured using the Sensation- 6.59) took part in the study; no monetary reward was Seeking Scale Form V (Zuckerman, Eysenck, & Eysenck, offered for participation. An a priori power analysis 1978). This scale measures four dimensions (10 self- showed that 40 participants per condition should have report items each) of sensation-seeking behavior: thrill 80% power to detect an effect size (Cohen’s d) of 0.63. and adventure seeking, disinhibition, experience seek- This was deemed sufficient, as we hoped to see relatively ing, and boredom susceptibility. Bicycling frequency was substantial effects of the helmet manipulation. 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 Materials frequency was measured using a Likert scale ranging State anxiety was measured using the State-Trait Anxiety from 1 (never) to 6 (always). Inventory (STAI) Form Y-1 (Spielberger, 1983). This form Either an Abus (Phoenix, AZ) HS-10 S-Force peak contains 40 questions, 20 that measure a person’s feelings bicycle helmet or a Beechfield (Bury, United Kingdom) of anxiety right at the moment of response and 20 that B15 five-panel baseball cap was used to support the measure his or her chronic levels of anxiety. Participants SensoMotoric (Teltow, Germany) head-mounted iView X here answered the former set. In the BART (Lejuez et al., HED-4.5 eye-tracking device (with its delicate 45° mirror 2002), which we programmed in Real Studio (Xojo, 2011), removed; see Fig. 1). Participants responded to the scales participants pressed a button to inflate an animated bal- using the Bristol Online Surveys Web site. All measures loon on a computer screen. Each button press inflated and the BART were completed on a 19-in. 4:3 LCD moni- the balloon more and increased the amount of fictional tor. The experimenter “operated” an Applied Science currency earned. If the balloon burst (which it would at Laboratories (Bedford, MA) Eye-Trac 6 desk-mounted a random point between 1 and 128 inflations), all 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 modeling, interactions of any of these variables (e.g., the Studio to increase the verisimilitude of the eye-tracking Condition × Bicycling Experience interaction was not sig- procedure. nificant; t = 0.39, p = .70). Prior research has shown that helmets do not affect cognitive performance in demand- ing laboratory tasks (Bogerd, Walker, Brühwiler, & Rossi, Procedure 2014), which means the results cannot be attributed to This study was conducted in the University of Bath this factor either. Department of Psychology’s eye-tracking laboratory. Participants were brought into the laboratory and told Discussion that they would complete a number of computer-based risk-taking measures while their point of gaze was mea- Laboratory measures showed greater risk taking and sen- sured using a head-mounted eye tracker. After reading sation seeking when participants wore a helmet, rather information about the study on the computer screen and than a baseball cap, during testing. These effects arose agreeing to participate, they entered their age and gender even though the helmet was introduced as a mount for and completed the STAI Y-1. A screen then appeared say- an eye-tracking apparatus and not as safety equipment, ing that the eye tracker would now be set up; the experi- and even though it could do nothing to alter participants’ menter placed the cap- or helmet-mounted eye tracker level of risk on the experimental task. Notably, the effect on the participant’s head, making a show of carefully was an immediate shift in both risk taking and sensation aligning everything as in a real eye-tracking procedure. seeking. This finding contrasts with those of previous The experimenter then moved to the eye-tracking com- work on unconscious influence, such as experiments on puter, where he or she ran the fake calibration software the persuasive effects of head movements (Wells & Petty, and conspicuously adjusted the eye-tracking controls to 1980) and environmental cues on consumer behavior make it appear to participants that their eye movements (Berger & Fitzsimons, 2008), which looked instead at were really being tracked. Participants then completed longer-term attitudinal changes from more overt signals. the Sensation-Seeking Scale, the BART, and the STAI Y-1 Our findings are plausibly related to social priming, again. Afterward, a screen appeared saying that the eye wherein social behaviors are cued by exposure to stereo- tracker was to be turned off, and the experimenter types or concepts (Bargh, 2006). However, whereas social removed the apparatus from participants’ heads. priming is generally understood in terms of behavior Participants then completed the final STAI Y-1 before directed toward another person, the effects in this study being debriefed, at which point they were informed of were individual, focused on the risk-taking propensity of the deception and asked not to share details of the exper- a person acting alone during exposure to a safety-related iment with anyone else. They then reported their bicy- prime. Schröder and Thagard (2013) produced computa- cling frequency and, if they did cycle, their helmet-wearing tional models of social priming in which primes activate frequency. shared cultural concepts in people’s minds, which in turn are associated with actions; through these links, the actions become available to the behavioral selection pro- Results cess. Speculatively, if what we saw in this study were to Wearing a helmet was associated with higher risk-taking be understood through such mechanisms, with the hel- scores (M = 40.40, SD = 18.18) than wearing a cap (M = met invoking concepts of protection from risk and thereby 31.06, SD = 13.29), t(78) = 2.63, p = .01, d = 0.59 (Fig. 2a). subconsciously shaping behaviors, our findings might Similarly, participants who wore a helmet reported higher suggest that Schröder and Thagard’s social-priming frame- sensation-seeking scores (M = 23.23, SD = 7.00) than par- work operates even when its interaction target compo- ticipants who wore a cap (M = 18.78, SD = 5.09), Welch’s nent (another person with whom to interact) is absent. t(69.19) = 3.24, p = .002, d = 0.73 (Fig. 2b). These effects Our findings initially appear different from those of cannot be explained by the helmet affecting anxiety, as some other studies. Fyhri and Phillips (2013; Phillips anxiety did not change significantly as a function of con- et al., 2011) found that risk taking in downhill bicy- dition, F(1, 78) = 0.19, p = .66, time of measurement, F(2, cling, measured through riding speed, did not simply 156) = 2.37, p = .10, or an interaction between the two, increase when a helmet was worn; rather, the people F(2, 156) = 1.18, p = .31 (Fig. 2c). Note that we used the who normally cycled with a helmet took fewer risks square roots of the anxiety scores for analyses because of when riding without one. Why did the participants in the skew seen in Figure 2c. There was no relationship Fyhri and Phillips’s study who were not habitual helmet between risk taking and gender, t(78) = 0.45, p = .66, bicy- users not react to wearing a helmet with increased risk cling experience (ρ = .12, p = .27), and extent of helmet taking, as our experiment might suggest they would? use when bicycling (ρ = .06, p = .60), nor, in regression Clearly more work is needed to definitively pin down 292 Gamble, Walker a b Cap Cap −20 0 20 40 60 80 100 10 20 30 40 Helmet Helmet −20 0 20 40 60 80 100 10 20 30 40 Score Score c Cap (Time 3) 20 30 40 50 60 Cap (Time 2) 20 30 40 50 60 Cap (Time 1) 20 30 40 50 60 Helmet (Time 3) 20 30 40 50 60 Helmet (Time 2) 20 30 40 50 60 Helmet (Time 1) 20 30 40 50 60 Score 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 complete Open Practices Disclosure for this article can be found the difference might be related to considerable varia- at http://pss.sagepub.com/content/by/supplemental-data. This article has received a badge for Open Data. More information tions between the two studies’ procedures. Fyhri and about the Open Practices badges can be found at https://osf Phillips greatly emphasized the physicality of their task .io/tvyxz/wiki/1.%20View%20the%20Badges/ and http://pss (“to increase the difference in measures between the .sagepub.com/content/25/1/3.full. helmet-on and -off conditions, all participants were instructed to cycle using one-hand in both conditions”; References p. 60), which provides a direct link between the action Adams, J. (1982). The efficacy of seat belt legislation. In (bicycling) and the condition (helmet wearing) that was Transactions of the Society of Automotive Engineers (Vol. absent in our study. Moreover, that study used a 91, pp. 2824-2838). Warrendale, PA: Society of Automotive repeated measures design, in which participants were Engineers. doi:10.4271/820819 aware they were riding a bicycle both with and without Adams, J. (1995). Risk. London, England: UCL Press. a helmet. 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