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Barriers and facilitators of bicycle helmet use among children and their parents
Transportation Research Part F xxx (2015) xxx–xxx
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Transportation Research Part F journal homepage: www.elsevier.com/locate/trf
Barriers and facilitators of bicycle helmet use among children and their parents Timo Lajunen Department of Psychology, Norwegian University for Science and Technology (NTNU), 7491 Trondheim, Norway
a r t i c l e
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Article history: Received 4 October 2014 Received in revised form 11 March 2015 Accepted 11 March 2015 Available online xxxx Keywords: Bicycle helmet use Barriers Facilitators Risk School children Adults
a b s t r a c t Despite the fact that bicycle helmet use protects against head injuries, helmet use rate is still low even in countries with high concern for traffic safety. Earlier research shows that helmet use declines with age and that helmet use is low especially among teenagers. The aim of the present study was to investigate barriers and facilitators of helmet use among primary and secondary school pupils and their parents. Identical surveys were conducted among school children (n = 235) and their parents (n = 106). Children’s and adults’ responses concerning cycling, helmet use, helmet ownership, risk assessment and barriers and facilitators were compared and separate regression analyses conducted. Helmet use rate was lower among pupils than adults and they scored higher in most of the barrier items. The results of regression analyses showed that among children, age, gender, barriers and facilitators predicted helmet use while among adults only frequency of cycling and barriers were related to helmet use. Among children, the strongest correlates of not using a helmet were the belief of not needing a helmet and wish to use a cap or a hat instead. Having a helmet wearing as a habit and feeling safer were the strongest correlates of using helmet. Among adults, the strongest correlates of not using a helmet were ‘‘helmet looks ridiculous’’, ‘‘just going to short trip’’ and riding close to home while the strongest correlate of using a helmet was the habit of helmet use. It was concluded that targeting the barriers in helmet wearing campaigns might work better both among children and adults than emphasising the benefits at least among Norwegian child and adult cyclists. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Cycling is a healthy and environmentally sound means of transportation (Lindsay, Macmillan, & Woodward, 2011). For some road user groups, like school children, cycling provides often the only effective means of transportation when distances are too long for walking and when car or bus transportation is not available or possible because of the age of the traveller. This is especially the case in sparsely populated countries like Norway. While virtually all countries promote bicycle use among children, teenagers and adults, a cycling accident is also one of the main risk factors in a child’s or teenager’s life (OECD, 2004; World Health Organization, 2008). For example in UK, about 75% of trauma among children occurs on the roads (Sinha & Lander, 2013). Therefore, it is essential to improve passive safety (i.e. protection in the case of an accident) among cyclists and especially among children (World Health Organization, 2008). Several studies show that a bicycle helmet is an effective way of preventing head injuries. According to a Cochrane survey conducted already in 1999, head injury is a leading cause of death among cyclists and bicycle helmets are effective in E-mail address: [email protected] http://dx.doi.org/10.1016/j.trf.2015.03.005 1369-8478/Ó 2015 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
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T. Lajunen / Transportation Research Part F xxx (2015) xxx–xxx
reducing head, brain and face injuries (Thompson, Rivara, & Thompson, 1999). A qualitative review about the protective effectiveness of helmets among children concluded that bicycle helmets are effective even when taking biases into account and recommended habitual used of helmets (Lastennet, Sizun, Dobrzynski, & De Parscau, 2001). Attewell, Glase, and McFadden (2001) conducted one of the first quantitative reviews of bicycle helmet use and head injuries. They reported a summary odds ratio estimate for efficacy as 0.40 for head injury, 0.42 for brain injury, 0.53 for facial injury and 0.27 for fatal injury (Attewell et al., 2001). This indicates a statistically significant protective effect of helmets and the authors concluded that ‘‘the evidence is clear that bicycle helmets prevent serious injury and even death’’ (Attewell et al., 2001). While some later investigations claim that the results of Attewell et al. (2001) showed inflated safety benefits for helmet use because of some methodological problems (e.g. publication bias) (Curnow, 2003; Elvik, 2011), it is still clear that bicycle helmets provide an effective and easy means for protection against head trauma among cyclists. The effectiveness of bicycle helmet in head injury reduction has recently been demonstrated in several case-control studies (Amoros, Chiron, Martin, Thélot, & Laumon, 2012; Bambach, Mitchell, Grzebieta, & Olivier, 2013; Hagel, 2011; Persaud, Coleman, Zwolakowski, Lauwers, & Cass, 2012) and biomechanical studies (Cripton, Dressler, Stuart, Dennison, & Richards, 2014; Schejbalová, Micˇunek, & Schmidt, 2013). World Health Organization (2008) has estimated by using a cost-benefit analysis that one unit of money invested on bicycle helmet campaigns returns as 29 units. We can expect the protective effect to be more significant among children and teenagers, who get involved in bicycle crashes more often than adults due to their way of using bicycles as means of commuting and in free time activities (Sleet, Ballesteros, & Borse, 2010). The main problem in cycling helmets is simply that the helmet use rate is low in many countries while there seem to be high variation in helmet rates among different countries and regions. Klein, Thompson, Scheidt, Overpeck, and Gross (2005) studied the prevalence of helmet use in 26 countries by using a school based survey. According to results, reported helmet use varied greatly by country from 39.2% to 1.9%. Hence, helmet use did not reach 50% in any country (Klein et al., 2005). The highest helmet use rate (39.1%) was reported in Norway. Since the Klein & al.’s study was conducted over 15 years ago, we can assume that the current helmet wearing rates are higher. In an observational study conducted in Eastern Norway in 2008, 39% (35% females and 41% males) of passing bicyclists above 17 years of age used a helmet (Muskaug, Nygaard, Rosland, Johansen, & Sjøvold, 2009). It should be noted, however, that this figure included only adults and was based on observed helmet use unlike the 26 country study by Klein et al. (2005). According to Trygg Trafikk – The Norwegian Council for Road Safety – the current helmet wearing rate in Norway is 54% (Trygg Trafikk, 2014). Although there is a considerable increase in helmet use when compared to Klein et al. (2005) and Muskaug et al. (2009), the helmet wearing rate is still low even in Norway, which ranks as the second best in road safety (measured with road fatalities per registered vehicle or fatalities per vehicle-kilometre) in 2011 (OECD, 2014). In the present study, the aim was to investigate reasons for not using a bicycle helmet among primary and secondary school children and their parents in Norway. Researchers have been investigating reasons for children and adolescents not wearing a bicycle helmet since 80s. In a study by Finnoff & all. conducted in 1999 in Minnesota, one of the most common reasons for not using a helmet was not owning one (Finnoff, Laskowski, Altman, & Diehl, 2001). Robertson and colleagues studied reasons for not using a bicycle helmet in rural Saskatchewan and found that helmet costs and lack of awareness were main barriers to helmet use (Robertson, Lang, & Schaefer, 2014). Secginli, Cosansu, & Nahcivan investigated prevalence of bicycle helmet use in two primary schools in Istanbul and reported a very low helmet use rate of 4.4% among 8–16 year olds (Secginli, Cosansu, & Nahcivan, 2013). One of the barriers for helmet use was not owning one in addition to parents’ and friends’ helmet use. Children’s and adolescent helmet ownership is probably partly related to the same factors as helmet use (e.g., attitudes) in addition to parents’ education and income level (Towner & Marvel, 1992). Many studies have shown that bicycle helmet use is related to the a child’s or teenager’s age so that younger children are more likely than teenagers to wear helmets (Dellinger & Kresnow, 2010; Klein et al., 2005; Lang, 2007; O’Callaghan and Nausbaum, 2006). Klein et al. (2005) analysed data from 26 countries and found that age was the strongest individual predictor of use across countries. In general, younger primary school children use helmet regularly whereas the use rate declines among secondary school aged children. The main challenge in bicycle helmet interventions is to prevent decrease and maintain high use rates during adolescence. To develop effective interventions, it is essential to study which factors influence helmet use in different age groups. It can be assumed that different specific factors are relevant for children (e.g. parent’s opinions), teenagers (e.g. peer pressure) and adults (e.g. convenience). In the present study, factors related to bicycle helmet use are studied among primary and secondary school children and their parents. Bicycle helmet use has been studied from different points of view ranging from peer influence and household factors (Dellinger & Kresnow, 2010) to social psychological models of helmet use (Fishman, Washington, & Haworth, 2012; Lajunen & Räsänen, 2001, 2004). Hence, the previous research has helped us to identify several factors influencing the helmet wearing rates among children and adolescents. The most important barriers to helmet use seem to be negative peer pressure and fear of appearing dumb (Forjuoh, Schuchmann, Fiesinger, & Mason, 2003; Howland et al., 1989; Loubeau, 2000; Rezendes, 2006; Stevenson & Lennie, 1992), lack of knowledge and awareness (Pierce, Palombaro, & Black, 2014; Robertson et al., 2014), inconvenience and finding the helmet uncomfortable (Finnoff et al., 2001; Loubeau, 2000; Rezendes, 2006; Stevenson & Lennie, 1992), and poor fit of helmets due to hair style (Forjuoh et al., 2003; Pierce et al., 2014). In some studies, perceiving the injury risk low or considering oneself as a safe rider (and, thus, facing low accident risk) have been listed as barriers to helmet use (Finnoff et al., 2001; Forjuoh et al., 2003). Interestingly, riders may agree that helmets provide a good protection against a head injury but still not use one if they assess the injury risk low (Finnoff et al., 2001). Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
T. Lajunen / Transportation Research Part F xxx (2015) xxx–xxx
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Literature review shows that barriers have been studied more than the facilitators of helmet use. Earlier studies show that having friends and parents using a helmet is positively related to helmet use (Finnoff et al., 2001; Lajunen & Räsänen, 2001; Secginli et al., 2013). In addition to friends’ and parents’ positive example, also habitual helmet use as well as having been using helmet earlier have been reported to be related to helmet wearing (Lajunen & Räsänen, 2004; O’Callaghan and Nausbaum, 2006; Page, Follett, Scanlan, Hammermeister, & Friesen, 1996). The problem with these facilitators is to get the friends or parents to use a helmet at the first place. Cycling habits and frequency depend on the climate (rainfall, snow, temperature) and traffic conditions (geography of the landscape, availability of bicycle route network) in large degree. Therefore, cycling habits and experienced facilitators and barriers of helmet use depend largely on the local conditions. For example, in sparsely habited Scandinavia, bicycle is an essential means of transportation whereas in some other countries bicycle is mostly used for recreational purposes. Similarly, the barriers for helmet wearing vary among countries; in a country with warm climate, one of the main barriers is the inconvenience related to over-heating and sweating (Finnoff et al., 2001). Moreover, climate, geography and culture related factors may influence children’s, teenagers’ and adults’ helmet use differently. The aim of the present study is to investigate barriers and facilitators of helmet use among Norwegian primary and secondary school pupils and their parents. The aim is to investigate if adults and children differ in terms of barriers and facilitators of bicycle helmet use in a country with high traffic safety awareness. 2. Method 2.1. Procedure and participants Survey data were collected in two schools (one primary and one secondary school) in Sør-Trøndelag region in Norway. Two similar questionnaire forms were prepared: a child’s form and a parents’ form. The core items in the questionnaires were identical (except few cases in which the wording was adjusted according to the age) while some questions were specific for children (e.g. grade) and some questions were specific to adults (e.g. education level). Since the core items were identical, children’s and adults’ responses could be directly compared. The questionnaires were delivered in classroom and the participants were assured about anonymity and confidentiality. Children filled in their copy during the class hour while the parents filled the questionnaire at home (which was delivered to them by their child) and returned the filled questionnaire in a sealed envelope. Since the children filled the questionnaire in classroom, the response rate was 100% while 45.1% of the parents returned a filled questionnaire. Since the data collection was based on anonymity, we could not send a reminder to those parents who did not participate. The Respondents for this study were 235 pupils (51.3% male) and 106 parents (34.6% male). The age range among pupils was between 10 and 16 years (M = 12.7 years, SD = 1.80) and among adults 29–60 years (M = 42.3, SD = 5.72). 2.2. Measures 2.2.1. Cycling frequency, helmet ownership and helmet use Frequency of cycling was measured with question ‘‘How often do you ride a bike?’’ (Response scale: 1 = Never, 2 = Rarely, 3 = Once a month, 4 = Once in two weeks, 5 = Once a week, 6 = 2–6 times a week, 7 = Every day) and the helmet use frequency with question ‘‘How often do you use helmet when you cycle?’’ (Response scale: 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = All the time). 2.2.2. Injury risk Respondents’ evaluation of their personal injury risk was measured with a question about the likelihood of an accident (‘‘There is a big chance that I fall while riding a bicycle’’) and severity of the consequence (‘‘There is a big chance that I end up at the doctor/hospital if I fall while riding a bicycle’’). The responses to both questions were given with a 5-point scale (1 = strongly disagree, 5 = strongly agree). In addition, an interaction variable ‘‘risk’’ was calculated by multiplying the likelihood of an accident with severity of the consequences. 2.2.3. Barriers and facilitators Barrier and facilitator items were collected from previous literature and new items were created in a brain storming session. The final item pool consisted of 18 statements including 12 barrier items and 6 facilitator items (see Table 1). The instruction for barrier items was ‘‘When I do not use a helmet it is because. . .’’ and for facilitator items ‘‘When I use helmet it is because. . .’’ A 5-point Likert response scale was used (from 1 = strongly disagree to 5 = strongly agree). This structure was chosen, because assumed that it would fit to both adults and pupils. 2.2.4. Background information Participants’ age and gender were also recorded but not any identification information like class.
Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
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Table 1 Descriptive statistics, correlations between the items and frequency of helmet use and between children and adults in the study variables. Children Mean How often do you use helmet when you cycle? Age Cycling frequency There is a big chance that I fall while riding a bicycle There is a big chance that I end up at the doctor/hospital if I fall while riding a bicycle Risk It is uncomfortable to wear I have no place and add it from me when I get there, so I have to carry it I’m just going to a short trip It messes up my hair I think the helmet looks ridiculous I think other people think it’s stupid to wear a helmet I do not need it because I’m not riding a bicycle where the motor vehicles are I don’t need it I forget to put it on It gets too hot or cold I don’t need because I just ride a bicycle close to home I would rather use a hat or cap It protects me in traffic It is a habit My friends use it I’m going to ride a bike a long way I feel safer with bicycle helmet on I cycle a lot on difficult surfaces * ** ***
SD
Adults R
Mean
Children vs. adults SD
R
t-test
df *
3.48 12.69 5.65 2.69 2.43
1.58 1.80 1.62 1.28 1.29
1.00 .76*** .16* .15* .03
3.93 42.27 4.38 2.81 3.15
1.43 5.72 1.98 1.39 1.21
1.00 .01 .45*** .04 .05
2.48 – 6.24*** .78 4.78***
334 – 335 336 335
7.38 2.94 2.46 3.03 2.64 2.85 2.59 2.27 2.42 2.36 2.31 2.73 2.60 4.48 3.61 3.11 3.89 3.97 3.16
6.35 1.55 1.50 1.54 1.62 1.57 1.44 1.40 1.49 1.35 1.37 1.54 1.62 .93 1.42 1.47 1.25 1.27 1.31
.10 .58*** .40*** .46*** .50*** .59*** .49*** .62*** .78*** .35** .42*** .56*** .68*** .40*** .68*** .51*** .25*** .65*** .21**
9.75 2.06 1.58 2.68 1.71 1.67 1.36 1.88 1.48 2.29 1.90 1.93 1.51 4.85 4.10 2.77 3.45 4.58 3.07
6.95 1.40 .99 1.58 1.22 1.11 .75 1.28 .89 1.43 1.26 1.20 1.02 .51 1.23 1.32 1.48 .80 1.36
.07 .42*** .35*** .47*** .41*** .55*** .29** .47*** .35*** .39*** .30** .47*** .35*** .33*** .65*** .06 .15 .29** .02
3.06** 4.83*** 5.33*** 1.81 5.05*** 6.73*** 7.96*** 2.35* 5.76*** .41 2.53* 4.55*** 6.14*** 3.78*** 3.03** 2.05* 2.84** 4.52*** .56
335 324 321 319 322 323 320 320 322 322 323 318 320 330 329 330 328 328 326
p < .05. p < .01. p < .001.
3. Results 3.1. Cycling frequency, helmet ownership and helmet use Chi-square statistics about participant type (child vs parent) showed that children used bicycle more often than adults
v2(1, N = 337) = 54.09, p < 0.001; 80.5% of children and 44.3% of adults reported that they ride a bike minimum of two times a week. In two-way ANOVA (gender participant type), both gender (F(1, 334) = 7.31, p < 0.01) and participant type (adults vs. child) F(1, 334) = 30.17, p < 0.001) main effects but no gender participant type interaction were found. Among children, a negative correlation between cycling frequency and age was found (r = 0.18, p < 0.01). Among adults, age was not significantly related to cycling frequency. In general, helmet ownership rate was high (88.9%). Helmet ownership was more common among children (91.6%) than adults (83.0%), v2(1, N = 332) = 5.34, p < 0.05. Gender was not related to ownership neither among adults nor children. Age correlated negatively with helmet ownership (Spearman’s rho = 0.22, p < 0.001) among children but no correlation between helmet ownership and age was found among adults. Among adults, the frequencies of the answers to the question ‘‘how often do you wear a helmet’’ were 11.3% for ‘‘never’’, 8.5% for ‘‘rarely’’, 9.4% for ‘‘sometimes’’, 15.1% for ‘‘often’’, and 53.8% for ‘‘always’’. Among, children the frequencies were 16.6%, 17.0%, 11.1%, 10.2%, 43.8%, respectively. Thus, adults reported more frequent helmet use (Table 1). In two-way ANOVA (gender participant type), a statistically significant main effect of participant type (adults vs. child) was observed F(1, 333) = 6.03, p < 0.05). No main effect of gender was observed while there was an interaction between gender and participant type, F(1, 333) = 3.93, p < 0.05); the difference between children and adults in helmet use was observed only among males, t(153) = 2.87, p < 0.01. School girls used helmet more often than school boys, t(229) = 2.11, p < 0.05, whereas no differences was observed between adult men and women or school girls and women. In this sample, the least frequent helmet users were school boys and the most frequent helmet users were adult men (Table 1). Age correlated strongly and significantly with helmet use among children but not among adults (Table 1). 3.2. Difference between children and adults in barriers and facilitators Descriptive statistics (M, SD), comparisons between children and adults in self-reported risk assessments, barriers and facilitators as well as correlation to helmet use frequency can be found in Table 1.
Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
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T. Lajunen / Transportation Research Part F xxx (2015) xxx–xxx
A difference between adults and children was found in one risk item (seriousness of the consequences) and in the summary item but not in the probability of an accident. Risk was only weakly but significantly related to helmet use among children. In general, risk estimation did not seem to be an important factor among adults or children. The most frequently reported barriers for children were shortness of the trip, uncomfortable helmet and looking ridiculous while the most common facilitators were the belief that the helmet protects and feeling safer with helmet while among adults the most reported barriers were shortness of the trip and just forgetting to use the helmet. Belief in the effectiveness as a protective device, feeling safer while wearing a helmet and helmet wearing as habit were the most frequently reported facilitators. T-tests (child vs adult) showed that children scored higher (reported higher agreement) in 10 of 12 barrier items but scored lower in 3 of the six facilitator items (Table 1). In two facilitator items children scored higher than adults. These results indicate that children in general express higher agreement with barriers than adults and lower agreement with facilitators. Table 1 presents Pearson correlation coefficients between risk items, barriers, facilitators and helmet use among adults and children. The highest (negative) correlations were between feeling helmet necessary and rather using a cap than a helmet among children and between ‘‘looking ridiculous’’ among adults. Strongest (positive) correlations were found between helmet use and helmet use as habit among both children and adults (Table 1). 3.3. Constructing the barrier and facilitator scales: factor analysis In order to construct sum variables ‘‘barriers’’ and ‘‘facilitators’’, the 18 barrier and facilitator items were factor analysed by using principal axis factoring. ‘‘Eigenvalue > 1.0’’ criterion and the Scree plot indicated a clear two factors structure with separate factors for barriers and facilitators. The correlation between factors was 0.30, so an orthogonal Varimax rotation was applied. The final two-factor solution explained 48.3% of variance; the first factor explained 36.1%.and the second 12.2%. The results of the exploratory factor analysis can be seen in Table 2. Table 2 shows that all barrier items loaded on the first factor and facilitator items to the second factor. The alpha reliability coefficients for the barrier (F1) and facilitator (F2) scales were 0.93 and 0.73, respectively. 3.4. Predictors of helmet use among children and adults: regression analyses In order to investigate the possible different reasons for using (and not using) helmet among children and adults, hierarchical multiple regression analyses were conducted separately for children and adults. In the first step, age, sex and frequency of cycling were entered to the model. In the second step, two risk variables (probability and severity as well as ‘‘risk’’ moderator variable) and barrier and facilitator variables were entered into the model by using forward selection method (Criterion: Probability-of-F-to-enter 6.050). The results of the regression analyses can be found in Table 3. Table 3 shows that age and gender as well as barriers and facilitators predicted helmet use among children whereas neither cycling frequency nor risk variables predicted helmet use. The most important predictor was age (b = .41) followed by barriers (b = .38) and facilitators (b = .20). The helmet use frequency decreased according to a child’s age and barriers were more related to helmet use than facilitators. The final model explained 73% of variance in helmet use among children. Table 2 Factor structure of barriers and facilitators. Barriers Barriers I don’t need because I just ride a bicycle close to home I think the helmet looks ridiculous I do not need it because I’m not riding a bicycle where the motor vehicles are I would rather use a hat or cap It is uncomfortable to wear It messes up my hair I don’t need it I’m just going to a short trip It gets too hot or cold I think other people think it’s stupid to wear a helmet I have no place and add it from me when I get there, so I have to carry it I forget to put it on Facilitators I feel safer with bicycle helmet on I’m going to ride a bike a long way It protects me in traffic My friends use it It is a habit I cycle a lot on hard surfaces
.82 .75 .73 .72 .72 .72 .71 .71 .67 .63 .63 .50 .49
.55
Facilitators
.31
.36
.25
.62 .57 .52 .52 .49 .47
Note: factor loadings <.30 omitted.
Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
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Table 3 Results of the regression analyses for predicting helmet use among children and adults. Block
Variable
Children (F5, 1
218
2
Adults (F4, 1
Barriers Facilitators 81
= 20.96***) Age Sex (1 = man, 2 = woman) Often How often do you ride a bike?
2 ⁄⁄ * ***
= 115.50***) Age Sex (1 = boy, 2 = girl) How often do you ride a bike?
Barriers
R2
B
Std. Error
Beta
t
.60
.37 .30 .01
.04 .11 .04
.41 .10 .01
8.31*** 2.66* .25
.73
.54 .34
.07 .08
.38 .20
7.92*** 4.32***
.35
.02 .09 .34
.02 .27 .06
.09 .03 .46
1.08 .32 5.34***
.52
.79
.15
.44
5.24***
p < .01. p < .05. p < .001.
The regression results among adults differed from those of children in two ways: age, gender or facilitator sum scores were not related to bicycle helmet use. Only the frequency of cycling (b = .46) and barriers age (b = .44) were related to helmet use. The final model explained 52% of variance in helmet use. 4. Discussion In the present study, bicycle helmet use was studied among children and adults in Norway which ranks as the second best country in traffic safety in OECD (OECD, 2014). The aim of the study was to investigate if there were differences between adults and children in the reasons for using or not using a bicycle helmet. If such differences existed, they should be taken into account when planning safety interventions among adult and child cyclists. In the present study based on anonymous self-reports, adults used helmet more frequently than children and child’s age was a strong predictor of helmet use. These results are in line with some earlier studies, which have reported that helmet use declines with age (Klein et al., 2005; Rezendes, 2006). In a large survey by Finnoff & al. (Finnoff et al., 2001), the highest proportion of helmet users (62%) were found among 50+ year-olds while the lowest user rate was reported among 11 to 19 year olds (31%). In a study conducted among secondary and upper secondary school pupils (age range 12–19) in Finland, the odds-ration for age was 0.70 (Lajunen & Räsänen, 2001). In the present study, the pupils were 10–16 year old (mean 12 years), which is the age bracket in which the teenagers’ helmet use tends to drop (Rezendes, 2006). In this Norwegian data, girls had slightly higher use rate than boys, which is similar to the findings by Parkin, Khambalia, Kmet, and Macarthur (2003). The difference between boys and girls was, however, small and we can conclude that gender is not a very important factor influencing helmet use among Norwegian primary and secondary school children. The main aim of this study was to identify the similarities and differences between adults’ and children’s self-reported reasons to use/not use a bicycle helmet. Interestingly, adults were more pessimistic about the health consequences of a possible accident than children but neither the perceived risk nor perceived severity of consequences (or the combination of these) predicted helmet use. In a study by Finnoff & al., majority of adults and adolescents indicated that was only a ‘‘slight risk’’ of head injury when cycling without helmet (Finnoff et al., 2001). It seems that cyclists – both adults and children – perceive their personal accident risk low and, thus, risk of getting seriously injured is not linked to helmet use. While cyclists recognize the protective value of the helmet, they simply do not perceive cycling as a high risk activity (Finnoff et al., 2001). These results indicate that bicycle helmet campaigns should not rely on cyclists’ ability to assess the cycling related risks. Another problem in ‘‘scare campaigns’’ for promoting helmet use is that they (if successful) might actually reduce cycling instead of increasing helmet use. The most important barrier for helmet use was ‘‘I’m just going to a short trip’’ (and thus do not need a helmet) both among children and adults. Among children, the second most common barrier was that the helmet is uncomfortable. For adults, forgetting to us the helmet was the second most common reason for not using one. These barriers are actually related to each other: since the helmet is uncomfortable, it is easy to skip using it especially in short trips. Helmet use is uncomfortable especially for children, who use bicycle mostly for recreational purposes and might combine playing to cycling. The bicycle helmet of being ‘‘uncomfortable’’, ‘‘too warm or cold’’ or ‘‘no fitting to hair style’’ have been frequently reported as barriers in earlier studies (Finnoff et al., 2001; Forjuoh et al., 2003; Loubeau, 2000; Pierce et al., 2014; Rezendes, 2006; Stevenson & Lennie, 1992). Interestingly, these barriers of helmet use all refer to bad design of helmets and, thus, cannot be removed simply by attitude campaigns. This is at the same time encouraging and discouraging finding. On one hand it means that the main barriers can be lifted by improving helmet design while on the other hand improving helmets can be difficult and costly.
Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
T. Lajunen / Transportation Research Part F xxx (2015) xxx–xxx
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Most of the studies about attitudes to helmet use have concentrated on barriers instead of facilitators or benefits. In the present study, the most important facilitator of helmet use among both children and adults use was the habit of using a helmet. The other important factor in both samples was ‘‘feeling safer with a helmet’’. Among children, having friends who use a helmet was also an important correlate of helmet use. These three issues, however, offer very little for traffic safety work: the main challenge is to start the habit at the first place. It can be assumed that developing the habit of using a helmet or having friends using a helmet is actually just another verbalization of the same problem of motivating cyclists to use a helmet. Regression analysis showed that the model explained an impressive amount of variance in helmet use among children (73%) and that the barriers were more important predictors of helmet use than facilitators. Among adults, only barriers but not facilitators predicted the helmet use. Among children and adults, barriers and facilitators (for children) or only barriers (for adults) were significant and important (13% of variance explained among children and 17% among adults) predictors of helmet use. This finding means that lowering the barriers would result in significant increase in helmet use. The role of barriers compared to benefits (or ‘‘facilitators’’ in the present study) has been demonstrated in theoretical studies applying the Health Belief Model to helmet use (Lajunen & Räsänen, 2004; Ross, Ross, Rahman, & Cataldo, 2010). The present study together with the earlier studies how that lowering the barriers is the best option for bicycle helmet use campaigns. This study has some shortcomings which should be taken into account. First, the study was conducted in Norway – one of the safest countries in the world – what might limit the applicability of the results to less safe regions. For example, Secginki et al. studied helmet use in a upper middle income country with high traffic fatality rate and very low helmet use rate and reported not owning a helmet as a significant barrier (Secginli et al., 2013). Norway is the wealthiest country among OECD countries (with gross national income of 67440 USD per capita in 2012) and the second safest country in OECD in terms of traffic safety with 33 road fatalities per million inhabitants or 51 fatalities per million vehicles (OECD, 2014). Findings based on Norwegian school children might not generalize well to countries with lower income and safety level. For example, the bicycle helmet ownership and the related costs do not seem to be a problem in Norway but can be a significant factor in low income countries. Second, the sample size was small and represents just one region in Norway. It is possible that different factors are related to helmet use in different regions. Third, this study was based on self-reports. Although the participants were assured about anonymity and confidentiality (no names or student numbers were recorded), there is still a slight possibility that the participants embellished their answers. In school settings, there is a possibility that parents want to show higher concern for safety than they actually have. Since the study was based on anonymous answering, we were not able to investigate if the non-responding parents were different from those who returned the filled questionnaire. It is possible that parents who participated in the study had higher concern for traffic safety or were more involved in their children’s school and free time activities than those who did respond. In the present study, factors predicting helmet use were studies among adults and children and comparisons showed some similarities and differences in predictors of helmet use. Age and sex were controlled in regression analysis. In future analyses of children’s helmet use, it would be important to investigate how parents’ helmet use and related attitudes predict their children’s helmet use and attitudes and how age and sex of the child might moderate these relationships. It can be assumed, for example, that young children are more likely to follow their parents’ example than teenagers. In conclusion, it seems that barriers for helmet use – especially among adults – are more related to decision to use a helmet than the facilitators. Especially such helmet related features as the helmets of being uncomfortable, helmets not fitting to hairstyle or helmets being too cold or hot should be addressed by improved helmet design. Social psychological factors like peer pressure can be approached best with school based interventions. In general, targeting the barriers might produce better results in helmet wearing rate than interventions trying to emphasise the benefits of helmet use. Acknowledgements I would like to thank Professors Tornbjørn Rundmo and Hermundur Sigmundsson for their most valuabe support for this study. This study was supported by Department of Psychology, Norwegian University for Science and Technology (NTNU). The study is part of COST Action TU1101 ‘‘Towards safer bicycling through optimization of bicycle helmets and usage’’. References Amoros, E., Chiron, M., Martin, J. L., Thélot, B., & Laumon, B. (2012). Bicycle helmet wearing and the risk of head, face, and neck injury: A French case-control study based on a road trauma registry. Injury Prevention, 18(1), 27–32. Attewell, R. G., Glase, K., & McFadden, M. (2001). Bicycle helmet efficacy: A meta-analysis. Accident Analysis and Prevention, 33(3), 345–352. Bambach, M. R., Mitchell, R. J., Grzebieta, R. H., & Olivier, J. (2013). The effectiveness of helmets in bicycle collisions with motor vehicles: A case-control study. Accident Analysis and Prevention, 53, 78–88. Cripton, P. A., Dressler, D. 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Barriers and facilitators of bicycle helmet use among children and their parents Timo Lajunen Department of Psychology, Norwegian University for Science and Technology (NTNU), 7491 Trondheim, Norway
a r t i c l e
i n f o
Article history: Received 4 October 2014 Received in revised form 11 March 2015 Accepted 11 March 2015 Available online xxxx Keywords: Bicycle helmet use Barriers Facilitators Risk School children Adults
a b s t r a c t Despite the fact that bicycle helmet use protects against head injuries, helmet use rate is still low even in countries with high concern for traffic safety. Earlier research shows that helmet use declines with age and that helmet use is low especially among teenagers. The aim of the present study was to investigate barriers and facilitators of helmet use among primary and secondary school pupils and their parents. Identical surveys were conducted among school children (n = 235) and their parents (n = 106). Children’s and adults’ responses concerning cycling, helmet use, helmet ownership, risk assessment and barriers and facilitators were compared and separate regression analyses conducted. Helmet use rate was lower among pupils than adults and they scored higher in most of the barrier items. The results of regression analyses showed that among children, age, gender, barriers and facilitators predicted helmet use while among adults only frequency of cycling and barriers were related to helmet use. Among children, the strongest correlates of not using a helmet were the belief of not needing a helmet and wish to use a cap or a hat instead. Having a helmet wearing as a habit and feeling safer were the strongest correlates of using helmet. Among adults, the strongest correlates of not using a helmet were ‘‘helmet looks ridiculous’’, ‘‘just going to short trip’’ and riding close to home while the strongest correlate of using a helmet was the habit of helmet use. It was concluded that targeting the barriers in helmet wearing campaigns might work better both among children and adults than emphasising the benefits at least among Norwegian child and adult cyclists. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Cycling is a healthy and environmentally sound means of transportation (Lindsay, Macmillan, & Woodward, 2011). For some road user groups, like school children, cycling provides often the only effective means of transportation when distances are too long for walking and when car or bus transportation is not available or possible because of the age of the traveller. This is especially the case in sparsely populated countries like Norway. While virtually all countries promote bicycle use among children, teenagers and adults, a cycling accident is also one of the main risk factors in a child’s or teenager’s life (OECD, 2004; World Health Organization, 2008). For example in UK, about 75% of trauma among children occurs on the roads (Sinha & Lander, 2013). Therefore, it is essential to improve passive safety (i.e. protection in the case of an accident) among cyclists and especially among children (World Health Organization, 2008). Several studies show that a bicycle helmet is an effective way of preventing head injuries. According to a Cochrane survey conducted already in 1999, head injury is a leading cause of death among cyclists and bicycle helmets are effective in E-mail address: [email protected] http://dx.doi.org/10.1016/j.trf.2015.03.005 1369-8478/Ó 2015 Elsevier Ltd. All rights reserved.
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reducing head, brain and face injuries (Thompson, Rivara, & Thompson, 1999). A qualitative review about the protective effectiveness of helmets among children concluded that bicycle helmets are effective even when taking biases into account and recommended habitual used of helmets (Lastennet, Sizun, Dobrzynski, & De Parscau, 2001). Attewell, Glase, and McFadden (2001) conducted one of the first quantitative reviews of bicycle helmet use and head injuries. They reported a summary odds ratio estimate for efficacy as 0.40 for head injury, 0.42 for brain injury, 0.53 for facial injury and 0.27 for fatal injury (Attewell et al., 2001). This indicates a statistically significant protective effect of helmets and the authors concluded that ‘‘the evidence is clear that bicycle helmets prevent serious injury and even death’’ (Attewell et al., 2001). While some later investigations claim that the results of Attewell et al. (2001) showed inflated safety benefits for helmet use because of some methodological problems (e.g. publication bias) (Curnow, 2003; Elvik, 2011), it is still clear that bicycle helmets provide an effective and easy means for protection against head trauma among cyclists. The effectiveness of bicycle helmet in head injury reduction has recently been demonstrated in several case-control studies (Amoros, Chiron, Martin, Thélot, & Laumon, 2012; Bambach, Mitchell, Grzebieta, & Olivier, 2013; Hagel, 2011; Persaud, Coleman, Zwolakowski, Lauwers, & Cass, 2012) and biomechanical studies (Cripton, Dressler, Stuart, Dennison, & Richards, 2014; Schejbalová, Micˇunek, & Schmidt, 2013). World Health Organization (2008) has estimated by using a cost-benefit analysis that one unit of money invested on bicycle helmet campaigns returns as 29 units. We can expect the protective effect to be more significant among children and teenagers, who get involved in bicycle crashes more often than adults due to their way of using bicycles as means of commuting and in free time activities (Sleet, Ballesteros, & Borse, 2010). The main problem in cycling helmets is simply that the helmet use rate is low in many countries while there seem to be high variation in helmet rates among different countries and regions. Klein, Thompson, Scheidt, Overpeck, and Gross (2005) studied the prevalence of helmet use in 26 countries by using a school based survey. According to results, reported helmet use varied greatly by country from 39.2% to 1.9%. Hence, helmet use did not reach 50% in any country (Klein et al., 2005). The highest helmet use rate (39.1%) was reported in Norway. Since the Klein & al.’s study was conducted over 15 years ago, we can assume that the current helmet wearing rates are higher. In an observational study conducted in Eastern Norway in 2008, 39% (35% females and 41% males) of passing bicyclists above 17 years of age used a helmet (Muskaug, Nygaard, Rosland, Johansen, & Sjøvold, 2009). It should be noted, however, that this figure included only adults and was based on observed helmet use unlike the 26 country study by Klein et al. (2005). According to Trygg Trafikk – The Norwegian Council for Road Safety – the current helmet wearing rate in Norway is 54% (Trygg Trafikk, 2014). Although there is a considerable increase in helmet use when compared to Klein et al. (2005) and Muskaug et al. (2009), the helmet wearing rate is still low even in Norway, which ranks as the second best in road safety (measured with road fatalities per registered vehicle or fatalities per vehicle-kilometre) in 2011 (OECD, 2014). In the present study, the aim was to investigate reasons for not using a bicycle helmet among primary and secondary school children and their parents in Norway. Researchers have been investigating reasons for children and adolescents not wearing a bicycle helmet since 80s. In a study by Finnoff & all. conducted in 1999 in Minnesota, one of the most common reasons for not using a helmet was not owning one (Finnoff, Laskowski, Altman, & Diehl, 2001). Robertson and colleagues studied reasons for not using a bicycle helmet in rural Saskatchewan and found that helmet costs and lack of awareness were main barriers to helmet use (Robertson, Lang, & Schaefer, 2014). Secginli, Cosansu, & Nahcivan investigated prevalence of bicycle helmet use in two primary schools in Istanbul and reported a very low helmet use rate of 4.4% among 8–16 year olds (Secginli, Cosansu, & Nahcivan, 2013). One of the barriers for helmet use was not owning one in addition to parents’ and friends’ helmet use. Children’s and adolescent helmet ownership is probably partly related to the same factors as helmet use (e.g., attitudes) in addition to parents’ education and income level (Towner & Marvel, 1992). Many studies have shown that bicycle helmet use is related to the a child’s or teenager’s age so that younger children are more likely than teenagers to wear helmets (Dellinger & Kresnow, 2010; Klein et al., 2005; Lang, 2007; O’Callaghan and Nausbaum, 2006). Klein et al. (2005) analysed data from 26 countries and found that age was the strongest individual predictor of use across countries. In general, younger primary school children use helmet regularly whereas the use rate declines among secondary school aged children. The main challenge in bicycle helmet interventions is to prevent decrease and maintain high use rates during adolescence. To develop effective interventions, it is essential to study which factors influence helmet use in different age groups. It can be assumed that different specific factors are relevant for children (e.g. parent’s opinions), teenagers (e.g. peer pressure) and adults (e.g. convenience). In the present study, factors related to bicycle helmet use are studied among primary and secondary school children and their parents. Bicycle helmet use has been studied from different points of view ranging from peer influence and household factors (Dellinger & Kresnow, 2010) to social psychological models of helmet use (Fishman, Washington, & Haworth, 2012; Lajunen & Räsänen, 2001, 2004). Hence, the previous research has helped us to identify several factors influencing the helmet wearing rates among children and adolescents. The most important barriers to helmet use seem to be negative peer pressure and fear of appearing dumb (Forjuoh, Schuchmann, Fiesinger, & Mason, 2003; Howland et al., 1989; Loubeau, 2000; Rezendes, 2006; Stevenson & Lennie, 1992), lack of knowledge and awareness (Pierce, Palombaro, & Black, 2014; Robertson et al., 2014), inconvenience and finding the helmet uncomfortable (Finnoff et al., 2001; Loubeau, 2000; Rezendes, 2006; Stevenson & Lennie, 1992), and poor fit of helmets due to hair style (Forjuoh et al., 2003; Pierce et al., 2014). In some studies, perceiving the injury risk low or considering oneself as a safe rider (and, thus, facing low accident risk) have been listed as barriers to helmet use (Finnoff et al., 2001; Forjuoh et al., 2003). Interestingly, riders may agree that helmets provide a good protection against a head injury but still not use one if they assess the injury risk low (Finnoff et al., 2001). Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
T. Lajunen / Transportation Research Part F xxx (2015) xxx–xxx
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Literature review shows that barriers have been studied more than the facilitators of helmet use. Earlier studies show that having friends and parents using a helmet is positively related to helmet use (Finnoff et al., 2001; Lajunen & Räsänen, 2001; Secginli et al., 2013). In addition to friends’ and parents’ positive example, also habitual helmet use as well as having been using helmet earlier have been reported to be related to helmet wearing (Lajunen & Räsänen, 2004; O’Callaghan and Nausbaum, 2006; Page, Follett, Scanlan, Hammermeister, & Friesen, 1996). The problem with these facilitators is to get the friends or parents to use a helmet at the first place. Cycling habits and frequency depend on the climate (rainfall, snow, temperature) and traffic conditions (geography of the landscape, availability of bicycle route network) in large degree. Therefore, cycling habits and experienced facilitators and barriers of helmet use depend largely on the local conditions. For example, in sparsely habited Scandinavia, bicycle is an essential means of transportation whereas in some other countries bicycle is mostly used for recreational purposes. Similarly, the barriers for helmet wearing vary among countries; in a country with warm climate, one of the main barriers is the inconvenience related to over-heating and sweating (Finnoff et al., 2001). Moreover, climate, geography and culture related factors may influence children’s, teenagers’ and adults’ helmet use differently. The aim of the present study is to investigate barriers and facilitators of helmet use among Norwegian primary and secondary school pupils and their parents. The aim is to investigate if adults and children differ in terms of barriers and facilitators of bicycle helmet use in a country with high traffic safety awareness. 2. Method 2.1. Procedure and participants Survey data were collected in two schools (one primary and one secondary school) in Sør-Trøndelag region in Norway. Two similar questionnaire forms were prepared: a child’s form and a parents’ form. The core items in the questionnaires were identical (except few cases in which the wording was adjusted according to the age) while some questions were specific for children (e.g. grade) and some questions were specific to adults (e.g. education level). Since the core items were identical, children’s and adults’ responses could be directly compared. The questionnaires were delivered in classroom and the participants were assured about anonymity and confidentiality. Children filled in their copy during the class hour while the parents filled the questionnaire at home (which was delivered to them by their child) and returned the filled questionnaire in a sealed envelope. Since the children filled the questionnaire in classroom, the response rate was 100% while 45.1% of the parents returned a filled questionnaire. Since the data collection was based on anonymity, we could not send a reminder to those parents who did not participate. The Respondents for this study were 235 pupils (51.3% male) and 106 parents (34.6% male). The age range among pupils was between 10 and 16 years (M = 12.7 years, SD = 1.80) and among adults 29–60 years (M = 42.3, SD = 5.72). 2.2. Measures 2.2.1. Cycling frequency, helmet ownership and helmet use Frequency of cycling was measured with question ‘‘How often do you ride a bike?’’ (Response scale: 1 = Never, 2 = Rarely, 3 = Once a month, 4 = Once in two weeks, 5 = Once a week, 6 = 2–6 times a week, 7 = Every day) and the helmet use frequency with question ‘‘How often do you use helmet when you cycle?’’ (Response scale: 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = All the time). 2.2.2. Injury risk Respondents’ evaluation of their personal injury risk was measured with a question about the likelihood of an accident (‘‘There is a big chance that I fall while riding a bicycle’’) and severity of the consequence (‘‘There is a big chance that I end up at the doctor/hospital if I fall while riding a bicycle’’). The responses to both questions were given with a 5-point scale (1 = strongly disagree, 5 = strongly agree). In addition, an interaction variable ‘‘risk’’ was calculated by multiplying the likelihood of an accident with severity of the consequences. 2.2.3. Barriers and facilitators Barrier and facilitator items were collected from previous literature and new items were created in a brain storming session. The final item pool consisted of 18 statements including 12 barrier items and 6 facilitator items (see Table 1). The instruction for barrier items was ‘‘When I do not use a helmet it is because. . .’’ and for facilitator items ‘‘When I use helmet it is because. . .’’ A 5-point Likert response scale was used (from 1 = strongly disagree to 5 = strongly agree). This structure was chosen, because assumed that it would fit to both adults and pupils. 2.2.4. Background information Participants’ age and gender were also recorded but not any identification information like class.
Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
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Table 1 Descriptive statistics, correlations between the items and frequency of helmet use and between children and adults in the study variables. Children Mean How often do you use helmet when you cycle? Age Cycling frequency There is a big chance that I fall while riding a bicycle There is a big chance that I end up at the doctor/hospital if I fall while riding a bicycle Risk It is uncomfortable to wear I have no place and add it from me when I get there, so I have to carry it I’m just going to a short trip It messes up my hair I think the helmet looks ridiculous I think other people think it’s stupid to wear a helmet I do not need it because I’m not riding a bicycle where the motor vehicles are I don’t need it I forget to put it on It gets too hot or cold I don’t need because I just ride a bicycle close to home I would rather use a hat or cap It protects me in traffic It is a habit My friends use it I’m going to ride a bike a long way I feel safer with bicycle helmet on I cycle a lot on difficult surfaces * ** ***
SD
Adults R
Mean
Children vs. adults SD
R
t-test
df *
3.48 12.69 5.65 2.69 2.43
1.58 1.80 1.62 1.28 1.29
1.00 .76*** .16* .15* .03
3.93 42.27 4.38 2.81 3.15
1.43 5.72 1.98 1.39 1.21
1.00 .01 .45*** .04 .05
2.48 – 6.24*** .78 4.78***
334 – 335 336 335
7.38 2.94 2.46 3.03 2.64 2.85 2.59 2.27 2.42 2.36 2.31 2.73 2.60 4.48 3.61 3.11 3.89 3.97 3.16
6.35 1.55 1.50 1.54 1.62 1.57 1.44 1.40 1.49 1.35 1.37 1.54 1.62 .93 1.42 1.47 1.25 1.27 1.31
.10 .58*** .40*** .46*** .50*** .59*** .49*** .62*** .78*** .35** .42*** .56*** .68*** .40*** .68*** .51*** .25*** .65*** .21**
9.75 2.06 1.58 2.68 1.71 1.67 1.36 1.88 1.48 2.29 1.90 1.93 1.51 4.85 4.10 2.77 3.45 4.58 3.07
6.95 1.40 .99 1.58 1.22 1.11 .75 1.28 .89 1.43 1.26 1.20 1.02 .51 1.23 1.32 1.48 .80 1.36
.07 .42*** .35*** .47*** .41*** .55*** .29** .47*** .35*** .39*** .30** .47*** .35*** .33*** .65*** .06 .15 .29** .02
3.06** 4.83*** 5.33*** 1.81 5.05*** 6.73*** 7.96*** 2.35* 5.76*** .41 2.53* 4.55*** 6.14*** 3.78*** 3.03** 2.05* 2.84** 4.52*** .56
335 324 321 319 322 323 320 320 322 322 323 318 320 330 329 330 328 328 326
p < .05. p < .01. p < .001.
3. Results 3.1. Cycling frequency, helmet ownership and helmet use Chi-square statistics about participant type (child vs parent) showed that children used bicycle more often than adults
v2(1, N = 337) = 54.09, p < 0.001; 80.5% of children and 44.3% of adults reported that they ride a bike minimum of two times a week. In two-way ANOVA (gender participant type), both gender (F(1, 334) = 7.31, p < 0.01) and participant type (adults vs. child) F(1, 334) = 30.17, p < 0.001) main effects but no gender participant type interaction were found. Among children, a negative correlation between cycling frequency and age was found (r = 0.18, p < 0.01). Among adults, age was not significantly related to cycling frequency. In general, helmet ownership rate was high (88.9%). Helmet ownership was more common among children (91.6%) than adults (83.0%), v2(1, N = 332) = 5.34, p < 0.05. Gender was not related to ownership neither among adults nor children. Age correlated negatively with helmet ownership (Spearman’s rho = 0.22, p < 0.001) among children but no correlation between helmet ownership and age was found among adults. Among adults, the frequencies of the answers to the question ‘‘how often do you wear a helmet’’ were 11.3% for ‘‘never’’, 8.5% for ‘‘rarely’’, 9.4% for ‘‘sometimes’’, 15.1% for ‘‘often’’, and 53.8% for ‘‘always’’. Among, children the frequencies were 16.6%, 17.0%, 11.1%, 10.2%, 43.8%, respectively. Thus, adults reported more frequent helmet use (Table 1). In two-way ANOVA (gender participant type), a statistically significant main effect of participant type (adults vs. child) was observed F(1, 333) = 6.03, p < 0.05). No main effect of gender was observed while there was an interaction between gender and participant type, F(1, 333) = 3.93, p < 0.05); the difference between children and adults in helmet use was observed only among males, t(153) = 2.87, p < 0.01. School girls used helmet more often than school boys, t(229) = 2.11, p < 0.05, whereas no differences was observed between adult men and women or school girls and women. In this sample, the least frequent helmet users were school boys and the most frequent helmet users were adult men (Table 1). Age correlated strongly and significantly with helmet use among children but not among adults (Table 1). 3.2. Difference between children and adults in barriers and facilitators Descriptive statistics (M, SD), comparisons between children and adults in self-reported risk assessments, barriers and facilitators as well as correlation to helmet use frequency can be found in Table 1.
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A difference between adults and children was found in one risk item (seriousness of the consequences) and in the summary item but not in the probability of an accident. Risk was only weakly but significantly related to helmet use among children. In general, risk estimation did not seem to be an important factor among adults or children. The most frequently reported barriers for children were shortness of the trip, uncomfortable helmet and looking ridiculous while the most common facilitators were the belief that the helmet protects and feeling safer with helmet while among adults the most reported barriers were shortness of the trip and just forgetting to use the helmet. Belief in the effectiveness as a protective device, feeling safer while wearing a helmet and helmet wearing as habit were the most frequently reported facilitators. T-tests (child vs adult) showed that children scored higher (reported higher agreement) in 10 of 12 barrier items but scored lower in 3 of the six facilitator items (Table 1). In two facilitator items children scored higher than adults. These results indicate that children in general express higher agreement with barriers than adults and lower agreement with facilitators. Table 1 presents Pearson correlation coefficients between risk items, barriers, facilitators and helmet use among adults and children. The highest (negative) correlations were between feeling helmet necessary and rather using a cap than a helmet among children and between ‘‘looking ridiculous’’ among adults. Strongest (positive) correlations were found between helmet use and helmet use as habit among both children and adults (Table 1). 3.3. Constructing the barrier and facilitator scales: factor analysis In order to construct sum variables ‘‘barriers’’ and ‘‘facilitators’’, the 18 barrier and facilitator items were factor analysed by using principal axis factoring. ‘‘Eigenvalue > 1.0’’ criterion and the Scree plot indicated a clear two factors structure with separate factors for barriers and facilitators. The correlation between factors was 0.30, so an orthogonal Varimax rotation was applied. The final two-factor solution explained 48.3% of variance; the first factor explained 36.1%.and the second 12.2%. The results of the exploratory factor analysis can be seen in Table 2. Table 2 shows that all barrier items loaded on the first factor and facilitator items to the second factor. The alpha reliability coefficients for the barrier (F1) and facilitator (F2) scales were 0.93 and 0.73, respectively. 3.4. Predictors of helmet use among children and adults: regression analyses In order to investigate the possible different reasons for using (and not using) helmet among children and adults, hierarchical multiple regression analyses were conducted separately for children and adults. In the first step, age, sex and frequency of cycling were entered to the model. In the second step, two risk variables (probability and severity as well as ‘‘risk’’ moderator variable) and barrier and facilitator variables were entered into the model by using forward selection method (Criterion: Probability-of-F-to-enter 6.050). The results of the regression analyses can be found in Table 3. Table 3 shows that age and gender as well as barriers and facilitators predicted helmet use among children whereas neither cycling frequency nor risk variables predicted helmet use. The most important predictor was age (b = .41) followed by barriers (b = .38) and facilitators (b = .20). The helmet use frequency decreased according to a child’s age and barriers were more related to helmet use than facilitators. The final model explained 73% of variance in helmet use among children. Table 2 Factor structure of barriers and facilitators. Barriers Barriers I don’t need because I just ride a bicycle close to home I think the helmet looks ridiculous I do not need it because I’m not riding a bicycle where the motor vehicles are I would rather use a hat or cap It is uncomfortable to wear It messes up my hair I don’t need it I’m just going to a short trip It gets too hot or cold I think other people think it’s stupid to wear a helmet I have no place and add it from me when I get there, so I have to carry it I forget to put it on Facilitators I feel safer with bicycle helmet on I’m going to ride a bike a long way It protects me in traffic My friends use it It is a habit I cycle a lot on hard surfaces
.82 .75 .73 .72 .72 .72 .71 .71 .67 .63 .63 .50 .49
.55
Facilitators
.31
.36
.25
.62 .57 .52 .52 .49 .47
Note: factor loadings <.30 omitted.
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T. Lajunen / Transportation Research Part F xxx (2015) xxx–xxx
Table 3 Results of the regression analyses for predicting helmet use among children and adults. Block
Variable
Children (F5, 1
218
2
Adults (F4, 1
Barriers Facilitators 81
= 20.96***) Age Sex (1 = man, 2 = woman) Often How often do you ride a bike?
2 ⁄⁄ * ***
= 115.50***) Age Sex (1 = boy, 2 = girl) How often do you ride a bike?
Barriers
R2
B
Std. Error
Beta
t
.60
.37 .30 .01
.04 .11 .04
.41 .10 .01
8.31*** 2.66* .25
.73
.54 .34
.07 .08
.38 .20
7.92*** 4.32***
.35
.02 .09 .34
.02 .27 .06
.09 .03 .46
1.08 .32 5.34***
.52
.79
.15
.44
5.24***
p < .01. p < .05. p < .001.
The regression results among adults differed from those of children in two ways: age, gender or facilitator sum scores were not related to bicycle helmet use. Only the frequency of cycling (b = .46) and barriers age (b = .44) were related to helmet use. The final model explained 52% of variance in helmet use. 4. Discussion In the present study, bicycle helmet use was studied among children and adults in Norway which ranks as the second best country in traffic safety in OECD (OECD, 2014). The aim of the study was to investigate if there were differences between adults and children in the reasons for using or not using a bicycle helmet. If such differences existed, they should be taken into account when planning safety interventions among adult and child cyclists. In the present study based on anonymous self-reports, adults used helmet more frequently than children and child’s age was a strong predictor of helmet use. These results are in line with some earlier studies, which have reported that helmet use declines with age (Klein et al., 2005; Rezendes, 2006). In a large survey by Finnoff & al. (Finnoff et al., 2001), the highest proportion of helmet users (62%) were found among 50+ year-olds while the lowest user rate was reported among 11 to 19 year olds (31%). In a study conducted among secondary and upper secondary school pupils (age range 12–19) in Finland, the odds-ration for age was 0.70 (Lajunen & Räsänen, 2001). In the present study, the pupils were 10–16 year old (mean 12 years), which is the age bracket in which the teenagers’ helmet use tends to drop (Rezendes, 2006). In this Norwegian data, girls had slightly higher use rate than boys, which is similar to the findings by Parkin, Khambalia, Kmet, and Macarthur (2003). The difference between boys and girls was, however, small and we can conclude that gender is not a very important factor influencing helmet use among Norwegian primary and secondary school children. The main aim of this study was to identify the similarities and differences between adults’ and children’s self-reported reasons to use/not use a bicycle helmet. Interestingly, adults were more pessimistic about the health consequences of a possible accident than children but neither the perceived risk nor perceived severity of consequences (or the combination of these) predicted helmet use. In a study by Finnoff & al., majority of adults and adolescents indicated that was only a ‘‘slight risk’’ of head injury when cycling without helmet (Finnoff et al., 2001). It seems that cyclists – both adults and children – perceive their personal accident risk low and, thus, risk of getting seriously injured is not linked to helmet use. While cyclists recognize the protective value of the helmet, they simply do not perceive cycling as a high risk activity (Finnoff et al., 2001). These results indicate that bicycle helmet campaigns should not rely on cyclists’ ability to assess the cycling related risks. Another problem in ‘‘scare campaigns’’ for promoting helmet use is that they (if successful) might actually reduce cycling instead of increasing helmet use. The most important barrier for helmet use was ‘‘I’m just going to a short trip’’ (and thus do not need a helmet) both among children and adults. Among children, the second most common barrier was that the helmet is uncomfortable. For adults, forgetting to us the helmet was the second most common reason for not using one. These barriers are actually related to each other: since the helmet is uncomfortable, it is easy to skip using it especially in short trips. Helmet use is uncomfortable especially for children, who use bicycle mostly for recreational purposes and might combine playing to cycling. The bicycle helmet of being ‘‘uncomfortable’’, ‘‘too warm or cold’’ or ‘‘no fitting to hair style’’ have been frequently reported as barriers in earlier studies (Finnoff et al., 2001; Forjuoh et al., 2003; Loubeau, 2000; Pierce et al., 2014; Rezendes, 2006; Stevenson & Lennie, 1992). Interestingly, these barriers of helmet use all refer to bad design of helmets and, thus, cannot be removed simply by attitude campaigns. This is at the same time encouraging and discouraging finding. On one hand it means that the main barriers can be lifted by improving helmet design while on the other hand improving helmets can be difficult and costly.
Please cite this article in press as: Lajunen, T. Barriers and facilitators of bicycle helmet use among children and their parents. Transportation Research Part F (2015), http://dx.doi.org/10.1016/j.trf.2015.03.005
T. Lajunen / Transportation Research Part F xxx (2015) xxx–xxx
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Most of the studies about attitudes to helmet use have concentrated on barriers instead of facilitators or benefits. In the present study, the most important facilitator of helmet use among both children and adults use was the habit of using a helmet. The other important factor in both samples was ‘‘feeling safer with a helmet’’. Among children, having friends who use a helmet was also an important correlate of helmet use. These three issues, however, offer very little for traffic safety work: the main challenge is to start the habit at the first place. It can be assumed that developing the habit of using a helmet or having friends using a helmet is actually just another verbalization of the same problem of motivating cyclists to use a helmet. Regression analysis showed that the model explained an impressive amount of variance in helmet use among children (73%) and that the barriers were more important predictors of helmet use than facilitators. Among adults, only barriers but not facilitators predicted the helmet use. Among children and adults, barriers and facilitators (for children) or only barriers (for adults) were significant and important (13% of variance explained among children and 17% among adults) predictors of helmet use. This finding means that lowering the barriers would result in significant increase in helmet use. The role of barriers compared to benefits (or ‘‘facilitators’’ in the present study) has been demonstrated in theoretical studies applying the Health Belief Model to helmet use (Lajunen & Räsänen, 2004; Ross, Ross, Rahman, & Cataldo, 2010). The present study together with the earlier studies how that lowering the barriers is the best option for bicycle helmet use campaigns. This study has some shortcomings which should be taken into account. First, the study was conducted in Norway – one of the safest countries in the world – what might limit the applicability of the results to less safe regions. For example, Secginki et al. studied helmet use in a upper middle income country with high traffic fatality rate and very low helmet use rate and reported not owning a helmet as a significant barrier (Secginli et al., 2013). Norway is the wealthiest country among OECD countries (with gross national income of 67440 USD per capita in 2012) and the second safest country in OECD in terms of traffic safety with 33 road fatalities per million inhabitants or 51 fatalities per million vehicles (OECD, 2014). Findings based on Norwegian school children might not generalize well to countries with lower income and safety level. For example, the bicycle helmet ownership and the related costs do not seem to be a problem in Norway but can be a significant factor in low income countries. Second, the sample size was small and represents just one region in Norway. It is possible that different factors are related to helmet use in different regions. Third, this study was based on self-reports. Although the participants were assured about anonymity and confidentiality (no names or student numbers were recorded), there is still a slight possibility that the participants embellished their answers. In school settings, there is a possibility that parents want to show higher concern for safety than they actually have. Since the study was based on anonymous answering, we were not able to investigate if the non-responding parents were different from those who returned the filled questionnaire. It is possible that parents who participated in the study had higher concern for traffic safety or were more involved in their children’s school and free time activities than those who did respond. In the present study, factors predicting helmet use were studies among adults and children and comparisons showed some similarities and differences in predictors of helmet use. Age and sex were controlled in regression analysis. In future analyses of children’s helmet use, it would be important to investigate how parents’ helmet use and related attitudes predict their children’s helmet use and attitudes and how age and sex of the child might moderate these relationships. It can be assumed, for example, that young children are more likely to follow their parents’ example than teenagers. In conclusion, it seems that barriers for helmet use – especially among adults – are more related to decision to use a helmet than the facilitators. Especially such helmet related features as the helmets of being uncomfortable, helmets not fitting to hairstyle or helmets being too cold or hot should be addressed by improved helmet design. Social psychological factors like peer pressure can be approached best with school based interventions. In general, targeting the barriers might produce better results in helmet wearing rate than interventions trying to emphasise the benefits of helmet use. 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