Scottish Government

Annex B - Detailed Data Analyses

Analysis of interview data

Characteristics of interviewees

Of the 124 interviewees, 117 had a current motorcycle licence and 116 owned a motorcycle. Their age varied from 20 years to 69 years, with an overall average age of 42 years (for those who currently own a bike the average age was 43 years and for those that did not it was 32 years). Only 9 interviewees were female (7%) and these were mainly pillion riders; only one female owned a motorcycle.

The average experience of those that were current riders was about 19 years of riding and they ride about 6,500 miles per year on a motorcycle and drive about 8,200 miles in car. About 43% used their bikes for commuting and a similar percentage used their bikes for rural road rides often on their own. About 35% used their bikes at the weekend with a club or organisation, about 67% used them at weekends with their mates on mainly rural roads overall nearly 80% used their bike for fun and enjoyment. About half of the respondents said they used their bike for fun and a car for transport.

During the summer 30% of riders said they used their bike on a daily basis, and over 60% on a weekly basis regardless of the conditions. These figures dropped to 13% and 35% respectively during the winter for daily and weekly use in all conditions. About 16% said that they used their bike in the winter when it was daylight and dry conditions, as compare to the 6% in the summer who only used their bike when it was daylight and dry.

Of the eight interviewees that did not currently ride a motorcycle, 6 stated that it was not because it was unsafe. Two stated that they could not afford it but that it was definitely not because of being inconvenient, albeit one thought it gave a bit of the wrong image. Only one stated that they would need to carry passengers. All of these interviewees were female.

Nearly a quarter of the interviewees who were current riders had taken a break of at least a year from riding. None of them were riding bikes less than 500cc, and only one had a 500cc bike. Over a quarter had 600cc bikes which were mainly sport bikes (a very popular size). Nearly 15% had 1000cc bikes, and over 35% had bikes of 1000cc or greater. The average size was 990cc, and the single female rider who was interviewed rode a 600cc sports touring motorcycle. Most of the bikes (42%) were described as sports-tourers and 34% as sports bikes, there were 16% tourer/roadsters and 4% each of custom and off-road/trailie type bikes.

Interviewees were asked about their offences, and 7% had received fixed penalty notices for motorbike related offences and 5% for car related offences. Of the 116 current riders there were 6% who had been flashed by a speed camera while riding a motorcycle and 5% while driving a car. There were 5 riders who had endorsement points incurred while riding and 4 that had points obtained while driving.

Of those who responded to the question about training taken, 50% said they had not taken any courses. There were 30% of respondents who had taken and passed their CBT and Direct Access course, about 10% had taken and passed their IAM qualification, one had taken and passed the BMF Blue Riband award, 2 a GNVQ qualification and about 23% had taken a Bikesafe course.

Nearly a third of interviewees who currently ride were members of a motorcycling club or organisation. These varied from MAG, BMF and IAM to BMW, Ducati and Honda Goldwing owner clubs as well as the Moray Coast motorcycle club and similar.

Nearly 30% used a tinted visor, 4 respondents had a small number-plate, 20% had an aftermarket exhaust system, 4% had up-rated their suspension and nearly a third said they had 'rear-set' footrests. They all wore protective clothing for upper body and legs of which 78% had armour in the jacket and 64% had armour in the trousers.

Interviewee accident and risk considerations

Interviewers had a table ³ from which they could provide an estimate of the riders' accident risk, given their age, experience and miles ridden per year. These estimates varied from 3 to 33 per 100 riders, with an average value of 7 and a median and mode of 6.

As was reported in the main text, interviewees were asked to consider riders of the same age and sex who rode the same number of miles per year, and state how many (out of 100) would have an accident or minor spill in the next 12 months. The distribution of respondents' own risk assessments for riders like themselves in terms of age, sex, experience and annual mileage is shown in Figure 3.9. The distribution of the statistical risk predictions for the same riders using the 'look-up' table supplied to interviewers is shown in Figure 3.10.

Figure B1 - Scatter plot of rider and model risk estimates.

The difference in the distributions of risk estimates seen in Figures 3.9 and 3.10 implies that riders had a very strong tendency to judge the risk of being in an accident higher than that derived from the model, i.e. they tended to over-estimate the risk faced by riders like themselves - in terms of age, sex and annual mileage.

The relationship between rider's assessment of risk and the statistical assessment of risk is shown in Figure B1. The correlation between the two risk estimates is about 0.3, which is statistically significant, albeit not strong. A large scatter of riders' estimates of risk at any given level of 'model-predicted' risk is apparent in Figure B1 and raises the question of whether riders who estimate that (say) 75 per cent of their peers will have an accident in a 12 month period, can be regarded as giving a serious estimate of risk. These findings may indicate that some respondents decided to over-estimate the risk, or that people find it extremely difficult to make such estimates.

The interviewees were asked if they were willing to believe the estimated accident risk taken from the tables. Their responses to this and associated questions are shown in Table B1.

Table B1 - Percentage level of agreement to estimated accident risk and related questions (interview survey)

Respondents were grouped by their age, as shown in Table B2. The average values on a number of questions relating to risk were computed and compared by age group. The questions in Table B1 were scored from 1 (strongly agree) to 5 (strongly disagree), as were the responses to a question on the likelihood of being involved in an accident within the next 12-months.

Table B2 Age group and frequency of interviewees

The questions where there was a statistically significant difference between the age group averages are shown in Table B3.

Table B3 Group averages for questions where there is statistically significant difference by age (interview sample)

Respondents were grouped by their experience as riders, as shown in Table B4. The average values on a number of questions were computed and compared by age group. A similar analysis was conducted by experience group as it was for age group.

Table B4 Experience group and frequency of interviewees

The questions where there was a statistically significant difference between the experience group averages are shown in Table B5.

Table B5 Group averages for questions where there is statistically significant difference (interview sample)

Interviewee responses to different road scenes

Using stimulus materials and a procedure developed by Broughton (2005; Broughton & Stradling, 2005) interviewees were shown a series of 5 pictures depicting different road scenes (see Annex E). They were asked to imagine that they are riding the road in their normal manner and to rate the setting on four characteristics on 5-point scales from 1 very low to 5 very high. The characteristics rated were:

• How enjoyable it would be
• The speed you would ride
• How much concentration you would need
• How risky it would be to ride the road.

Table B6 gives the mean ratings on each scale for each picture. Picture 5 was rated the most and Picture 4 the least enjoyable scenario. Pictures 5 and 3 received the highest 'speed you would ride' ratings and Picture 4 the lowest. There was most variation between scenes in ratings of enjoyment and speed and least variation between scenes in ratings of concentration as reflected in the values for the standardised Cronbach's alpha for each scale. Thus across these five scenes the amount of concentration required varied least while the amount of enjoyment 'available' in each setting and the appropriate speed for the setting varied most. Rated risk varied, on average, from intermediate (Picture3: 3.33) to high (Picture4: 4.23): bikers know they are vulnerable road users.

Table B6 - Mean scale ratings for each picture

Table B7 shows the correlations between scores on the four scales for each of the five pictures and between enjoyment, speed, concentration and riskiness scale scores computed by averaging ratings across the five settings.

Table B7- Correlations between scale ratings for each picture and overall

* p < .05; *** p < .001

For each picture, and overall, there were highly significant associations between ratings of enjoyment and speed, and between ratings of concentration and risk. The only association between ratings of speed and risk was a weak one for Picture5, and the only association between speed and concentration was a weak one for Picture4. Fuller (2005) in his task-capability interface model of driver behaviour suggests that car drivers manipulate running speed to vary perceived task difficulty. A plausible hypothesis would be that, across the range of road settings represented in the 5 pictures here, bikers vary speed to manipulate enjoyment and vary concentration in the face of varying perceived risk, but that rated enjoyment and rated risk are statistically independent, i.e. high enjoyment has little or nothing to do directly with the perceived risk of the setting.

The relationship between rated enjoyment and rated risk was examined further. Neural Network software was used to train for recognition of 6 possible response patterns: risk remains constant as enjoyment varies; enjoyment remains constant as risk varies; enjoyment falls and then rises as risk increases (U pattern); enjoyment rises and then falls with increasing risk (inverted U pattern); enjoyment decreases as risk increases; enjoyment increases as risk increases. Data from each respondent were sorted into ascending order of rated risk across the 5 pictures and then allocated by the trained software to one of the 6 patterns. No cases were found of the first three patterns. 59% were allocated to the inverted U group, labelled Risk Acceptors; 33% to the Risk Averse group whose enjoyment ratings tended to fall as rated risk increased; and 9% to the Risk Seeker group whose enjoyment ratings rose as their risk ratings rose, (ref: Broughton & Stradling 2005).

The three types did not differ significantly on the demographic variables ( e.g., age, years experience, type of bike ridden, etc.) nor on mean scores of enjoyment, speed, concentration or riskiness. Asked in an open-ended question 'What types of risk do you take as a rider?' 70% of the Averse group, 64% of the Acceptor group and 33% of the Seeker group wrote in 'None' or an equivalent response.

There were statistically significant differences between the 3 groups on 4 of 20 comparisons of ratings across the 5 pictures. The Risk Averse scored lower on speed ratings for Picture 5 (p=.017); and the Risk Seekers scored lower on concentration for Picture 4 (p=.002) and higher on riskiness for Picture 2 (p=.018) and Picture 5 (p=.006), but otherwise mean ratings of the amount of enjoyment, speed, concentration and risk in each setting did not differ between the three groups.

There were however somewhat different patterns in the correlations for the three groups between scores on the 4 scales, as shown in Table B8. The Risk Averse group failed to show an association between concentration and risk, and thus run counter to the hypothesis noted above that bikers vary concentration with perceived risk, but did show a significant association between concentration and speed.

It should be noted that the three riders groups identified in this section (as derived in previous research by Broughton & Stradling 2005), bear some similarity with two of the three found using the set of variables which asked about understanding and acceptance of risk, see section 3.47. Specifically the 'risk accepters' are very much like the 'optimistic accepters' and the 'risk averse' like the 'realistic accepters'.

Table B8- Correlations between scale ratings for each biker type

Thus the three rider types identified by the responses to the 'picture' questions appear not to differ in the amount of enjoyment they obtain from riding and differ only in particular road settings on speed, concentration and perceived riskiness, and while all three types show a strong association between enjoyment and speed only two show a relationship between concentration and risk.

Interviewees were asked how safe or risky they considered motorcycling is in general and for themselves, the responses are shown in Table B9. It is interesting to see how much safer respondents regard motorcycling to be for them as compared to riders in general. This again confirms that riders perceptions of themselves are usually as safer, better rider than of riders in general.

Table B9 - How risky is motorcycling perceived (n=123)

Analysis of survey data

Introduction

The questionnaire contains data that has been used to derive measures of sensation seeking, attitudes, riding styles, riding behaviours and risk assessment. The data has been used to examine the interactions of various self-reported factors and how they relate to risk and accident liability.

The outcome from such analyses provides a further understanding on what factors are potentially important influences on risk acceptance and how attitudes to risk may be influencing risk acceptance.

Characteristics of self-completion questionnaire respondents

Of the 364 respondents returning the self-completion questionnaire, 344 (95%) had a full motorcycle licence and 347 (96%) owned a motorcycle. Their age varied from 18 years to 68 years, with an overall average age of 43 years. About 89% of respondents were male of whom 98% currently owned a motorcycle; of the 11% of females who responded ( i.e. 40), 75% reported owning a motorcycle.

The average experience of those that were current riders was about 15 years of riding and they ride about 5,300 miles per year on a motorcycle and drive about 11,250 miles in car.

Of the 12 respondents that did not currently ride a motorcycle, 9 stated that it was not because it was unsafe. Seven stated that they could not afford it and only two said that it was because of being inconvenient. None thought that it gave the wrong image. Five stated that they would need to carry passengers. About three quarters of respondents who did not own a motorcycle were female.

Nearly 44% of respondents had taken a break of at least a year from riding. The engine size varied from 50cc to 2,300cc, just over 20% had 600cc bikes which were mainly sport bikes. Nearly 11% had 1000cc bikes, and nearly 30% had bikes of 1000cc or greater. The average engine size was 860cc. Most of the bikes (33%) were described as sports-tourers and 26% as sports bikes, there were 19% tourer/roadsters, 9% custom bikes, 6% off-road/trailie bikes, 6% classic bikes and 2 moped/scooters (which were 50cc).

Respondents were asked about their offences, and 5% had received fixed penalty notices for motorbike related offences and nearly 10% for car related offences. There were 15 riders who had endorsement points incurred while riding and 33 that had points obtained while driving.

Of those who responded to the question about training taken, 47% said they had not taken any courses. There were 45% of respondents who had taken and passed their CBT course and about 30% their Direct Access course. About 12% had taken and about 9% had passed their IAM qualification, 12 had passed their RoSPA test, four had passed the BMF Blue Riband award, one a GNVQ qualification and about 15% had taken a Bikesafe course.

Nearly a half of the respondents were members of a motorcycling club or organisation. These included riders from MAG, BMF and IAM to BMW, Ducati, Bandit, Harley Davidson, Triumph and Honda Goldwing owner clubs as well as the Moray Coast, Tweed Valley, Clyde Valley motorcycle clubs and similar.

Accident involvement

There were 39 respondents who had been accident involved within the past 12 months (just under 11%). Of these accident involved nearly 53% stated that they were not to blame at all, with just 5 accepting that they were fully to blame. There were nearly 64% who had the impression of just avoiding an accident within the past 12 months, i.e. had a near miss. Of these about half had the impression of have 1 or 2 near misses in the past 12 months. There were a few riders who reported as having a near miss on a weekly basis, i.e. about 50 in the past 12-months.

Risk estimates

Riders were asked to imagine 100 riders and to estimate how many would be involved in an accident of some kind within the next 12-months. Three types of accident were suggested and an estimate was required for each type:

• minor accident or spill with no injury,
• accident involving a minor injury and
• accident involving a serious of fatal injury

The 100 riders to be considered were either typical riders, riders of a similar age and experience covering similar miles or riders exactly like you. Estimates for the three severity of accident were required for each combination, thus generating 9 estimates in total. A summary across all respondents is given in Table B10.

Table B10 - Summary of estimates of number of accidents per 100 riders pa

The range of estimates extends from 0 to 100 and an examination of response patterns suggests that respondents are using the scales in differing ways. For example one respondent gave 100 to all non-injuries, 50 for minor injury and 2 for all serious or fatal injury. However, there was another respondent who gave the risk of a no injury accident as low (20), the minor accident risk as much higher (40) and of a serious or fatal accident as even higher (80). The second respondent presumably considers that having an accident on a motorcycle is likely to involve injury, whereas the first thinks that all riders have accidents but they are not usually fatal or serious. Alternatively, these responses may simply indicate that some respondents misunderstood the questions.

The average values do show a logically consistent and sensible pattern. The numbers decrease with severity of the accident. The numbers also decrease as the estimate becomes personalised, thus demonstrating that riders do perceive themselves to be safer than riders in general and even riders who are very similar in terms of age, sex, experience and miles ridden per year.

Defining risk groups

The self-completion questionnaire also asked questions about different aspects of riders' perception of risk when riding and their acceptance of risk. They were asked how much they agreed or disagreed (on a 5-point scale) with the statement, with a code of 1 meaning they strongly agreed and 5 that they strongly disagreed. The risk they were asked to consider in the self-completion questionnaire was that motorcyclists were 25-times more likely to be killed in an accident as compared to car drivers.

The eight questions were as follow:

(i) I am willing to believe that riding a motorcycle is 25 times more risky than driving a car

(j) I was aware that riding was more risky than driving a car, but did not realise it was 25 times more risky

(k) I was aware that riding was 25 times more risky than driving a car, and I am willing to accept this risk

(l) I am a good rider so the high risk does not apply to me

(m) I worry about the high risk of riding a motorcycle

(n) I wear protective gear and so reduce the risk of injury

(o) You have to accept some risk, if life is not to be too boring

(p) If motorcycling really is 25 times more risky than driving a car, I'll consider giving up riding motorbikes

The distribution of responses to these questions is shown in Table B11.

Table B11 - Percentage level of agreement to estimated accident risk and related questions (self-completion survey)

Respondents were grouped by their age and by their experience as riders, as shown in Tables B2 and B4 respectively. A similar analysis to that carried out for the interview sample comparing averages across a number of questions about risk was conducted.

Table B12 Age group and frequency of self-completion questionnaire respondents

Table B13 Experience group and frequency of self-completion questionnaire respondents

Only the experience group analyses produced any statistically significant differences between group averages. These questions for the experience group average values are shown in Table B14.

Table B14 Group averages for questions where there is statistically significant difference between experience groups (self completion questionnaire sample)

The average values for each of the motorcycle rider behaviour questionnaire ( MRBQ) behaviour measures and motorcycle rider motivation questionnaire ( MRMQ) factors are shown in Table B15 for each response to a question about risk acceptance.

Table B15 - Average values of behaviour and attitudes measures

The k-cluster ⁴ analysis technique was used to define 3 groups on the basis of responses to these eight statements. The technique generates groups which differ from each other as much as possible from the responses given. The three groups had mean values on each of the 8 statements as shown in Table B16.

Table B16 - Mean values for each group

Comparison of the three rider groups

A number of behaviour, attitude, sensation seeking and other measures were computed and have been identified in an earlier section. These have been compared between the rider risk groups and may help to understand some of the differences between the riders in each group, Table B17. For example those in group 3 covered less mileage and had less experience than those in group 1. However it is group 2 riders who are seeking more sensations overall as well as the novelty and intensity of the sensation.

Table B17 - Mean values for each group on a number of rider measures

* indicates that there was statistically significant difference between some of the group means on this variable

Relative risk was assessed across a number of activities on a 7-point scale (1=no risk to 7=high risk). The average scale values were then ranked with rider group. The lowest score has a rank of 1 indicating the lowest relative risk. Table B18 shows that driving a car is considered the least risky activity and hang-gliding the most risky. Overall motorcycling ranks 4th and is seen as more risky than driving a car, cycling or surfing but less risky than rock climbing, skiing and hang-gliding. However, those riders in group 1 only rank motorcycling as riskier than driving a car and less risky than cycling, surfing, rock climbing, skiing and hang-gliding.

Table B18 - Ranking on risk of activity, for each of the 3 rider groups

The seriousness of having an accident while engaged in a number of activities was assessed by riders on a 7-point scale (1=not serious to 7=extremely serious) and then ranked according to the average value for the group. Table B19 shows that driving a car is likely to be the least serious and hang-gliding the most serious. Overall motorcycling ranks 5th and is seen as having a potentially more serious outcome than an accident when driving a car, cycling, surfing or skiing but less serious an outcome than rock climbing and hang-gliding. Motorcycling ranks higher for the seriousness of the outcome than the risk in the accident occurring.

Table B19 - Ranking serious of an accident while participating in activity, for each of the 3 rider groups

The controllability of avoiding death or injury while engaged in a number of activities was assessed by riders on a 7-point scale (1=controllable to 7=not controllable) and then ranked according to the average value for the group. Table B20 shows that driving a car is seen as the most controllable and hang-gliding the least controllable. Overall and in group 2 and 3 motorcycling ranks 3rd and is seen as less controllable than driving a car or cycling, but more controllable than skiing, rock climbing, surfing and hang-gliding. However those riders in group 1 see motorcycling as more controllable than cycling.

Table B20 - Ranking controllability of avoidance of injury or death while engaging in each activity, for each of the 3 rider groups

Riders were asked how safe or risky they thought that motorcycling was in general and specifically for them. They rated the perceived risk on a 7-point scale going from 1=very safe to 7=very risky. Table B21 shows the distribution of responses. It indicates that riders perceive they personally are at less risk than riders in general. They consider that it is risky for 31% of riders in general, but only 13% consider that they personally are at risk. This is consistent with the findings from the interview survey.

Table B21 - How risky is motorcycling perceived (n=355)

The average rating values for each of the three rider groups are given in Table B22, and there is a statistically significant difference between the average values.

The group 1 riders perceive the risk in motorcycling less than the other two groups, in general and for themselves. Group 3 riders consider the risk to be highest, and specifically for themselves, i.e. they are the more risk aware group as is reflected by the characteristics described elsewhere.

Table B22 - Mean values for each rider group on perception of risk

Riders were ask to compare the risk when riding a motorcycle with the risk when driving a car and to state if they felt it was higher, lower or about the same. The row percentages in Table B23 shows that riders in group 1 perceive riding relatively less risky than riders in the other two groups, and those in group 3 relatively more risky. Overall, riders perceive riding as a more risky mode of transport than driving.

Table B23 - Perception of relative risk of riding compared to driving

*A Chi-squared test indicated a relationship between rows and columns (24=32.5 p<0.001)

Those respondents who had indicated they thought riding was less risky than driving were asked to say by how many times. The responses varied from 1 to 100 with an average of 12, suggesting that they thought riding is 12 times less risky than driving. Similarly, riders who had indicated they thought riding was more risky than driving were asked to say by how many times. The responses also varied from 1 to 100 with an average of 9, suggesting that they thought riding is 9 times more risky than driving. There were no statistically significant differences between the 3 rider groups on either measure, probably due to the large variation in the relative risk estimates.