Research Question
How different types of pressure can affect peer risk-taking on a fictional young male driver’s estimated speeding behavior and estimated intention to speed?
Hypotheses
- Passive peer pressure would lead to a greater estimated speeding behavior of the scenario driver (ESBSD) and estimated intention to speed of the scenario driver (ESISD) than active pressure.
- High-risk-taking peers would have a higher estimated ESBSD and ESISD.
- Passive peer pressure with high risk-taking peers would have the highest ESBSD and ESISD than active pressure.
Theoretical Framework
Peer presence had resulted that there was a negative effect on young drivers’ driving behavior such as being out of focus, drunk driving, speeding, and breaking the traffic rules which might cause accidents and injuries. However, some had found that dangerous driving behaviors can be stopped by the passengers too. Young drivers can be disturbed by peer presence while driving in three different ways.
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First, peer presence can lead to an increment of the driver’s cognitive workload by chit-chatting. This can divert the driver’s attention and cause him or her to make mistakes like unintentionally ignoring traffic rules while driving.
It can also lead to traffic violations. This is because the driver wants to prove to the peers that he or she can do risky behaviors too. When a social identity represents the basis of self-conception, people are high to be influenced by their peers since the actions acknowledged by the peer group are outstanding. If the peer risk-taking level as a whole group is high, it will be high as an individual in the group as well, and it is related to car crashes.
Besides, peer passengers can push the drivers to disobey traffic rules by persuading them to do a risky action that has not been done before. However, there were studies showing that drivers still would not change their behaviors in the future even though the behavioral change was achieved. Allen and Brown (2008) found out that peers can change the driver’s behavior with two types of influence, which were proximal influence and distal influence. Proximal influence is about passengers interrupting the driving actively. Distal influence happens outside of the driving environment and includes negotiation of approved driving behaviors and patterns. It also assumes the negotiation while peer risk-taking is based on subtle influence, relying on the highlight of risk-taking norms rather than on the negotiation. Therefore, peer risk-taking increases the chance of drivers’ risk-taking behavior.
Method
Participants
The participants involved in this study were 180 young French drivers ranging from 18 to 25 years old with a mean age of 22.10 years and an equal amount for both genders. They have had their driving licenses for at most seven years with a mean of 2.67 years and a standard deviation of 1.78. They drove almost a maximum of 700,000km ever since with a mean of 30,156km and a standard deviation of 10,000km. 69.4% have driven less than 10,000km in the past year, and 20% among them only had a car crash once in the past 3 years. 17.2% of the 69.4% of 180 participants had lost a maximum of 8 points on their licenses with a mean of 2.48 and a standard deviation of 1.83. This was due to speeding which occupied 25 to 30 cases.
Measurement of variables
Most of the variables were measured by using 5-point Likert scales except for measuring estimated speeding behavior. The scales ranged from one, which was not at all, to five or also known as completely. The single average scores for scales that had multiple items would be calculated as well. Certain variables like peer risk-taking and peer pressure type had manipulated. Peer risk-taking was manipulated by giving details on speeding behavior by the peers while the type of peer pressure was manipulated by approving the driver to speed, no matter if it was voiced out or not. Question examples were ‘In your opinion, at what speed will Mark, the driver in the scenario, choose to drive in this situation?’, which was used to measure estimated speeding behavior, ‘Will Mark, the driver in the scenario, have the intention to exceed the speed limit?’ for estimated speeding intention, ‘In your opinion, did Mark’s passengers try to change his driving behavior?’ for measuring peer pressure, ‘In your opinion, do Mark’s passengers take risks when driving?’ which was for measurement of peer risk-taking, and ‘In your opinion, are Mark and his passengers' close friends?’ for group identification.
Data collection procedure
Six conditions were allocated by the participants that were high risk-taking (HI-R) direct active pressure which was high risk-taking peers supported the driver to speed through talking, HI-R indirect active pressure which was high-risk takers talked about another driver who sped, HI-R passive pressure where high risk-taking peers supported speeding without saying anything, low risk-taking (LO-R) direct active pressure which represented low-risk takers approved speeding through words, LO-R indirect active pressure where low risk taking peers shared a story about other drivers with speeding behavior, and LO-R passive pressure which was about low-risk takers’ silent approval on speeding. 30 participants with equal amounts for both genders were placed in each condition.
Participants were asked to estimate the speed the driver in the scenario was most likely to exceed to measure estimated speeding behavior. To measure estimated speeding intention, they assessed if the driver had the intention to exceed the speed limit and estimated if the driver will continue to drive at 90 km/h. To analyze the manipulations’ effectiveness, they were asked to determine if the peers had tried to give the driver stress and made the driver change the driving speed, and passengers’ risk-taking level, and if the passengers and driver had formed a group for peer pressure measurement. They were also asked to assess whether the peers and the driver were in the same group, had similar interests and personalities, spent time together often, and became good friends for perceived group identification. They judged the level of risk-taking regarding speed limits and traffic rules as well.
Findings and Conclusions
Results have stated that participants had analyzed that the peers had pressured the driver. Participants in the high-risk-taking group considered that their peers took more risks while driving than the low-risk-taking group and that the drivers and passengers were in a group. Participants had also estimated that the driver would have the intention to exceed the speed limit and speed. Researchers also found that ESBSD correlated with estimated ESISD and peer pressure while ESISD correlated with peer pressure and group identification.
The first hypothesis was met as results had shown that pressure type had a common effect on ESBSD. However, there was a difference between different pressure types. Active pressure greatly influenced the drivers rather than the passive pressure. Besides, the estimation of speed intention had no change in behavior, and therefore speeding seems to be a voluntary action.
The second hypothesis was not totally met. Effect on ESISD was found that a higher risk-taking level would have higher ESISD but not ESBSD due to the reason that peer risk-taking was not really taken into account and therefore lesser impact on the behavior. Interactions with high-risk-taking peers seem to have a huge and lasting impact on speeding. Young drivers usually find their own identity in driving after having a license. In the meanwhile, they can be influenced and change their behavior through social learning easily. The more they are revealed to dangerous driving behavior by their peers, the more and quicker they will adapt to it.
Unfortunately, the third hypothesis was not met at all as the study unexpectedly found out that active pressure yielded a higher level of estimated speeding behavior instead of passive pressure. It could be because the driver who the participants estimated was a fictional main character and anonymous to them, so the participants probably did not have a hard time estimating.
The most unexpected and surprising finding was that there was no difference between both genders. It opposed our general knowledge of women are more careful than men when it comes to driving. This could be due to gender expectations of men are more likely to drive dangerously, so female participants could have overestimated the speed and intention to meet this expectation.
Practical Implications
The results of this study are useful for preventing speeding. To reduce the peer presence effect, the transportation department should enforce new traffic rules and regulations such as limiting the number of passengers in a car and reducing the speed limit. Police should have a spot check regularly in different areas too. Penalties such as fines, imprisonment, or revocation should be given if the driver is caught breaking the rules.
Safety talks and campaigns should be organized for all young drivers. During the campaigns, certain topics like peer presence, dangerous driving behaviors, traffic laws, and even consequences of offense should be explained then instill the drivers with good driving skills and teach them the skills of resisting peer presence. Driving learners should also be informed about the different negative influences of peers during their driving lessons.
Future Research
In the future, other risky driving behaviors like drinking, crossing the red light, and not wearing seatbelts should also take into account as well as this study only considers speeding as the only variable that affects driving behavior. Researchers should examine if peer presence has the same impact on those other hazardous driving behaviors as speeding by using a similar approach as this study. Future studies should look into other factors that may cause risky driving behavior such as personality. Researchers can investigate if a driver will engage in dangerous driving actions or not due to the reason that he or she has an aggressive personality.
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