Effect Of Emotions And Mood On Risky Driving: A Research Study

1.

1. The title of the article is “Do Young Drivers Become Safer After Being Involved in a Collision?”
2. The authors of the article are Fearghal O’Brien, Joe Bible, Danping Liu, and Bruce G. Simons-Morton.
3. Journal- Psychological Science; year of publication- 2017; volume- 28; pages- 407-413.

2.

1. The aim of the article is to investigate the trend of being involved in car collisions is due to drivers facing collision sin their early lives, thereby reducing the rates of risky driving after such events.
2. Risky driving has been associated with several methodological problems that made the researchers in the past depend upon only subjective data that encompassed risk behaviours that are self-reported or police based reports. Furthermore, not much success has been achieved in determining and establishing the validity of self-reported behaviours and reports from the police, owing to the fact that the latter depends on inferences as the reason for car collisions. One major approach to overcome the issue is the use of technological advances that directly measure behaviour of the drivers during collision events or regular driving. Furthermore, this approach also facilitates understanding the role of secondary-task engagement, during collisions (O’Brien et al., 2013).
3. The main prediction made by the researchers is that some drivers might be in possession of risky styles of driving when compared to their peers, at the beginning of their driving profession, thereby being more vulnerable to collision events. Besides, it was also assumed that such collisions make the drivers adopt less risky attitudes in near future.

3.

1. There were a total of 254 participants aged 16-17 years were recruited for the study across 6 different states via e-mails, mass mailings, advertisements and media. 137 were female (54%), with an average age of 17.1 years (SD=0.6). Different age groups had equal number of participants. Of all the participants, 41 were involved in severe collisions and/or police reports. All the participants were present in the research for 16.2 months on an average and there was no difference between the subgroups based on the average age or male proportion (O’Brien et al., 2013).
2. A data-acquisition system (DAS) was installed by the researchers on the dashboards that contained camera footage and accelerometer. The cameras were placed at an angle near the driver’s face, pedals, windshield, and over the shoulder. Images produced by custom software by combining the footages from all four cameras were monitored by trained coders. Each collision episode was coded for different characteristics namely occurrence of event near collision (422), minor collision (98), police reported collision (26), low risk tire striking off curb (86), and severe collision (16). The researchers also calculated previous driving experience by subtracting age of participant during full-time licensure from that at the start of the trial (O’Brien et al., 2013).
3. Age at licensure for the collision-involved and non-collision-involved participants failed to create an impact on the results that were reported. The recruitment of non-collision-involved participants acted as a benchmark that helped in understanding the driving behaviour of the particular age group. Furthermore, g-force event rates failed to show any significant changes in this group during the first, second and third months. The participants in this group also did not show any reduction in their mileage after month 0.

4.

1. Poisson regression with random effects helped in tracking changes in the major outcome variable, the monthly number of g-force events, for both the centred months and the intercept. This helped to describe the correlations that existed among the driving behaviour of particular participant at different point of time. Sandwich variance estimator was used with the aim of dealing with the overdispersion in Poisson distribution.
2. Participants involved in collision showed lower rates of g-force events following a car collision and the difference was found to persist over a period of 2 months, when compared to those in the non-collision group. Furthermore, significant recovery were observed in the rates of g-force event in month 3. Gradual reduction was also observed in the rates of the g-force events. However, the non-collision participants showed an increase in the rates in the preceding months. Rate of the events among collision-involved participants also increased in month 3 to levels that were less than those obtained before any collision. Additionally, the measures also elaborated on the fact that the participants involved in collision returned to previous driving behaviour (O’Brien et al., 2013).

5.

1. The researchers suggested that future study can be conducted on grounds that compare the outcome for novice drivers with those who are much older and experienced in driving. They also emphasised on the need of conducting a longitudinal examination on the impact of near misses or collision with less severity. Further suggestions were related to gaining a better understanding of the impact that personal experiences might have on such behaviour.
2. The researchers focused on the fact that adolescent age exposes an individual to a range of behaviours that impose great risks to the overall health of the person. They elaborated on the importance of educational programs in helping the young people gain information on the different health risks that are associated with specific behaviours (O’Brien et al., 2013). The educational program would focus on training young people on steps that can prevent such risky behaviour. It is essential that the young people receive this education as a part of their curriculum. The education would focus on practical training sessions that are based on realistic road environment namely, rules of driving, speed, crossing at intersections and parking (Sami et al., 2013). Furthermore, taking into account the cultural, educational, financial and transport circumstances would also ensure success of the programs.

6. I would rate the abstract as 4.5. This rating can be attributed to the fact that the abstract attempted to provide an easy explanation for the research objective to a layman. Use of technical terms such as, g-force events were supported with their meanings, in addition to the method of the research being explained in a compact manner. Information was also accurately provided on the number of participants and the significant variations that were observed among them during months 1, 2 and 3. Moreover, establishing change in risky behaviour as a temporary effect established the findings of the research.

7. References

Hu, T. Y., Xie, X., & Li, J. (2013). Negative or positive? The effect of emotion and mood on risky driving. Transportation research part F: traffic psychology and behaviour, 16, 29-40.

O’Brien, F., Bible, J., Liu, D., & Simons-Morton, B. G. (2017). Do Young Drivers Become Safer After Being Involved in a Collision?. Psychological science, 28(4), 407-413.

Zimbardo, P. G., Johnson, R., & McCann, V. (2012). Psychology: Core Concepts with DSM-5 Update. Boston, MA: Pearson Education, Inc.

References

O’Brien, F., Bible, J., Liu, D., & Simons-Morton, B. G. (2017). Do Young Drivers Become Safer After Being Involved in a Collision?. Psychological science, 28(4), 407-413.

Sami, A., Moafian, G., Najafi, A., Aghabeigi, M. R., Yamini, N., Heydari, S. T., & Lankarani, K. B. (2013). Educational level and age as contributing factors to road traffic accidents. Chin J Traumatol, 16(5), 281-5.