Reward versus punishment: Reinforcement sensitivity theory, young novice drivers' perceived risk, and risky driving

TLDR: The authors applied reinforcement sensitivity theory (RST, specifically reward sensitivity and punishment sensitivity) to predict young novice drivers' perceived risk and self-reported risky driving engagement, while accounting for potential influences of age, sex, and driving experience.

Abstract: One reason that young novice drivers remain statistically over-represented in road deaths is their rate of engagement in risky driving. Prominent contributing factors include driver’s age, sex, personality, risk perception, and their driving experience. This study applied reinforcement sensitivity theory (RST, specifically reward sensitivity and punishment sensitivity) to predict young novice drivers’ perceived risk and self-reported risky driving engagement, while accounting for potential influences of age, sex, and driving experience. Drivers ( N  = 643, 490 females, 17–25 years, M  = 20.02, SD  = 2.32) who held an Australian driver’s license (P1, P2, or Open) anonymously completed an online survey containing the Behaviour of Young Novice Drivers Scale, the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, and a measure of perceived risk of driving-related behaviours. A path analytic model derived from RST showed that perceived risk had the strongest negative association with reported risky driving engagement, followed by reward sensitivity (positive association). Respondent’s age and reward sensitivity were associated with perceived risk. Age, reward sensitivity, and perceived risk were associated with reported engagement in risky driving behaviours. Driver sex only had direct paths with RST variables, and through reward sensitivity, indirect paths to perceived risk, and reported risky driving. Neither punishment sensitivity nor driving experience contributed significantly to the model. Implications and applications of the model, and the unique set of variables examined, are discussed in relation to road safety interventions and driver training.

Figures

Table 1 Means, standard deviations, reliability coefficients, and zero-order correlations between criterion and predictor variables (N = 643).

Figure 1. Path diagram showing effects of RST, driver sex, age, and length of licensure on perceived risk and reported engagement in risky driving (N = 643).

Full text

Reward versus punishment: Reinforcement sensitivity
theory, young novice drivers' perceived risk, and risky
driving
Author
Harbeck, Emma L, Glendon, A Ian, Hine, Trevor J
Published
2017
Journal Title
Transportation Research Part F: Traffic Psychology and Behaviour
Version
Accepted Manuscript (AM)
DOI
https://doi.org/10.1016/j.trf.2017.04.001
Copyright Statement
© 2017 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International (http://creativecommons.org/licenses/by-nc-nd/4.0/) which
permits unrestricted, non-commercial use, distribution and reproduction in any medium,
providing that the work is properly cited.
Downloaded from
http://hdl.handle.net/10072/340868
Griffith Research Online
https://research-repository.griffith.edu.au

1
Reward versus punishment: Reinforcement sensitivity theory, young novice drivers’
perceived risk, and risky driving
Emma L. Harbeck
a
, A. Ian Glendon
a,b,c*
, Trevor J. Hine
a,b
a
School of Applied Psychology, Griffith University, Parklands Drive, Southport, Queensland
4222 Australia
b
Menzies Health Institute Queensland
c
Centre for Work, Organization and Wellbeing
ELH: e.harbeck@griffth.edu.au, AIG: i.glendon@griffith.edu.au, TJH: t.hine@griffith.edu.au
*Corresponding author. Tel: +61 7 567 88964
Email address: i.glendon@griffith.edu.au (A. I. Glendon)

2
Highlights
• Reward sensitivity and driver age predicted young novice drivers’ perceived risk
• Perceived risk predicted young novice drivers’ reported engagement in risky driving
• Reward sensitivity and driver age predicted young novice drivers’ risky driving

3
ABSTRACT
One reason that young novice drivers remain statistically over-represented in road deaths is
their rate of engagement in risky driving. Prominent contributing factors include driver’s age,
sex, personality, risk perception, and their driving experience. This study applied
reinforcement sensitivity theory (RST, specifically reward sensitivity and punishment
sensitivity) to predict young novice drivers’ perceived risk and self-reported risky driving
engagement, while accounting for potential influences of age, sex, and driving experience.
Drivers (N = 643, 490 females, 17-25 years, M = 20.02, SD = 2.32) who held an Australian
driver’s license (P1, P2, or Open) anonymously completed an online survey containing the
Behaviour of Young Novice Drivers Scale, the Sensitivity to Punishment and Sensitivity to
Reward Questionnaire, and a measure of perceived risk of driving-related behaviours. A path
analytic model derived from RST showed that perceived risk had the strongest negative
association with reported risky driving engagement, followed by reward sensitivity (positive
association). Respondent’s age and reward sensitivity were associated with perceived risk.
Age, reward sensitivity, and perceived risk were associated with reported engagement in
risky driving behaviours. Driver sex only had direct paths with RST variables, and through
reward sensitivity, indirect paths to perceived risk, and reported risky driving. Neither
punishment sensitivity nor driving experience contributed significantly to the model.
Implications and applications of the model, and the unique set of variables examined, are
discussed in relation to road safety interventions and driver training.
Keywords: young drivers, punishment sensitivity, reward sensitivity, perceived risk, risky
driving

4
1. Introduction
1.1. The young novice driver
Despite declining fatalities (BITRE, 2014, 2015), road safety remains a major concern in
Australia and internationally. Although driving on average fewer hours and less kilometres
than more mature drivers do, young novice drivers are over-represented in national road
deaths (BITRE, 2014; Scott-Parker et al., 2013; Scott-Parker et al., 2012a). One reason is
young drivers’ engagement in risky driving, contributing factors to which include: driver’s
age, sex, personality, risk perception, and their driving experience. This study applied
reinforcement sensitivity theory (RST, specifically reward sensitivity and punishment
sensitivity) to explore young novice drivers’ perceived risk and self-reported risky driving
engagement, while accounting for potential influences of age, sex, and driving experience.
Younger drivers’ (< 26 years) risky driving behaviours (e.g., speeding, drink-driving)
contribute to their comparatively higher crash, injury, and death rates (Laapotti et al., 2001;
Machin & Sankey, 2008). Novice drivers in their early to mid-20s report engaging in risky
driving for reasons that include: gaining autonomy, self-enhancement, optimism bias, to
please friends, and to gain more adult-like status (Arnett, 1992; Begg & Langley, 2001;
Harré, Foster, & O’Neill, 2005; Hartos et al., 2000).
The safest period for young drivers is the newly licensed learner stage, when risk exposure
is attenuated by an in-vehicle supervisor (Bates, Watson, & King, 2009). Novice drivers’
crash risk peaks during the first few months’ of unsupervised driving upon obtaining their
Provisional 1 (P1) license (Bates et al., 2009; McCartt, Shabanova, & Leaf, 2003; Preusser &
Tison, 2007), decreasing substantially after the first 1600 km driven (Kinnear et al., 2013;
McCartt et al., 2003). Crash risk continues to fall over the next 18 months (Williams, 2003),

Frequently asked questions

Q1. What are the contributions in "Reward versus punishment: reinforcement sensitivity theory, young novice drivers' perceived risk, and risky driving author" ?

This study applied reinforcement sensitivity theory ( RST, specifically reward sensitivity and punishment sensitivity ) to predict young novice drivers ’ perceived risk and self-reported risky driving engagement, while accounting for potential influences of age, sex, and driving experience. A path analytic model derived from RST showed that perceived risk had the strongest negative association with reported risky driving engagement, followed by reward sensitivity ( positive association ). Implications and applications of the model, and the unique set of variables examined, are discussed in relation to road safety interventions and driver training. 

Q2. What future works have the authors mentioned in the paper "Reward versus punishment: reinforcement sensitivity theory, young novice drivers' perceived risk, and risky driving author" ?

Future research using a more general driving population and examining response rates, could usefully validate current findings, and determine whether differences exist between university student and non-university drivers. 

Q3. What are the three processes that affect young drivers?

Cognitive processes include: 1) risk perception, 2) recognising the risk of the behaviours, and 3) willingness to engage in risky driving. 

Q4. What are the reasons for the risky driving behaviours of young drivers?

Novice drivers in their early to mid-20s report engaging in risky driving for reasons that include: gaining autonomy, self-enhancement, optimism bias, to please friends, and to gain more adult-like status (Arnett, 1992; Begg & Langley, 2001; Harré, Foster, & O’Neill, 2005; Hartos et al., 2000). 

Q5. Why do some drivers find it difficult to learn inhibition and control impulsive behaviour?

Due to their stronger motivation towards reward seeking, drivers with high reward sensitivity and who prefer immediate rewards, find learning inhibition and controlling impulsive behaviour difficult (Constantinou et al., 2011). 

Q6. What can be done to help identify factors influencing novice drivers’ risk perception and risky driving?

Identifying relevant motivation systems, such as sensitivity to reward and punishment, may inform road safety initiatives seeking to identify factors influencing novice drivers’ risk perceptions and risky driving. 

Q7. What are the limitations of the study?

Study limitations include those usually associated with online survey research, specifically cross-sectional design, self-report data, and common method variance (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). 

Q8. Why are self-report measures often used to assess driver behaviour?

because self-report measures can access constructs that are unavailable through other methods, they are frequently used to assess driver behaviour. 

Q9. What is the safest period for young drivers?

The safest period for young drivers is the newly licensed learner stage, when risk exposureis attenuated by an in-vehicle supervisor (Bates, Watson, & King, 2009). 

Q10. What does the strong negative relationship between perceived risk and reported risky driving mean?

7The strong negative relationship between perceived risk and reported risky driving does notimply that because a behaviour is perceived to be risky, drivers will not engage in it, or that attempting to further increase perceived risk will reduce the incidence of risky driving. 

Q11. How did the respondents gain their driving experience?

It is likely that most respondents gained their driving experience through Queensland’s graduated driver licensing program, incorporated in 2007 and revised in 2011 (DTMR, 2014). 

Q12. What is the main reason why young drivers are not more likely to engage in risky driving?

Results indicated that deterrence due to likelihood of punishment or negative consequences (e.g.,injury, loss of life) may not significantly reduce some young drivers’ engagement in risky driving, though this remains the primary approach used in Australia (Scott-Parker et al., 2013). 

Q13. What measures were used to assess driving behaviour risk?

Items developed from measures previously used to assess driving behaviour risk (Harbeck & Glendon, 2013; Ivers et al., 2009; Machin & Sankey, 2008) were: speeding, drink driving, seatbelt use, fatigue, mobile (cell) phone use, tailgating, red traffic light violation, illegal driving manoeuvres, drug-driving, distracted driving, and having peer passengers. 

Q14. What factors could be used when examining variables that may be changed in the young risky driver?

Such factors could be used when examining variables that may be changed in the young risky driver, instead of variables that cannot be changed (e.g., age, sex), or that are relatively more resistant to change (e.g., personality, cognitive biases). 

Q15. What could have meant that of these drivers’ driving experience was beyond the threshold level?

This could have meant that most of these drivers’ driving experience was beyond the threshold level, thereby nullifying the possibility of detecting an experience effect.