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Adira2022article.pdf
W K 2 Gadjah Mada Journal of Psychology, Volume 8, Number 1, 2022: (page 95-110) E-ISSN 2407-7798
https://jurnal.ugm.ac.id/gamajop DOI: 10.22146/gamajop.72115
D i f f i c u l t i e s i n E m o t i o n R e g u l a t i o n a n d O p t i m i s t i c B i a s i n
Y o u n g D r i v e r s ' R i s k y D r i v i n g B e h a v i o r s
Psyc 2720
Nesya Adira', Machmuroch', Pratista Arya Satwika3 123Department of Psychology, Faculty of Medicine, Universitas Sebelas Maret
'Department of Psychology, Faculty of Education, Universitas Negeri Yogyakarta
Submitted 10 January 2022 Accepted 16 March 2022 Published 23 May 2022
Abstract. Risky driving behavior is the most dominant human error among young novice drivers. This research's objective was to find the correlation between difficulties in emotion regulation and optimistic bias towards risky driving behavior of teenagers. Sample was Senior High School students from grade 10 to 11 S who drove private vehicles on a daily basis (N=160). Instruments used were modified Behavior of Young Novice Drivers' Scale (BYNDS), modified Difficulties in Emotion Regulation Scale (DERS) and optimistic bias scale. Hypotheses were tested using multiple regression analysis. Results showed that there was a positive and significant correlation between difficulties in emotion regulation and optimistic bias towards risky driving behavior (F (2, 157) - 47.846; p < 01). Bigger contribution was found on difficulties in emotion regulation, indicating that teenagers while driving, relied more on their emotion regulation abilities than their awareness of driving risks.
Keywords: emotion regulation; optimistic bias; risky driving behavior; teenagers
The increase of private vehicle use is followed by the rise of traffic accidents rate in Indonesia (usuf et al., 2017; Soehodho, 2007). Based on WHO Global Road Safety report
in 2018, traffic accidents still become one of the biggest risk factors in developing
countries, especially in Africa and Southeast Asia, which reported three times higher death rates due to traffic accidents compared to the global index (WHO, 2018). Indonesia
is one of the biggest contributors for the most deaths due to traffic accidents. Statistically
speaking, the latest traffic accidents fatality rate in Indonesia was 18.01 per 100.000 of
population (WHO, 2018). To note, this number is always on the linear rising trend where
fatality rate was 4.71 in 2004 and rose as high as 13.74 in 2011 per 100.000 of population Jusuf et al., 2017).
Statistical data also showed that economic loss due to traffic accidents in low to
mid GDP countries had reached 3% of GDP (WHO, 2015). Indonesia reported that 2021's
economic loss due to traffic accidents as per February was IDR 295 million (Korlantas, 2021). Thus, we should never turn blind eye to the huge impact of traffic accidents and its
need for more attention, especially in finding the effective preventive solution. Preventive
action needs more planned execution, especially in terms of determining the cause of the
accidents. The most reported and biggest traffic accidents cause is human error (Ulleberg
& Rundmo, 2003). Human error consists of risky driving behaviors such as violation of traffic signs and careless driving.
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
Risky driving behavior is the most dominant human factor in young drivers (Reason et al., 1990). This is in line with the fact that the highest traffic accidents victim is
reported by this age group both in Indonesia and other countries (WHO, 2018). Included
in this group are high school and college students. Private vehicles, especially motorbikes,
are very popular due to their practicality and time efficiency. One of the main reasons to
use private vehicles for students is to lessen parents' burden to drive their children from
and to school.
Globally, young drivers by WHO are grouped into people aged 15 to 29 (WHO,
2015). This age grouping depends on the policy of each country (Scott-Parker, 2017). Indonesia's Traffic Corps (Korlantas) often groups young drivers between 15 to 19 years
old, similar to the age group of high school students' age in Indonesia (CNN, 2021). Therefore, young drivers in this research belong to this age group. This age group, by
experts, is noted for the transition period from a child to an adult, characterized by their
biological, psychological, moral, religious, cognitive and social developments (Sarwono,
2016). During this period, they explore their self-capabilities and are faced by their discovery of selves, how will they grow to be and where will they go in the future. Having their own private vehicle is one of the freedom expressions given by their parents. Driving, in this period, is not only seen as a transportation mode but also as a way to
express their self-capabilities and freedom (Constantinou et al., 2011).
Young drivers have significantly more risk of being involved in traffic accidents
compared to the other age groups (Constantinou et al., 2011; Regev et al., 2018; Scott- Parker & Oviedo-Trespalacios, 2017). Other factors include their lack of experience, but
with the tendency to overestimate their abilities and underestimate the possibilities of accidents (Fisher et al., 2002). Young drivers believe they have less risk of being involved
in accidents compared to adult drivers and their own peers (Constantinou et al., 2011).
Their significant development progress has an impact on risky driving behavior since risk
taking is one of the most common things to do during this period (Scott-Parker, 2012). Not
only that, they are also affected by both personal and social factors (Shope & Bingham,
2008). Not much different with global research, research on traffic accidents in Indonesia
indicates that young drivers in Indonesia tend to get distracted and generally unaware of
the dangers of risky driving (Santosa et al., 2017; Zuraida e al., 2017). Moreover, Joewono and Susilo (2017) found that motorbike drivers in young age group take bigger risks than
older age group drivers. Therefore, trait, social and personal factors all need to be considered in learning
more about risky driving behavior in young drivers (Scott-Parker, 2012). This identification will eventually lead to significant contribution in policy making and to get a
more preventive solution of traffic accidents.
Difficulties in Emotion Regulation and Risky Driving Behaviors
ADIRA et al. Il EMOTON REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
Most studies have found that attitudes towards safety is the variable correlated to
aggressive and careless driving behaviors (Ulleberg & Rundmo, 2003). In result, many
preventive programs were held to give importance in abiding traffic laws and rules, intended to change their attitudes. However, these programs still have not managed to decrease the traffic accidents rates. This failure can be attributed to how most of the
programs intend to change the attitudes without considering the role of emotions and the
drivers' decision-making capabilities (Ulleberg & Rundmo, 2003).
Attitudes and behavior relate strongly to emotions. Chan and Singhal (2013) found
that emotion directs drivers' attention from driving as an activity to an emotional stimulus which resulted in loss of attention and important information processing while driving. Young drivers are more vulnerable to emotional driving (Scott-Parker, 2017). A
study has found that in the US, most young drivers have driven while having both strong
negative or positive emotions such as anger or excitement. For example, angry driving is
associated with the high tendency to speeding (Gulliver & Begg 2007). Furthermore, excitement can lead to overly heightened sensation or expression seeking. These things
can affect driving behavior since sensation can turn young drivers to alter their behavior
to be riskier so that they can get more intense experience while driving (Scott-Parker,
2012). These findings indicate that emotion can play a big role in driving safety, especially
if it can be regulated well. With good emotion regulation, individuals can control themselves to avoid negative behaviors (Mawardah & Adiyanti, 2014).
Emotion regulation refers to how we can control what emotion to have, when to have it, and how to experience and express those emotions. In Western context, emotion
regulation includes the process of minimizing experience and behaviors resulted from negative emotions such as anger, fear, and sadness. Positive emotion is also regulated,
such as when we attempt to look less excited after defeating other people (for courtesy).
Emotion regulation can also involve the process of maximizing emotional experience, such as when we share good news to other people to strengthen its impact (McRae &
Gross, 2020). Gratz and Roemer (2004) defined emotion regulation as individual's emotional abilities such as emotional awareness, clarity, acceptance, impulsive control;
and their ability to fulfill their goals despite having negative emotions; and capability of
using proper strategies to modulate their expected emotional responses. The inexistence
of one of these abilities indicates the difficulties in emotion regulation (Trógolo et al.,
2014) Rhodes and Pivik (2011) found that there is an interaction between emotion and
risk perception, especially in young drivers. Risk perception and situational awareness are
vital for drivers to recognize the environment in which they are driving (Whelan et al.,
2002). Risk perception is a subjective measurement of the possibility of anything and how
big the consequences might be (Ghosh, 2004). Emotion certainly plays a role. Hu et al.
(2013) found that negative emotion induces a higher risk perception while positive emotion induces lower risk perception. Hence, the ability to regulate both positive and
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
negative emotions becomes more important since while driving, drivers are always faced
with risky situations and the need for rapid decision making.
Meta analysis conducted by Scott-Parker (2017) indicates that difficulty in emotion
regulation is associated with risky driving behaviors. In Indonesia, related research had been conducted to examine the association between self regulation - in which one of its
characteristics is the ability to modulate emotion- with risky driving behaviors. Nirmala
and Patria (2018) found that self regulation was negatively associated with risky driving behavior while conformity was positively associated. Based on these findings, we predicted difficulties in emotion regulation will correlate positively with risky driving behavior.
Optimistic Bias and Risky Driving Behavior
Optimistic bias is defined by the tendency of individuals to believe that positive experiences are more likely to happen compared to negative experiences (Weinstein,
1989). When individuals consider themselves to be less likely to have a negative experience compared to other people in their group, unrealistic optimism is formed (Ghosh, 2004).
Optimistic bias has been studied in variations of research topics and is associated
with risky behaviors ranging from health to business risks (e.g. Masiero et al., 2018; Wu et
al., 2018). Most studies in optimistic bias have found that this tendency is more likely to
appear in conditions that can be controlled personally, and individuals indeed see themselves having less risks compared to others (Dillard et al., 2009). Optimistic bias is
especially relevant in traffic safety since the ability to measure risks can determine whether to behave risky or safely. Previous research has consistently found that the
majority of drivers consider themselves to have above average capabilities in driving and
believe that they will be less likely to get involved in accidents compared to other drivers
(Gosselin et al., 2010). This kind of optimism can make people feel less vulnerable and less
motivated to engage in protective behaviors (White et al., 2011).
Cestac et al. (2011) found that in social comparison, majority of drivers experience
optimistic bias by overestimating their driving abilities, seeing their abilities as better than
others. This, in turn can affect their driving behaviors as confirmed in research conducted
by Jovanovic et al. (2014). By assuming that low risk perception is associated with careless
driving, they found that there is a significant correlation between risk perception and overestimation of driving ability and rates of traffic regulation violation and traffic accidents. Not only in Europe, in Indonesia inaccurate risk perception has also led to high
risky driving behavior among young drivers (Agung, 2014). Hence, we predicted that
higher optimistic bias will be followed by higher risky driving behaviors.
Current Research
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
The high number of traffic accidents in young drivers and the complexities of their development stages led to our interest in doing research in this age group, especially
among high school students. Seeing high school students driving is not something new in
Indonesia and mostly happens in big cities in Indonesia, such as Surakarta. Geographically, Nusukan region is one of the regions with most reported transportation
modes and activities in Surakarta (BPS Surakarta, 2016). One of the high schools located in
this region is SMAN VI Surakarta, which based on field study fits the criterion for research sample. This school was also chosen for its strategic location, namely being far
away from police station, which can lead to the possibility of higher risky driving and also the freedom for the students to drive even with no driving license.
In choosing this location, we did a small observation and interviews with involved
parties. Based on the teachers' explanation, almost 60 to 70% students drove their own
vehicles, whether they had driving licenses or not, and at least 2% of them had experienced traffic accidents while driving. In line with the teachers, all of the students interviewed admitted that they often engaged in traffic violations while driving. One of
them was even caught by the police due to not using safety equipment, such as helmets.
Moreover, when asked why they did that despite knowing the risks, they considered the actions as menial or 'normal' violations.
Studies on risky driving behaviors in young drivers have been well documented, both in Indonesia and globally. However, not many have identified the variables directly
related to the context of risk taking in driving, especially in Indonesia. The tendency of young drivers to take risks can be dependent on their emotional competency, such as
difficulties in emotion regulation. Moreover, variables such as optimistic bias is an interesting take since this variable is directly associated with subjective measurement of
risk perception. While similar in its sense, they differ because optimistic bias can be considered as heuristic judgment often associated with emotion-laden decision making (Bodenhausen, 1993). Both variables, emotion regulation and optimistic bias, rely on the
role of emotion, and are relevant to the risky driving behaviors of young drivers since
they belong in the critical period of emotional development (Chervonsky & Hunt, 2019).
This research was conducted to examine the relationship between emotion regulation and optimistic bias with risky driving behaviors, especially in young drivers. This research hoped to contribute to giving more informations about difficulties in regulation emotion, optimistic bias, and risky driving behaviors, while practically could give a consideration in developing preventive programs for traffic accidents.
M e t h o d
Sample
Population in the research were all students of SMAN VI Surakarta grade 10 to 11 who
used private vehicles on a daily basis, with total population of 261 students. They were
ADIRA et al. II EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
identified by the age group of 15 to 17 years old. We decided not to consider the ownership of driving license since previous research has indicated that there is no correlation between driving license ownership and traffic accidents or driving knowledge (Nastiti, 2017)
Sample was acquired using cluster random sampling. The clusters identified were
grade 10 and grade 11. Grade 10 was divided into eleven groups and grade 11 was divided into nine groups. From each cluster, we took five groups randomly for research
by lottery. We used the Slovin formula to determine the minimum sample size. Based on
the calculation with tolerance of error 5%, the sample needed was at least 158 students.
Due to the controversies surrounding the validity of Slovin formula (Tejada & Punzalan,
2012), we also used a sample size calculation using Gpower 3.1 (Erdfelder et al., 2009)
with power (1-ß) set at 0.70 and a = 0.05 based on effect size of 0.05 (calculated based on
previous research). This calculation generated a similar sample size with at least 158 students needed to get a comprehensive finding.
Data collection was conducted in ten days with 199 students using self report questionnaires. They were administered classically in each class during counselling guidance class with the school permission. Fifteen students were exluded from analysis
due to incompleteness of the questionnaires and the other 24 were considered outliers
based on Mahalanobis distance, Cook's distance and leverage. Final sample used in the analysis was 160 students.
Instruments
Risky driving behavior was measured the Behavior of Young Novice Drivers Scale (BYNDS), developed by Scott-Parker et al. (2012) and modified by the author consistent
with Indonesian context. For example, authors eliminated all items involving legal alcohol
consumption or illegal drugs, as these violations are not particularly documented among
youngsters in Indonesia. Other modifications included the addition of helmets usage for
safety measures, considering majority of the population use motorbikes instead of cars.
This measure was chosen due to its relevancy for target respondents and has been
through a well-documented validity testing (Scott-Parker et al., 2012). The scale was a Likert 5-points ranging from 1 for never to 5 for always, consisting of 27 items (a=0.893)
with dimensions such as transient violations ("You deliberately sped when overtaking"), fixed
violations ("Your passengers did not wear helmets or seatbelts"), misjudgment ("You misjudged
the gap when you were turning right"), risky exposure ("You drove at dusk or dawn"), driver
mood ("Your driving was affected by negative emotions like anger or frustration"). Higher score
in the scale indicates higher tendency of engaging in risky driving behavior. All scale modifications have been going through content validity by methodological experts. Item
analysis conducted prior also showed the scale having a good item discrimination index
with corrected item total correlation (fi) ranging from 0.301 - 0.656.
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
Difficulties in emotion regulation was measured using Difficulties in Emotion Regulation Scale (DERS) by Gratz and Roemer (2004) based on six emotion regulation dimensions which are non-acceptance of emotional responses ("I become irritated with myself when I am upset"), difficulties engaging in goal-directed behavior ("I have difficulty
getting work done when I am upset"), impulse control difficulties ("I have difficulty thinking
about anything else when I am upset"), lack of emotional awareness ("My emotions feel
overwhelming when I am upset"), limited access to strategies ("I believe that I will remain that
way for a long time when I am upset") and lack of emotional clarity ("I have difficulty making
sense out of my feelings."). This scale has been adapted frequently to Indonesian language
and was often used to target respondents with younger age group (e.g. Amanda et al., 2018; Athalia & Kilis, 2020). We employed the adapted version by Putri (2015). The scale was Likert 5-points ranging from 1 for highly disagree to 5 for highly agree, consisting of
21 items (a=0.920) with item discrimination index ranging from 0.432 - 0.796. Higher score
in the scale indicates higher difficulties in emotion regulation faced by the individual.
Optimistic bias. We employed direct comparison technique with a scale constructed by the authors based on three life event risks defined by Prentice et al. (2005).
We asked respondents how likely they are to experience these events based on three life risks which are controllable ("Getting involved in traffic accidents due to traffic violations"),
uncontrollable ("Becoming a victim of mugging in the road") and neutral ("Getting stuck in a
bad traffic"). The scale was a Likert 7-points ranging from 1 for very unlikely to 7 for
highly likely. Final scale consists of 21 items (a=0.936) with item discrimination index
ranging from 0.333 - 0.779. Lower score indicates higher optimistic bias.
A preliminary study was conducted to 33 respondents to analyze the basic psychometric components of each scale, the descriptive statistics, and discriminatory
index to determine whether to keep or drop the items. Reliability testing was conducted by internal consistency technique Cronbach's Alpha.
Data Analysis
To test the relationships between independent variables difficulties in emotion regulation
and optimistic bias with dependent variable risky driving behavior, we used multiple
linear regression. Prior to hypothesis testing, all the assumptions for multiple linear
regression were tested. The research model has met the normality, linearity, no
multicollinearity, autocorrelation, and heteroscedasticity assumptions. All the tests were
conducted with the help of statistical program Statistical Product and Service Solution (SPSS) version 24.0 for Windows.
Resul ts
Prior to hypothesis testing and after the assumptions testing, we employed demographic
analysis with mean comparison. Respondents' characteristics were shown in Table 1.
ADIRA et al. II EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
Table 1.
Respondents' Characteristics Characteristics N %
Age
15 years old
16 years old
17 years old
1 8
8 1
6 1
10
51.25
38.75
Sex
Male
Female
Years of driving
1-2 years
3-4 years
5-6 years
7-8 years
9 2
6 8
57.5
42.5
7 8
4 6
2 8
8
4 8 . 7 5
2 8 . 7 5
1 7 . 5
5
Mean comparisons based on age and number of years since driving were conducted using
analysis of variances (ANOVA), meanwhile comparison based on gender was conducted
using Mann Whitney since this grouping distribution did not meet the homogeneity assumption. Analysis results were shown in Table 2. We found no differences in risky
driving behavior based on demographic characteristics age, gender or number of years
since driving.
Table 2.
A N O V A
Risky Driving Behavior Mean Comparisons Based on Demographic Characteristics
Pred i c to r
A g e Years of driving
Sum of
Squares
405.219
479.819
d f Mean Square F Sig.
202.610
159.940
1 . 2 1 1
0 . 9 5 3
0,301
0,417
Mann Whitney Test
Pred ic to r
S e x
M a n n W h i t n e y W i l c o x o n
W
2884.500 5230.500
Z
- 0 . 8 4 1
Sig.
0 . 4 0 1
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
Regression analysis showed a significant relationship between difficulties in emotion regulation and optimistic bias together with risky driving behavior in young drivers from
SMA Negeri 6 Surakarta (F(2, 157) - 47.846; p < 0.01) with R? = 0.379. This indicated that
37.9% of variances and predictors difficulties in emotion regulation and optimistic bias explained risky driving behavior, while the other 62.1% were explained by other factors
outside the research.
Tab le 3 .
Partial Correlations
Unstandard ized
M o d e l C o e f f i c i e n t
S E
Standard i zed
C o e f f i c i e n t
Beta
C o n s t a n t
D E R S
O B
29 .561 6 .249
0 . 9 2 8 0 . 1 0 8
0 .151 0 .053
0 . 5 5 2
0 . 1 8 3
a Dependent variable: BYNDS (R - 0.615, R2 = 0.379, Adj. R? = 0.371)
t Sig.
0 . 5 6 6
0 . 2 2 2
4 . 7 3 1
8 .605
2 .852
0 . 0 0 0
0 . 0 0 0
0 . 0 0 5
Partial correlation shown in Table 3 was conducted to examine each independent
variable's association with the dependent variable once the other variables were statistically controlled. When optimistic bias was statistically controlled, significant and
positive correlation was found between difficulties in emotion regulation and young drivers' risky driving behavior (B = 0.552; r = 0.566; p < 0.05). In other words, the higher the
difficulties in emotion regulation, the higher their tendency to be engaged in risky driving
behavior. Meanwhile when the difficulties in emotion regulation were statistically controlled, significant and positive correlation was also found between optimistic bias
with risky driving behavior (B = 0.183; r = 0.222, p < 0.05). The higher respondents'
tendency to be optimistically biased, the higher their risky driving behaviors. Comparisons of ß score of each variable showed that higher contribution was given by
difficulties in emotion regulation compared to optimistic bias.
Discuss ion
This research was conducted to examine whether difficulties in emotion regulation and
optimistic bias tendency were associated with risky driving behaviors in young drivers.
Results showed these two variables indeed significantly predict the tendency of young
drivers to engage in risky driving behaviors. Previous studies have found the associations of young drivers' driving behavior
with their emotional competencies (Scott-Parker, 2017). Young drivers, in terms of their
developmental stage, are more vulnerable to driving emotionally. Based on the developmental stages, this period is the peak of emotional development. One of the
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
achievements of this emotional development is a competent emotion regulation. Emotion
regulation refers to individuals' ability to control and match their emotional reactions with the appropriate intensity to reach their goals. Moreover, young people in this stage
are more likely to develop egocentric attitudes (Redshaw, 2004). Egocentrism is one of the key factors inducing the tendency to be optimistically biased, or the tendency to believe
their likelihood to experience positive events is higher than that of the negative events.
Firstly, this research is in line with previous studies which have found the association between emotions and driving behaviors. Among them are Scott-Parker (2012) who had found emotion as a big factor in risky driving for young drivers, and Chan and
Singhal (2013) who also found emotion is related to their attention management while driving. Specifically, this research extends those studies by explaining that not only the
emotion valences, but their difficulties in emotion regulation affected by their developmental stages are main drivers of risky driving behaviors in young drivers. This
result supports the findings of Trógolo et al. (2014) where they found that difficulties in
emotion regulation were associated with driving behavior that is aggressive and dissociative. Aggressive and dissociative traits can be considered risky when we put them in the context of driving, where the need for a full attention is high.
Each individual has different risk perceptions for each life event. Therefore, risk perception is a subjective measurement by individuals of how likely an event to happen
and how big the consequences are likely to happen (Sjöberg et al., 2004). Risk perception
is ideally formed by the assumption of rational decision making, where individuals are expected to evaluate the consequences based on benefit and loss. However, this judgment
is not always rational and can be easily affected by heuristics (Paek & Hove, 2017). One of
the heuristic judgments in risk perception is the optimistic bias. People with high optimistic bias are more likely to perceive their risks to be less than that of others (Dillard
et al., 2009; Paek & Hove, 2017). Optimistic bias is especially relevant in traffic safety since
risk perception ability can determine whether people behave safely or risky, including
driving. Jiang et al. (2008) found optimistic bias in their respondents with high risky driving behaviors. This finding is also supported by Jovanovic et al. (2014) who found
that there is a significant association between risk perception, overestimation of driving ability with the likelihood of drivers to engage in traffic violations and accidents. In line
with those findings, this research specifically found the significant association between
optimistic bias in perceiving risks while driving and risky driving behaviors.
We found a bigger contribution of difficulties in emotion regulation more than optimistic bias in predicting risky driving behaviors. This can be attributed to the fact that
optimistic bias as a construct is more often measured in the group level of analysis, where
the life events had been specified and measurement targets were comparative. The
measurement in the individual level of analysis is not very well-documented. Due to those limitations, research with optimistic bias can be considered new. Weinstein et al. (2005) stated that the methodological problems in measuring optimistic bias could explain
ADIRA et al. II EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
the difficulties in examining how this bias can directly influence risky behaviors, unlike
easily accessed constructs such as self-efficacy or affects. Higher contribution in emotion
regulation also indicates that young drivers in particular, rely more on their emotional controls rather than their risk awareness while driving.
We also found gender as a variable with insignificant contribution in determining
whether there was a difference in risky driving behaviors among these groups. In contrast
with previous studies who have found gender as a significant predictor to risky driving
behaviors (e.g., Jelalian et al., 2000; Scott-Parker, 2017), we found no evidence to support
these findings. Meanwhile, this result is in line with the suggestion that the gap between
men and women is decreasing each year (Chen et al., 2010). Furthermore, hormonal effect
and cognitive analysis by Kusev et al. (2017) on risky behaviors also showed no evidence for differences based on gender.
Not only gender, we also did not find any evidence of differences based on age in
the young drivers' age group or number of years since driving, in contrast with previous
theories in how age can influence risky driving or the development of emotional competencies (Scheibe et al., 2016; Scott-Parker, 2012). However, this can be very well
explained for the small gap of age numbers in our sample age group. Therefore, the age
range for young drivers should be important to define for future research, considering these variations are vital to generalization and the need of designing target-appropriate
intervention programs (Scott-Parker, 2017). Constantinou et al., (2011) found that young
drivers in productive age were significantly more likely to be involved in traffic accidents
than other age groups. Hence, different results might be found among other age groups.
C o n c l u s i o n
Our findings generally supported our main hypothesis indicating the association between
difficulties in emotion regulation and optimistic bias with risky driving behaviors in young drivers. This finding can be included in suggestions for relevant parties such as the
school, communities and authorities on the importance of good emotion regulation development strategies and in raising risk awareness to minimize risky driving behavior.
Limitations and Future Research
This research is not free from limitations. Among them is scale administration which
could not be distributed at the same time, hence we could not ensure identical conditions
and contexts for data collection. To overcome this, we could only ensure the exact standard of the instructions given during each administration. We also could not find
differences based on age, in contrast with previous theories. Therefore, consideration
given for future research is to employ samples from various age groups.
ADIRA et al. Il EMO1TON REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
Acknowledgement
The authors would like to express our thanks to all parties who had helped with data collection.
We would also like to thank SMA Negeri 6 Surakarta, all the students and teachers involved, who had granted permission for data collection.
Funding
The research was self-funded by the author.
Author's contribution
First author NA was responsible for the overall content of the article. NA built the theoretical
concepts, did the data collection and wrote the whole manuscript. Second author M helped in developing theoretical concepts, literature review and managing data collection. Finally, PAS
developed the original research ideas, responsible for most of the data analysis and some parts of the discussion.
Conflict of interests The authors declare no conflict of interests in writing this article.
Orcid ID
Nesya Adira 0000-0002-8013-5196
Pratista Arya Satwika 0000-0002-6569-0108
Re fe rences
Agung, I. M. (2014). Model pengendara berisiko pada remaja. Jurnal Psikologi Integratif,
2(2), 35-41.
Amanda, S. R., Sulistyaningsih, W., & Yusuf, E. A. (2018). The involvement of father,
emotion regulation, and aggressive behavior on adolescents. International Research
Journal of Advanced Engineering and Science, 3(3), 145-147.
Athalia, A., & Kilis, G. (2020). A comparative study of mental health and emotional regulation between musicians and non-musicians. In 3rd International Conference on
Intervention and Applied Psychology (ICIAP 2019) and the 4th Universitas Indonesia
Psychology Symposium for Undergraduate Research (UIPSUR 2019) (pp. 56-68).
https://doi.org/10.2991/assehr.k.201125.005
Bodenhausen, G. V. (1993). Emotions, arousal, and stereotypic judgments: A heuristic
model of affect and stereotyping. In D. M. Mackie & D. L. Hamilton (Eds.), Affect,
Cognition and Stereotyping: Interactive Processes in Group Perception (pp. 13-37).
Academic Press. https://doi.org/10.1016/b978-0-08-088579-7.50006-5
BPS Surakarta (2016). Kecamatan-kecamatan Surakarta dalam angka tahun 2016. BPS
Surakarta. Retrieved from http://www.surakartakota.bps.go.id/
Cestac, J., Paran, F., & Delhomme, P. (2011). Young drivers' sensation seeking, subjective norms, and perceived behavioral control and their roles in predicting speeding
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
intention: How risk-taking motivations evolve with gender and driving experience. Safety Science, 49(3), 424-432. https://doi.org/10.1016/j.ssci.2010.10.007
Chan, M., & Singhal, A. (2013). The emotional side of cognitive distraction: Implications
for road safety. Accident Analysis and Prevention, 50, 147-154, https://doi.org/10.1016/j.aap.2012.04.004
Chen, H. Y., Senserrick, T., Martiniuk, A. L. C., Ivers, R. Q., Boufous, S., Chang, H. Y., &
Norton, R. (2010). Fatal crash trends for Australian young drivers 1997-2007: Geographic and socioeconomic differentials. Journal of Safety Research, 41(2), 123-
128. https://doi.org/10.1016/j.jsr.2009.12.006
Chervonsky, E., & Hunt, C. (2019). Emotion regulation, mental health, and social wellbeing in a young adolescent sample: A concurrent and longitudinal investigation. Emotion, 19(2), 270-282. https://doi.org/10.1037/emo0000432
CNN (2021). 100 ribu kecelakaan lalin pada 2020, pelajar SMA terbanyak. CNNIndonesia.com.
Retrieved from https://www.cnnindonesia.com/teknologi/20210310124314-384-
615978/100-ribu-kecelakaan-lalin-pada-2020-pelajar-sma-terbanyak
Constantinou, E., Panayiotou, G., Konstantinou, N., Loutsiou-Ladd, A., & Kapardis, A.
(2011). Risky and aggressive driving in young adults: Personality matters. Accident
Analysis and Prevention, 43(4), 1323-1331. https://doi.org/10.1016/j.aap.2011.02.002
Dillard, A. J., Midboe, A. M., & Klein, W. M. P. (2009). The dark side of optimism: Unrealistic optimism about problems with alcohol predicts subsequent negative
event experiences. Personality and Social Psychology Bulletin, 35(11), 1540-1550.
https://doi.org/10.1177/0146167209343124
Erdfelder, E., Faul, F., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using
G*Power 3.1: Tests for correlation and regression analyses. Behavior Research
Methods, 41(4), 1149-1160. https://doi.org/10.3758/BRM.41.4.1149
Fisher, D. L., Laurie, N. E., Glaser, R., Connerney, K., Pollatsek, A., Duffy, S. A., & Brock, J.
(2002). Use of a fixed-base driving simulator to evaluate the effects of experience
and PC-based risk awareness training on drivers' decisions. Human Factors, 44(2),
287-302. https://doi.org/10.1518/0018720024497853
Ghosh, A. K. (2004). Explaining risk. Minnesota Medicine, 87(2), 6.
Gosselin, D., Gagnon, S., Stinchcombe, A., & Joanisse, M. (2010). Comparative optimism
among drivers: An intergenerational portrait. Accident Analysis & Prevention, 42(2),
734-740. https://doi.org/10.1016/j.aap.2009.11.001
Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of emotion regulation and
dysregulation: Development, factor structure, and initial validation of the difficulties in emotion regulation scale. Journal of Psychopathology and Behavioral
Assessment, 26(1), 41-54. https://doi.org/10.1023/B:JOBA.0000007455.08539.94
Gulliver, P., & Begg, D. (2007). Personality factors as predictors of persistent risky driving
behavior and crash involvement among young adults. Injury Prevention, 13(6), 376- 381. https://doi.org/10.1136/ip.2007.015925
ADIRA et al. I| EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
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. https://doi.org/10.1016/j.trf.2012.08.009
Jelalian, E., Alday, S., Spirito, A., Rasile, D., & Nobile, C. (2000). Adolescent motor vehicle
crashes: The relationship between behavioral factors and self-reported injury.
Journal of Adolescent Health, 27(2), 84-93. https://doi.org/10.1016/S1054- 139X(00)00098-7
Jiang, L., Li, Y., & Liu, X. (2008). The effects of motor impulsiveness and optimism bias on
risky driving behavior in Chinese urban areas. In IEEE Conference on Intelligent
Transportation Systems, Proceedings, ITSC (pp. 605-609). https://doi.org/10.1109/ITSC.2008.4732582
Joewono, T. B., & Susilo, Y. O. (2017). Traffic violations by young motorcyclists on Indonesian urban roads. Journal of Transportation Safety and Security, 9(sup1), 236-
261. https://doi.org/10.1080/19439962.2016.1247123
Jovanovic, D., Stanojevic, P., Jaksic, D. (2014). The influence of risk perception and self- assessed driving. In Proceedings of the XII International Symposium "Road Accidents
Prevention (pp. 9-10).
Jusuf, A., Nurprasetio, I. P., & Prihutama, A. (2017). Macro data analysis of traffic accidents in Indonesia. Journal of Engineering and Technological Sciences, 49(1), 133-
144. https://doi.org/10.5614/j.eng.technol.sci.2017.49.1.8
Korlantas. (2021). Statistik Laka Februari 2021. Korlantas Polri. Retrieved from https://korlantas.polri.go.id/statistik-laka/
Kusev, P., Purser, H., Heilman, R., Cooke, A. J., Van Schaik, P., Baranova, V., ... Ayton, P.
(2017). Understanding risky behavior: The influence of cognitive, emotional and
hormonal factors on decision-making under risk. Frontiers in Psychology, 8, 102. https://doi.org/10.3389/fpsyg.2017.00102
Masiero, M., Riva, S., Oliveri, S., Fioretti, C., & Pravettoni, G. (2018). Optimistic bias in
young adults for cancer, cardiovascular and respiratory diseases: A pilot study on
smokers and drinkers. Journal of Health Psychology, 23(5), 645-656. https://doi.org/10.1177/1359105316667796
Mawardah, M., & Adiyanti, M. (2014). Regulasi emosi dan kelompok teman sebaya pelaku cyberbullying. J u r n a l Psikologi, 41(1), 60-73.
https://doi.org/10.22146/jpsi.6958
McRae, K., & Gross, J. J. (2020).Emotion regulation. Emotion, 20(1), 1-9. https://doi.org/10.1037/emo0000703
Nastiti, F. A. (2017). Hubungan antara kepemilikan SIM C dan keikutsertaan dalam tes
pembuatan SIM dengan pengetahuan berkendara dan kecelakaan lalu lintas di
Kabupaten Sidoarjo. The Indonesian Journal of Public Health, 12(2), 167-178. https://doi.org/10.20473/ijph.v12i2.2017.167-178
Nirmala, H. V. P., & Patria, B. (2018). Peran regulasi diri dan konformitas terhadap
ADIRA et al. Il EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
perilaku berkendara berisiko pada remaja. Gadjah Mada Journal of Psychology
(GamajoP), 2(2), 113-125. https://doi.org/10.22146/gamajop.33095
Paek, H.-J., & Hove, T. (2017). Risk perceptions and risk characteristics. In Oxford Research
Encyclopedia Communication.
https://doi.org/10.1093/acrefore/9780190228613.013.283
Prentice, K. J., Gold, J. M., & Carpenter, W. T. (2005). Optimistic bias in the perception of
personal risk: Patterns in schizophrenia. American Journal of Psychiatry, 162(3), 507-
512. https://doi.org/10.1176/appi.ajp.162.3.507
Putri, A. G. (2015). Pengaruh terapi membatik terhadap peningkatan regulasi emosi pada remaja
di SMK Batik 1 Surakarta. Universitas Gadjah Mada.
Reason, J., Manstead, A., Stephen, S., Baxter, J., & Campbell, K. (1990). Errors and violations on the roads: A real distinction? Ergonomics, 33(10-11), 1315-1332.
https://doi.org/10.1080/00140139008925335
Redshaw, S. (2004). Theories of driver behaviour and driving emotions. In Proceedings of
the Australasian road safety research, policing and education conference (Vol. 8).
Retrieved from https://trid.trb.org/view/771067
Regev, S., Rolison, J. J., & Moutari, S. (2018). Crash risk by driver age, gender, and time of
day using a new exposure methodology. Journal of Safety Research, 66, 131-140.
https://doi.org/10.1016/j.jsr.2018.07.002
Rhodes, N., & Pivik, K. (2011). Age and gender differences in risky driving: The roles of
positive affect and risk perception. Accident Analysis & Prevention, 43(3), 923-931.
https://doi.org/10.1016/j.aap.2010.11.015
Santosa, S. P., Mahyuddin, A. I., & Sunoto, F. G. (2017). Anatomy of injury severity and
fatality in Indonesian traffic accidents. Journal of Engineering and Technological
Sciences, 49(3), 412-422. https://doi.org/10.5614/j.eng.technol.sci.2017.49.3.9
Sarwono, S. W. (2016). Psikologi remaja (Edisi pertama). Rajawali Pers.
Scheibe, S., Spieler, I., & Kuba, K. (2016). An older-age advantage? Emotion regulation
and emotional experience after a day of work. Work, Aging and Retirement, 2(3),
307-320. https://doi.org/10.1093/workar/waw010
Scott-Parker, B. (2017). Emotions, behaviour, and the adolescent driver: A literature
review. Transportation Research Part F: Traffic Psychology and Behaviour, 50, 1-37.
https://doi.org/10.1016/j.trf.2017.06.019
Scott-Parker, B., Watson, B., King, M. J., & Hyde, M. K. (2012). Confirmatory factor analysis of the Behaviour of Young Novice Drivers Scale (BYNDS). Accident Analysis & Prevention, 49, 385-391. https://doi.org/10.1016/j.aap.2012.02.021
Scott-Parker, B. (2012). A comprehensive investigation of the risky driving behaviour of young
novice drivers. Queensland University of Technology.
Scott-Parker, B., & Oviedo-Trespalacios, O. (2017). Young driver risky behaviour and predictors of crash risk in Australia, New Zealand and Colombia: Same but different?. Accident Analysis Prevention, 99, 30-38.
ADIRA et al. II EMOTION REGULATION, OPTIMISTIC BIAS, RISKY DRIVING
https://doi.org/10.1016/j.aap.2016.11.001
Shope, J. T., & Bingham, C. R. (2008). Teen driving. Motor-vehicle crashes and factors that
contribute. American Journal of Preventive Medicine, 35, S261--S271.
https://doi.org/10.1016/j.amepre.2008.06.022
Sjöberg, L. (2004). Explaining individual risk perception: The case of nuclear waste. Risk
Management, 6(1), 51-64.
Soehodho, S. (2007). Motorization in Indonesia and its impact to traffic accidents. IATSS
Research, 31(2), 27-33. https://doi.org/10.1016/s0386-1112(14)60219-3
Tejada, J., & Punzalan, J. (2012). On the misuse of Slovin's formula. The Philippine
Statistician, 61(1), 129-136.
Trógolo, M. A., Melchior, F., Medrano, L. A. (2014). The role of difficulties in emotion
regulation on driving behavior. Journal of Behavior, Health & Social Issues, 6(1), 107-
117. https://doi.org/10.5460/jbhsi.v6.1.47607
Ulleberg, P., & Rundmo, T. (2003). Personality, attitudes and risk perception as predictors
of risky driving behaviour among young drivers. Safety Science, 41(5), 427-443.
https://doi.org/10.1016/S0925-7535(01)00077-7
Weinstein, N. D. (1989). Optimistic biases about personal risks. Science, 246(4935), 1232-
1233. https://doi.org/10.1126/science.2686031
Weinstein, N. D., Marcus, S. E., & Moser, R. P. (2005). Smokers' unrealistic optimism
about their risk. Tobacco C o n t r o l , 14(1), 55-59.
http://dx.doi.org/10.1136/tc.2004.008375
Whelan, M. I., Groeger, J. A., Senserrick, T., & Triggs, T. J. (2002). Alternative methods of
measuring hazard perception: Sensitivity to driving experience. In Road Safety
Research, Policing and Education Conference, RS2002 (Vol. 6, pp. 81-86). Retrieved
from http://trove.nla.gov.au/work/17479316?q=t&versionld=20497433
White, M. J., Cunningham, L. C., & Titchener, K. (2011). Young drivers' optimism bias for
accident r isk and driving ski l l : Accountabi l i ty and insight experience
manipulat ions. Accident Analys is & Prevention, 43(4), 1309-1315.
https://doi.org/10.1016/j.aap.2011.01.013
WHO [World Health Organization]. (2015). Global status report on road safety 2015.
Retrieved from https://www.who.int/publications/i/item/9789241565684
WHO [World Health Organization]. (2018). Global road safety report 2018. Retrieved from
https://www.who.int/publications/i/item/9789241565684
Wu, Y., Liu, T., Han, L., & Yin, L. (2018). Optimistic bias of analysts' earnings forecasts:
Does investor sentiment matter in China? Pacific Basin Finance Journal, 49, 147-163.
https://doi.org/10.1016/j.pacfin.2018.04.010 Zuraida, R., Iridiastadi, H., & Sutalaksana, I. Z. (2017). Indonesian drivers' characteristics
associated with road accidents. International Journal of Technology, 8(2), 311-319.
https://doi.org/10.14716/ijtech.v8i2.6148
