category: literaturenote citekey: stanojeviceffectivenessimplementinggraduateddriver2022 title: Effectiveness of implementing a Graduated Driver Licensing (GDL) law among young Serbian drivers authors: "Stanojević, Predrag; Lajunen, Timo; Jakšić, Dragana; Jovanović, Dragan; Matović, Boško" year: 2022 date: 2022-00-00 2022 doi: 10.1016/j.jsr.2022.09.008 publication: Journal of Safety Research url: "https://doi.org/10.1016/j.jsr.2022.09.008" zotero_key: ISX3X7RE zotero_storage: 2CNJ7JFE collections: transpordi_planeerimine folder: 001_artiklid firstAuthor: "Stanojević, Predrag"

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Journal of Safety Research

journal homepage: www.el sevier.com/locate/jsr

Effectiveness of implementing a Graduated Driver Licensing (GDL) law among young Serbian drivers

Predrag Stanojevic´ ^a , Timo Lajunen ^b , Dragana Jakšic´ ^a , Dragan Jovanovic´ ^c , Boško Matovic´ d,⇑

^a Academy of Applied Studies of Kosovo and Metohija, Serbia
^bDepartment of Psychology on the Norwegian University of Science and Technology, Trondheim, Norway
^cDepartment of Transport and on the Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia
^d Faculty of Mechanical Engineering, University of Montenegro, Podgorica, Montenegro

article info

Article history: Received 24 July 2021 Received in revised form 1 June 2022 Accepted 13 September 2022 Available online 22 September 2022

Keywords: Young drivers Graduated driver licensing Attitudes Risk behavior

abstract

Introduction: Young novice drivers have higher rates of engagement in road crashes worldwide, often owing to unfavorable attitudes toward road safety or lack of knowledge, experience, and risk consciousness. However, the implementation of graduated driver licensing (GDL) systems has proven effective in reducing the high incidence of young drivers involved in crashes. Method: The purpose of this study was to compare the change in driving outcomes (e.g., attitudes toward traffic safety, behavior patterns while driving, risk assessment in traffic, assessment of personal driving skills, and involvement in traffic crashes) of young drivers prior to and following the implementation of a GDL law. Respondents (n = 642) completed a battery of questions, including a driver attitudes questionnaire (Behaviour of Young Novice Drivers Scale), a self-assessed driving ability questionnaire, and a risk perception questionnaire. Of the total sample size, 324 drivers passed the old system of training driver's license candidates, and 318 drivers passed the new GDL system. Results: The results showed that drivers licensed with GDL reported safer attitudes toward traffic rule violations and speed, and higher levels of safety orientation with regard to their driving abilities. They also reported much higher levels of risk perception and lower exposure to risky situations (risky driving exposure). There were no differences between GDL drivers and non-GDL drivers in terms of self-reported crashes or transient or fixed violations. In addition, GDL was not related to the number of traffic crashes, the number of fatalities, or serious and slight injuries in crashes involving young drivers in crashes obtained from official records. Conclusions: The results suggest that GDL contributed to the improvement of drivers' attitudes and understanding of risk but did not contribute to significant changes in the behavior of young drivers and traffic crashes. In addition, the GDL program in Serbia only ranks fair on the Insurance Institute for Highway Safety (IIHS) scale. Strengthening the GDL program in Serbia with additional components in line with GDL programs rated as good by the IIHS scale could improve the safety of young and novice drivers in traffic.

1. Introduction

Road traffic crashes have been the leading cause of death and serious injury among young adults in the last decade. Based on data provided by the World Health Organization (WHO, 2018), road traffic crashes are a leading cause of death globally, and young drivers aged 16–25 are significantly overrepresented among those killed and seriously injured.

Research has shown that young drivers commonly engage in risky driving behaviors, including exceeding the speed limit

E-mail address: boskom@ucg.ac.me (B. Matovic´).

(ECMT, 2006; Scott-Parker et al., 2013), driving under the influence of alcohol (ECMT, 2006; NHTSA, 2018), dangerous overtaking (Fernandes et al., 2010), and distracted driving (Korpinen & Pääkönen, 2012; Lipovac et al., 2017). Using Serbia state year data on fatal crashes during 2016–2019, it has been found that among young drivers aged 18–24, 22 % and 8 % of all fatal traffic accidents involved inappropriate speed in relation to traffic and road conditions and alcohol-impaired driving (RTSA, 2021), respectively.

The main factors related to young driver traffic crashes are inexperience, sex, and age (ECMT, 2006). Studies that included the factors of inexperience and age have shown that these two factors are the critical predictors of crashes among young drivers (Chapman et al., 2014; McCartt et al., 2003; Twisk & Stacey, 2007). McCartt et al. (2009) reviewed 11 studies that attempted to separate the

^⇑ Corresponding author at: Faculty of Mechanical Engineering, University of Montenegro, Podgorica, Bulevar Dzˇordzˇa Vašingtona bb, Montenegro.

crash effects of age and experience, represented by the length of licensure. The results showed that age and experience have important, independent effects on crash risk, even after differences in driving mileage are accounted for. Meanwhile, studies on sex have demonstrated that male drivers are prevalent in traffic crashes involving young drivers. In Australia, for example, the death rate in 2017 was three times higher for males than for females in the 17–25 age category (BITRE, 2018). Further, studies have reported that drivers' attitudes, sensation-seeking, and personality traits could predict poor driving outcomes and high-risk driving behavior in young individuals (e.g., Hassan & Abdel-Aty; 2013; Khan et al., 2020; Preece et al., 2018; Ulleberg & Rundmo, 2003).

To reduce risks to young drivers, a range of countermeasures needs to be applied. Such countermeasures should include improvements in the areas of training, education, testing, communication, enforcement, and technology (ECMT, 2006; Molloy et al., 2019; Scott-Parker et al., 2015; Twisk & Stacey, 2007). A reasonable assumption is that education and training can correct attitudes toward traffic safety and establish safe behavioral patterns in young drivers. Driver training refers to teaching people driving skills to control and operate a vehicle to obtain a license, whereas driver education is a broader term that implies not only driver training but also general road safety concepts, road laws, behaviors, and awareness as well (Barua et al., 2014). Research findings on the effects of driver education in terms of fewer traffic violations and crashes have been mixed: Some studies show no significant effects of education on crashes or violations (Bates et al., 2020; Lonero & Mayhew, 2010); others show reductions in crashes or violations for those receiving driver education (Shell et al., 2015; Vanlaar et al., 2009).

Various licensing systems are used worldwide. Generally, the following categories of licensing systems can be distinguished: (1) traditional licensing systems and two-phase systems and (2) graduated driver licensing (GDL) systems. Two-phase systems represent a variation in probationary licensing systems, in which candidates must go through two phases of driving theory and training before becoming a fully licensed driver. After completing the first phase of the licensing process, candidates obtain a provisional or probationary license that allows them to drive solo under given conditions; a full license is issued after completion of the second phase of theory and training, without further testing (ECMT, 2006). Similar to other related systems, such as two-phase systems or systems that include a probationary license, GDL aims to address certain specifics of the ''young driver problems." GDL systems include an extension of the learning period, supervised driving, and after obtaining the initial license, restrictions on driving with peer passengers and nighttime driving. In essence, GDL programs focus on inexperienced drivers and are tasked with ensuring that they are exposed only to driving conditions appropriate to their skills while they are in the process of developing additional skills and experience (Foss, 2007). GDL systems have proven highly effective in reducing the risk of crashes among young drivers (Bates et al., 2018; Shope, 2007). In October 2012, a GDL system was introduced in Serbia, comprising educational training and the GDL component proper. The educational training component consists of several phases. The first phase includes 40 hours of education (acquisition of theoretical knowledge for safe participation in traffic). The second phase includes mastering driving skills, and the training includes practical driving (on the street) after obtaining the certificate for the completion of the theoretical test. The third phase includes a first-aid examination. First-aid training and examination are organized by the Red Cross of Serbia. When all of these phases are completed, the driving test proper is conducted. The new GDL system component in Serbia implies first obtaining a probationary driver's license with restrictions on speed, night driving, cell phone use, and alcohol use, and with required supervised driving. A full license is obtained after one year of driving with a probationary license. Supervised driving is required for holders of a probationary driver's license obtained at the age of 17 and lasts one year, that is, until the expiration of the probationary license. Supervised driving is not required for drivers who obtain a probationary license after the age of 18. All other restrictions affect all holders of a probationary driver's license. The police are responsible for enforcing restrictions on young drivers. They can readily identify drivers subject to restrictions based on a ''P" sticker placed on drivers' vehicle and check whether young drivers adhere to the legally defined restrictions. Further, for the enforcement of restrictions on holders of a probationary driver's license obtained at the age of 17, the person who supervises the driver (who should hold a license valid for at least five years) is responsible.

In the traditional training system that was in place in Serbia before the GDL system, the novice driver was fully licensed after passing the driving test, and no special conditions were placed. Novice drivers had 40 hours of driving training (polygon and street driving), and after completing the training, a driving exam was conducted, which was composed of two parts: theoretical and practical. After passing the driving test, candidates instantly obtained a full license. A more detailed presentation of the new GDL system and its comparison with the traditional training system are presented in Table 1.

Evaluation of the effects of driver education on intermediate outcome criteria should include examinations of changes in behavior, attitudes, knowledge, and exposure to risk (Lonero & Mayhew, 2010). In their literature review, Thomas et al. (2012) found little solid evidence that driver education affects teen crashes or other outcomes. However, recent studies have revealed that education and training within GDL programs are linked to a smaller number of crashes and traffic violations (Mayhew et al. 2014; Shell et al., 2015). Based on the reviewed literature, we hypothesized that: drivers licensed with GDL have more favorable attitudes toward traffic safety (H1); drivers licensed with GDL have safer behavior patterns while driving (H2); drivers licensed with GDL have better risk assessment in traffic (H3); drivers licensed with GDL have better assessment of personal driving skills (H4); and drivers licensed with GDL have fewer crash involvements (H5).

2. Methods

2.1. Participants and procedure

The data in this study were collected by mail. The names and addresses of 1,000 individuals (young drivers aged 17–26 years with driving experience of up to three years) with valid driver's licenses were obtained from a registry of motor-vehicle owners. Participants were instructed to thoroughly read all the questions in the study questionnaire and honestly provide their answers, which would be treated as anonymous. Participants were also assured that their data would be treated as confidential and would only be used for the purpose of the study. To reduce the possibility of participants giving socially desirable answers, participants were not asked to provide their names in the questionnaire. Questionnaires were collected on two occasions. At the end of 2012, 500 questionnaires were distributed to young drivers who had passed the old system of training driver's license candidates (pre-GDL). At the end of 2016, another 500 questionnaires were distributed to young drivers who passed the new system of training driver's license candidates (GDL). In both cases, a reminder was sent to non-respondents. A total of 642 participants completed and returned the distributed questionnaires: 265 were female and 377 were male. Based on data obtained from the questionnaires, a comparison of young drivers licensed pre-GDL and those licensed

Table 1 Comparison of the content of the traditional training system with the GDL system in Serbia.

	Pre-GDL	GDL
Learner's entry age	18	16
Minimum age for obtaining a license	18	17
Full license	Immediately after passing the driving exam	After one-year of driving with a probationary license
Learner's holding period	about 1 month	About 3 months
Theoretical education	No theoretical education	40 hours of theoretical education (acquisition of theoretical knowledge for safe participation in traffic)
Driving training	40 hours of driving (driving training is not conditioned by taking the theoretical test)	40 hours of driving (prior to driving training, passing the theoretical test is obligatory)
First-aid training	Was not applicable	8 hours of training followed by the examination
Probationary driver's license	Did not exist	Probationary driver's license with one-year validity. For the holders of a probationary driver's license who obtain a license at the age of 17, the restrictions are as follow: (a) Supervised driving with a person who holds a license with a validity of at least 5 years (b) Not allowed to drive at a speed of over 110 km/h on a highway, 90 km/h on a motorway, and 90 % of the speed allowed on the part of the road on which driving takes place (other roads) (c) Night driving restriction from 11:00p.m. to 5:00 a.m. (d) The driver may not use a cell phone while driving (e) Allowed BAC 0.0 g/l
Price Video surveillance	From 250 to 300 Euros (280 to 330 USD) Did not exist	(f) Vehicle must have a ''P" sticker on a visible place on the front and the rear side of the vehicleFor the holders of a probationary driver's license who obtained the license at the age of 18, the same restrictions apply except under paragraph a). From 500 to 550 Euros (550 to 600 USD) Obligatory when taking tests and during the lectures

with GDL was conducted using various measures, including attitudes, risky behavior, self-assessed driving ability, risk perception, and the number of self-reported crashes.

The demographic characteristics of the overall sample are presented in Table 2.

To obtain a more complete picture of the effects of GDL, a comparison of the rates of crashes with causalities, fatalities, serious injuries, and slight injuries per 100,000 licensed drivers (aged 18–26) before and after the implementation of GDL was performed. Data on traffic crashes and the number of young drivers were obtained from official records (Road Traffic Safety Agency and Ministry of Interior). The time coverage was the period from 2002 to 2020, and the rates of traffic crashes with causalities, fatalities, serious injuries, and slight injuries in the period from 2002 to 2012 (before the implementation of GDL) were compared with the period from 2013 to 2020 (after the implementation of GDL).

2.2. Measures

2.2.1. Drivers' attitudes

Drivers' attitudes were measured using a questionnaire that comprised 23 items. The responses were marked on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). We used this questionnaire to test the following attitudes: the attitude toward the violation of traffic regulations (8 items; e.g., 'There are many traffic rules which cannot be obeyed to keep up the traffic flow,' or 'Sometimes it is necessary to bend the rules to keep traffic going'); the attitude toward speed (7 items; e.g. 'If you have good skills, speeding is OK,' or 'Driving 5 or 10 miles above the speed limit is OK because every-one does it'); the attitude toward drinking and driving (5 items; e.g., 'People can drive safely even if they are under the influence of alcohol,' or 'People should be allowed to decide themselves how much they can drink and drive after that'); and the attitude toward joyriding (6 items; e.g., 'Adolescents have a need for fun and excitement in traffic,' or 'Speeding and excitement belong together when you are driving'). The attitude scales were based on questionnaires developed by Ulleberg and Rundmo (2003) and Iversen and Rundmo (2004).

2.2.2. Behaviour of young novice drivers scale

The Behaviour of Young Novice Drivers Scale (BYNDS, Scott-Parker et al., 2010) was used to measure the risky behavior of young novice drivers. The BYNDS contains five subscales that are added to obtain a composite risky driving score. Transient violations (13 items) measure risky driving behaviors that can change throughout the journey, such as driving speed and speaking on a mobile phone. Fixed violations (10 items) explore risky driving behaviors that are unlikely to change throughout the journey, such as alcohol and/or drug intoxication, and the wearing of seatbelts. Misjudgment (9 items) captures the novice driving errors that

Table 2 Participants' demographic characteristics.

	pre-GDL	GDL	P value
Response rate	64.8 %	63.6 %
Sex
Male (%)	195 (60.2)	182 (57.2)	0.447
Female (%)	129 (39.8)	136 (42.8)
Age
Mean (S.D.)	20.21	21.12	<0.001
	(2.17)	(2.43)
Range	18–26	18–26
Distribution of ages
17–18 (%)	91 (28.1)	64 (20.1)	<0.001
19–20 (%)	106 (32.7)	80 (25.2)
21–22 (%)	76 (23.5)	76 (23.9)
23–24 (%)	33 (10.2)	58 (18.2)
25–26 (%)	18 (5.6)	40 (12.6)
Duration of driving experience in moths
Mean (S.D.)	21.07	15.14	<0.001
Range	0–84	0–42
Month mileage in km
Mean (S.D.) - Total sample	516 (1059)	272 (604)	<0.001
Mean (S.D.) - Males	705 (1261)	336 (643)
Mean (S.D.) - Females	230 (527)	185 (537)
Education
College degree or more (%)	63 (19.4)	102 (32.1)	<0.001
Less than college degree (%)	261 (80.6)	216 (67.9)
Number of self-reported crashes from the obtaining the license
Range	0–6	0–6	0.427
Mean (S.D.)	0.40 (0.89)	0.35 (0.88)

place the young driver at an increased risk of crash, such as underestimating the distance required to stop and misjudging the gap when overtaking or turning across traffic. Risky exposures (9 items) gauge the risky circumstances of the young novices' driving, including driving at night and with their friends as their passengers. Driver moods (3 items) demonstrate the extent to which the young novices are driving in response to their emotions, including anger and frustration (Scott-Parker & Proffitt, 2015).

Respondents were asked to indicate how often they have engaged in the following behaviors. Responses were recorded on a 5-point Likert scales that ranged from 1 to 5 (1 = never to 5 = almost all the time).

2.2.3. Self-assessed driving ability questionnaire

The measurement instrument applied to examine self-assessed driving ability comprised 22 indicators (Tronsmoen, 2008). The indicators fell into four dimensions. The first dimension related to self-assessment of general driving ability (8 items) included skills such as speeding, anticipating, driving in slippery conditions, and driving in the dark. The second dimension, safety orientation (6 items), referred to the driver's perception of his/her own ability to identify risk, danger and his/her perception of their ability to drive with satisfactory safety margins. The third dimension was the body dimension (5 items), which measured the feeling of unity with and control of the car. The fourth dimension was specific task skills (8 items) and items under this dimension consisted of judgment of the ability for precise and effective parallel parking, reversing into a garage, as well as reversing using the rear-view mirrors. The subjects were asked how well the statements fit the way they manage and perceive driving a car. The responses were marked on a 5-point scale (1 = does not fit me at all to 5 = fits me perfectly).

2.2.4. Risk perception questionnaire

The risk perception questionnaire (Harbeck & Glendon, 2013) comprised 10 items. The respondents were asked to estimate how risky the given actions were in traffic (e.g., driving under influence of alcohol, driving over the 20 km/h speed limit). The responses were recorded on a 5-point Likert-type scale (from 1 = not risky to 5 = extremely risky).

2.2.5. Demographic variables

Respondents answered questions about their age, sex, education, and crash involvement during the previous three years (number of self-reported crashes [crashes with fatalities + crashes with material damage]), and were also asked to estimate their monthly mileage.

2.2.6. Data from official records

Data on traffic crashes of young drivers age 18–26 (data on the total number of crashes with casualties, killed and injured young drivers can be found in Appendix A Table A1) are extracted from the integrated database of characteristics of traffic safety RTSA (RTSA, 2021).

The number of licensed young drivers aged 18–26 was obtained from the Ministry of Interior of the Republic of Serbia. This was used for the calculation of rates pertaining to crashes, fatalities, serious injuries, and slight injuries per 100,000 licensed drivers (aged 18–26) for each year of investigation.

2.3. Statistical analyses

Instruments used in this study had not yet been validated on a Serbian sample. Because some cultural, social, and economic factors could result in a different factor structure, we decided to analyze all scales using factor analysis. Considering the recommendations that confirmatory factor analysis (CFA) should be used when the underlying structure has been established based on prior empirical and theoretical grounds, the factor structure of all the instruments used in the study was initially examined using CFA. However, if the model on some scale produced a poor fit to the data, principal component analysis was run to examine the factor structure of the given instrument. Reliability for finalized measures and established scales was assessed using internal consistency (Cronbach's alpha). The values for asymmetry and kurtosis between 2 and + 2 are considered acceptable in order to prove normal univariate distribution (George & Mallery, 2010). A oneway between groups analysis of covariance (ANCOVA) was used to identify differences between young drivers licensed pre-GDL with those licensed with a GDL, after controlling for sex and mileage. As the self-reported yearly accident rate did not follow normal distribution, Poisson or negative binomial regression analyses (see Lord, Washington, & Ivan, 2005) were performed to test the relationship between GDL program and traffic crashes. In this analysis, the dependent variable was traffic crashes and independent variables were mileage, GDL program and their interactions (GDL mileage). Interaction between GDL program and mileage was included in the model because there is a statistically significant difference between young drivers licensed pre-GDL and those licensed with a GDL (see Table 2). Therefore, there is a possibility that GDL is associated with the reduction of mileage at young drivers that further leads to the reduction of the number of traffic crashes. Finally, a comparison of traffic crashes (obtained from the official records) of young drivers before and after the implementation of GDL was performed. The time coverage of the research is the period 2002–2020.

3. Results

3.1. Factor analysis of the scales for examining attitudes, behaviors, self-assessed driving ability, and risk perception of young drivers

Confirmatory factor analysis (CFA) was used to test the internal structure of the driver attitudes questionnaire, Behaviour of Young Novice Drivers Scale (BYNDS), self-assessed driving ability questionnaire, and risk perception questionnaire used in this study. Model fit was evaluated using the v² /degree of freedom ratio, root mean square error of approximation (RMSEA), goodness-of-fit index (GFI), comparative fit index (CFI), and standardized root mean square residual (SRMR). In general, a good model fit should have a 2:1 or 5:1 v² /degree of freedom ratio and GFI > 0.90, CFI > 0.90 (preferably > 0.95), RMSEA < 0.08 or 0.10 (preferably < 0.06), and SRMR < 0.08 (preferably < 0.05) indices (Hu & Bentler, 1999; Russell, 2002). All scales except the BYNDS model showed a good fit for the data (the results of the CFA can be found in Appendix A, Table A2).

Methodologically, CFA and exploratory factor analysis (EFA) models cannot be applied to the same data. Therefore, the initial group of 642 participants was randomly divided into two subgroups. The first subgroup (Sample 1) was used to perform the CFA and consisted of 317 drivers (179 males and 138 females). Given that the application of CFA provided a poor fit for the BYNDS (the results are given in Appendix A Table A2), the data were reexamined within an EFA framework. An EFA was conducted with the second subgroup (Sample 2, 325 drivers, out of which 198 were male and 127 were female) with principal components by using an oblique promax rotation with Kaiser normalization. Initially, 44 items of the BYNDS translated into the Serbian language were used. However, the final solution included only 35 items because four items (TR3, TR11, TR12, FI10, and MS9) had a factor loading below 0.4, and four items (TR7, TR8, FI3, and EX7) had a high loading (>0.4) on two factors. The Kaiser–Meyer–Olkin measure of sampling adequacy was acceptable at 0.893, and Bartlett's test of sphericity was significant at p < 0.001. The EFA of the remaining 36 items revealed a structure of five factors, explaining 55.93 % of the variance in risky young driving behavior (the results of the EFA can be found in Appendix A Table A3).

3.2. Scale statistics

The items within each factor were summed and comprised four subscales of ''attitudes toward traffic," five subscales of ''Serbian BYNDS," four subscales of ''self-assessed driving ability," and one scale of ''driving risk perception" (the range [min–max], means, standard deviations, skewness, kurtosis, and Cronbach's alpha for all subscales can be found in Appendix A Table A4). The skewness and kurtosis values indicated that the distributions of the subscales did not deviate substantially from normality (skewness < 2; kurtosis < 2 in all cases). All subscales had good internal consistency coefficients, with Cronbach's alpha ranging from 0.73 to 0.90.

3.3. Results of analysis of covariance (ANCOVA)

ANCOVA was conducted to test whether the mean differences in the dependent variables (attitudes toward traffic, Serbian BYNDS, self-assessed driving ability, and risk perception) between groups (pre-GDL versus GDL) would be significant after removing the effects of covariates (sex and mileage). For this purpose, 14 ANCOVAs were performed. In each ANCOVA, driver licensing systems (pre-GDL vs GDL) were the independent variables, and the sex and mileage variables were treated as covariates. Table 3 shows that after adjusting for sex and mileage, there were significant differences between young drivers licensed pre-GDL and those licensed with GDL with regard to attitude toward violation of traffic regulations, attitude toward speed, risky driving exposure, safety orientation, and driving risk perception. Drivers licensed with GDL reported safer attitudes toward traffic rule violations and speed and higher levels of safety orientation, which refers to a driver's perception of his or her ability to identify risks and dangers and the driver's perception of his or her ability to drive with satisfactory safety margins. They also reported higher levels of risk perception and less exposure to risky situations (i.e., risky driving exposure).

3.4. Results of the regression analyses

The distribution of crashes did not follow a normal distribution. Thus, Poisson or negative binomial regression analyses were performed. In this analysis, the dependent variable was self-reported traffic crashes, and the independent variables were mileage, the GDL program, and their interactions (GDL mileage). We used goodness-of-fit statistics to test the appropriateness of the regression models based on Poisson distribution. These statistics indicated a misfit of the Poisson distribution for self-reported yearly accident involvement, v² (638) = 1187.21, p < 0.001, therefore, models based on negative binomial distribution were constructed. As shown in Table 4, mileage (Z = 1.07, p = 0.283), the GDL program (Z = 0.33, p = 0.740), and GDL mileage (Z = 1.63, p = 0.103) were not significantly related to the number of traffic crashes.

The stepwise regression analysis was used to explain the variance in the direct road safety outcome measures reported by the police (see Table 1 in Appendix A). The results showed that the change in calendar years explained significant amount of variability in the number of crashes with casualties (R² = 0.293; p = 0.017), the number of fatalities (R2 = 0.703; p = 0.000), and the number of serious injuries (R2 = 0.688; p = 0.000) in crashes involving young drivers (18–26). However, calendar years did not predict a significant amount of variance in the number of slight injuries (R2 = 0.077; p = 0.249). The inclusion of the pre/post GDL variable did not predict a significant level of variance in the road safety outcomes.

4. Discussion

In Serbia, young drivers are more frequently involved in car crashes than any other age group. The aim of this study was to determine the effects of adopting GDL on various important factors directly related to the safety of young drivers. A comparison between young drivers licensed pre-GDL and those licensed with GDL was conducted using various measures, including attitudes, risky behavior, self-assessed driving ability, risk perception, and the number of self-reported crashes and crashes obtained from official records.

Responses for two of the four dimensions measuring attitudes showed a tendency to report attitudes indicative of greater safety among drivers licensed with GDL compared with drivers licensed

Table 3 Differences between young drivers licensed pre-GDL and licensed with a GDL.

	pre-GDL	GDL			F(1,737)	Eta2
	Mean	SE	Mean	SE
Attitudes towards traffic
Attitude towards violation of traffic regulations	18.20	0.34	16.80	0.34	8.49**	0.013
Attitude towards speed	18.22	0.36	16.05	0.36	17.99**	0.027
Attitude towards drinking and driving	8.51	0.22	7.98	0.22	2.91	0.005
Attitude towards joyriding	13.89	0.27	13.29	0.27	2.55	0.004
Serbian BYNDS
Transient rule violations	17.66	0.33	16.99	0.33	2.07	0.003
Fixed rule violations	12.19	0.24	11.66	0.25	2.27	0.004
Misjudgement	14.29	0.27	14.30	0.28	0.01	0.000
Risky driving exposure	28.39	0.39	27.20	0.39	4.55*	0.007
Driver mood and aggressive driving	12.38	0.27	11.89	0.27	1.57	0.002
Self-assessed driving ability
General driving ability	24.93	0.36	25.57	0.36	1.55	0.002
Safety orientation	21.70	0.26	20.84	0.26	5.49*	0.010
The body dimension	17.36	0.23	17.31	0.23	0.02	0.000
Specific task skills	10.36	0.17	10.39	0.17	0.02	0.000
Driving risk perception	34.34	0.35	36.32	0.35	15.86**	0.024

Note: Attitudes towards traffic: lower totals scores express safer attitudes; Serbian BYNDS: lower total scores indicate the safer behaviour in traffic; Self-assessed driving ability: lower total scores indicate critical view of their own driving skills; Driving risk perception: lower total scores indicate high perceived risk. The means are adjusted for sex and mileage. SE = standard error. *p < 0.05; ** p < 0.001.

Table 4 Negative binomial regression analyses on crash involvement during the previous 3 years.

Variables	Incidence rate ratios (IRR)	Std. Err.	Z-value	95 % conf. interval	Pseudo R2
GDL program (1 = pre-GDL, 2 = GDL)	0.793	0.171	1.07	0.519–1.211	0.023
Mileage GDL mileage	0.999 1.000	0.000 0.000	0.33 1.63	0.999–1.001 0.999–1.001

pre-GDL. Drivers licensed with GDL reported more favorable attitudes toward traffic regulations and speed. This result was expected because traffic regulations and speed are commonly represented in education programs for drivers licensed with GDL. These results are consistent with those of other studies that have shown that educational programs can change drivers' attitudes (Floreskul et al., 2016; Mann & Lansdown, 2009). However, there were no significant differences between young drivers licensed pre-GDL and those licensed with GDL in terms of attitudes toward drinking and driving and toward joyriding. These results are not consistent with our hypothesis. There are several potential reasons for these results. The total score on the attitude toward drinking and driving scale in both groups was low, which indicates that young drivers are largely opposed to drinking and driving; thus, there is not much room to upgrade this attitude.

Other studies using the questionnaire on the attitude toward drinking and driving that we used in our study also reported low total scores, that is, in range of our results (Endriulaitiene˙ et al., 2018; Ulleberg & Rundmo, 2002). Moreover, studies in Serbia conducted in the period relevant to our research (2010 and 2017) showed that there have been no significant changes in drinking and driving. For example, in 2010 and 2017, 90.4 % and 89 % of car drivers respectively reported that they had not driven above the legal limit the past month (Antov et al., 2012; RTSA, 2019). Attitude toward joyriding represents a specific attitude, and topics of the training program do not cover this area.

Further, the differences in participants' risk perception were expected. Risk perception is directly related to informing the driver, and it seems that the content of the theoretical part of the training has had an effect, that is, the young driver's better understanding of the risks in traffic. This result is consistent with studies that have shown that training and campaigns can increase the risk perception of traffic among young drivers (Rosenbloom et al., 2008; Rundmo & Iversen, 2004). Interestingly, a statistically significant difference was observed in self-assessed driving ability, in the sense that drivers licensed pre-GDL had higher scores on the safety orientation scale than those licensed with GDL. One possible explanation for this result is that GDL education and training contribute to addressing the problem of overconfidence and may lead young drivers to adopt a more self-critical view of their driving abilities. No difference was observed in transient and fixed violations, which was unexpected, considering the existing differences in risk perception and attitudes toward regulations and speed. Notably, a difference in the total scores of transient and fixed violations was observed, but the difference was not statistically significant. Other studies have provided evidence of small changes in target behavior when attempting to change attitudes (Elvik et al., 1997; OECD, 1994). Studies have shown that applying a combination of different measures is critical for determining whether there are significant effects on behavior (Aarø & Rise, 1996; Delhomme, 1999).

The results show that the application of the GDL is not related to the number of self-reported crashes. In addition, the GDL is not related to the total number of crashes with casualties, fatalities, serious injuries, and slight injuries among young drivers. The data were obtained from official records. It seems that the application of GDL did not reduce the number of traffic crashes and their consequences among young drivers. The new Road Traffic Safety Law in Serbia was implemented in 2010, while the application of GDL was delayed to 2013. Based on data on the number of total crashes and killed and injured young drivers, it can be seen that the decline in the number of killed and injured young drivers started in 2010 (see Appendix A Table A1) under the influence of the new law, and it seems that the application of GDL per se did not have expected effects. These results are unexpected, considering the results of studies that have shown that the application of GDL significantly contributes to the reduction of traffic crashes (e.g., Dee et al., 2005; Males, 2007).

It seems that GDL increased the awareness of young drivers with regard to traffic risks, but not sufficiently to be evident in changing behavior and lessening involvement in traffic crashes. Several studies have reported that the implementation of the new Road Traffic Safety Law in Serbia has had mild effects on traffic safety (Antic´ et al., 2011; Nazif-Munoz & Nikolic, 2018). It seems that strengthening the GDL program in Serbia with additional components is necessary to change drivers' behavior and reduce young drivers' traffic crashes. Strengthening should take into account two directions. First, education and training of novice drivers should be adjusted to the GDL framework. It seems that education and training should include content that would provide risk-prevention and self-evaluation skills related to the strategic and personal levels of driving behavior. Although several studies have shown little or no convincing evidence that driver training reduces crashes or other outcomes (e.g., Lonero & Mayhew, 2010; Thomas et al., 2012), it is important to not abandon but improve driver education. Second, the GDL system in Serbia does not include components such as driving under the supervision of an adult with driving experience after the age of 18 and driving without the presence of peers. In addition, the learner's license-holding period is quite short (three months). Studies have reported that supervised driving has multiple advantages and significantly reduces crash risk in young drivers (ECMT, 2006; Masten et al., 2015; Siskind et al., 2019). Further, passenger restrictions are associated with a substantial reduction in young drivers' fatal crash rates (Hirschberg & Lye, 2020; McCartt et al., 2010; Senserrick & Williams, 2015). In addition, multiple studies have shown that license-holders who spent a longer time in the learner stage had fewer crashes (Ehsani et al. 2013; Senserrick & Williams, 2015).

5. Limitations and future research

This study has some methodological limitations that should be considered. First, because this study is based on self-reported data, it suffers from the usual perceived weaknesses such as social desirability bias. However, because no names were collected, and data collection was undertaken remotely, the impact of social desirability bias is unlikely to have significantly affected the results. Second, drivers' attitudes, risk perception, self-assessed driving ability, and driver behavior could have been influenced by other factors (e.g., traffic safety campaigns and traffic enforcement), not only by education and training. The Road Traffic Safety Law in Serbia (which came into force in 2010) has brought many traffic-related novelties, with the most important of these being strategic actions in traffic safety, a traffic safety financing system, a penalty points system, improvement of road infrastructure safety, and traffic safety campaigns. However, most of these measures have not yet been implemented in practice. For example, there have been no differences between the periods before and after the enactment of the new law in terms of campaign implementation, intensity of traffic enforcement, and strategic actions in traffic safety. Considering that there were no significant changes in our other factors, it can be assumed that driver training was the factor that contributed the most to the differences related to drivers' attitudes, risk perception, self-assessed driving ability, and behavior of young drivers.

The results of the present study show that the education of novice drivers leads to a change in the attitudes and risk perception of young drivers, but there is no change in behavior. Future studies should take different approaches in driver education that would contribute to understanding the importance of appropriate safety attitudes and behavior to avoid accident involvement in traffic.

6. Conclusion

The effects of GDL in Serbia have been limited. GDL has contributed to the improvement of drivers' attitudes and understanding of risk, but it has not contributed to significant changes in the behavior of young drivers and traffic crashes. The results of this study suggest that it is necessary to further improve the education and training of new drivers. The Insurance Institute for Highway Safety developed a rating system that can be applied to various driver education programs. The rating system includes components such as minimum age limit, permit holding periods, required practice hours, nighttime and passenger restrictions, and durations of the restrictions. Laws are rated as good, fair, marginal, or poor (for additional information, see McCartt et al., 2010). Based on its components, the Serbian GDL program may be rated as fair. McCartt et al. (2010) provide evidence that a strong graduated licensing law can serve as an effective countermeasure for reducing fatal crash involvements of teenage drivers aged 15–17 years. Laws rated good were associated with a 30 % and 19 % reduction in the fatal crash rate compared with laws rated poor and fair, respectively. The GDL program in Serbia, in relation to programs rated as good, has the following deficiencies: short learner's holding period (about three months), restriction on night driving in the probationary phase starting from 11:00p.m., and passenger restrictions not being included in the probationary phase. It seems that strengthening the GDL program in Serbia with additional components would be necessary to change drivers' behavior and reduce traffic crashes of young drivers.

Acknowledgement

This work was supported by the Provincial Secretariat for HigherEducation and Scientific Research (Autonomous Province of Vojvodina) through project "Development of a spatially based intelligent traffic safety management system" [grant number 142-451-2690/2021-01/02].

Appendix A

See Tables A1–A4.

Table A1 The total number of crashes with casualties, the number of fatalities, serious and slight injuries in crashes involving young drivers (18–26) and the number of licensed young drivers (18–26), 2002–2020.

Year	Total crashes with casualtiesa (ratesb )	Fatalities (ratesc )	Serious injuries (ratesd )	Slight injuries (ratese )	Number of licensed young drivers	Licensing systems
2002	4369 (102.54)	72 (1.69)	410 (9.62)	1317 (30.91)	426,065	Pre-GDL
2003	4706 (104.24)	64 (1.42)	453 (10.03)	1455 (32.23)	451,476	Pre-GDL
2004	5090 (111.87)	73 (1.60)	472 (10.37)	1648 (36.22)	455,007	Pre-GDL
2005	5042 (107.87)	73 (1.56)	466 (9.97)	1668 (35.69)	467,412	Pre-GDL
2006	5461 (110.68)	84 (1.70)	547 (11.09)	1887 (38.25)	493,394	Pre-GDL
2007	6531 (131.49)	100 (2.01)	595 (11.98)	2479 (49.91)	496,692	Pre-GDL
2008	6452 (129.68)	89 (1.79)	649 (13.04)	2564 (51.54)	497,518	Pre-GDL
2009	5972 (117.77)	81 (1.60)	576 (11.36)	2401 (47.35)	507,095	Pre-GDL
2010	5234 (101.58)	58 (1.13)	454 (8.81)	2042 (39.63)	515,283	Pre-GDL
2011	4825 (94.51)	69 (1.35)	409 (8.01)	1877 (36.77)	510,515	Pre-GDL
2012	4390 (88.16)	60 (1.20)	376 (7.55)	1691 (33.96)	497,977	Pre-GDL
2013	4375 (92.74)	54 (1.14)	306 (6.49)	1711 (36.27)	471,753	GDL
2014	4135 (96.02)	39 (0.91)	298 (6.92)	1529 (35.51)	430,639	GDL
2015	4313 (109.35)	45 (1.14)	289 (7.33)	1569 (39.78)	394,412	GDL
2016	4622 (124.20)	41 (1.10)	277 (7.44)	1774 (47.67)	372,145	GDL
2017	4755 (132.25)	39 (1.08)	299 (8.32)	1804 (50.18)	359,537	GDL
2018	4498 (128.40)	38 (1.08)	264 (7.54)	1657 (47.30)	350,298	GDL
2019	4615 (129.09)	39 (1.09)	252 (7.05)	1757 (49.15)	357,492	GDL
2020	4238 (117.30)	44 (1.22)	280 (7.75)	1685 (46.64)	361,282	GDL

Note:

^a Sum of fatal and injury crashes.
^b Rates of crashes with causalities per 10,000 licensed young drivers.
^c Rates of fatalities per 10,000 licensed young drivers.
^d Rates of serious injuries per 10,000 licensed young drivers.
^e Rates of slight injuries per 10,000 licensed young drivers.

Table A2 Fit indexes from confirmatory factor analysis.

Model	v2 /df	RMSEA (95 % CI)	GFI	CFI	SRMR
Attitudes towards traffic	859.8/283 = 3.0	0.06 (0.05 to 0.06)	0.90	0.91	0.05
Self-assessed driving ability	631.3/194 = 3.3	0.06 (0.05 to 0.06)	0.92	0.94	0.04
Behaviour of Young Novice Drivers Scale	2937.4/892 = 3.3	0.09 (0.08 to 0.09)	0.68	0.74	0.09
Driving risk perception (one factor)	102.3/24 = 4.2	0.07 (0.06 to 0.07)	0.97	0.96	0.05

Note: A good fit of model should, in general, have 2:1 or 5:1 v² /df, GFI > 0.90, CFI > 0.90 (preferably > 0.95), RMSEA < 0.08 or 0.10 (preferably < 0.06), and SRMR < 0.08 (preferably < 0.05) indices.

Table A3 Serbian version of the Behaviour of Young Novice Drivers Scale.

	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5
Risky driving exposure
EX2. You drove in the rain	,868
EX4. You drove at night	,867
EX3. You drove at peak times in the morning	,851
EX5. You drove at dusk or dawn	,812
EX1. You drove on the weekend	,770
EX6. You carried your friends as passengers at night	,627
EX8. Your car was full of your friends as passengers	,521
EX9. You went for a drive with your mates giving you directions to where they wanted to go	,458
Misjudgement

MS3. You misjudged the gap when you were turning left		,882
MS6. You misjudged the gap when you were overtaking another vehicle		,880
MS2. You misjudged the speed of an oncoming vehicle		,756
MS4. You misjudged the stopping distance you needed		,707
MS1. You misjudged the speed when you were exiting a main road		,686
MS7. You missed your exit or turn		,471
MS5. You turned left into the path of another vehicle		,461
MS8. You entered the road in front of another vehicle		,400
Transient violations
TR2. You went 10–20 km/h over the speed limit (e.g. 72 km/h in a 60 km/h zone, 112 km/h in a 100 km/h zone)			,925
TR1. You drove over the speed limit in areas where it was unlikely there was a radar or speed camera			,827
TR5. You went up to 10 km/h over the speed limit (e.g. 65 km/h in a 60 km/h zone, 105 km/h in a 100 km/h zone)			,824
TR6. You drove more than 20 km/h over the speed limit (e.g. 60 km/h in a 40 km/h zone, 120 km/h in a 100 km/h zone)			,773
TR9. You sped up when the lights went yellow			,678
TR10. You didn't always indicate when you were changing lanes			,544
TR4. You sped at night on roads that were not well lit			,444
Driver mood and risky driving
FI5. You drove without a valid licence as because you had not applied for one yet or it had been suspended				,810
FI7. If there was no red light camera, you drove through intersections on a red light				,703
DM3. You drove faster if you were in a bad mood				,692
FI2. You drove after taking an illicit drug such as marijuana or ecstasy				,678
DM2. You allowed your driving style to be influenced by your mood				,648
DM1. Your driving was affected by negative emotions such as anger or frustration				,585
FI9. You drove when you thought you may have been over the legal alcohol limit				,508
Fixed violations
FI6. You did not wear a seatbelt if it was only for a short trip					,803
FI4. You did not always wear your seatbelt					,746
FI1. Your passengers did not wear seatbelts					,628
TR13. You spoke on a mobile that you held in your hands					,487
FI8. You carried more passengers than there were seatbelts for in your car					,413

Eigenvalues	9.95	4.57	2.06	1.54	1.46
Variance (%)	28.43	13.07	5.87	4.40	4.16

Extraction method: principal components, rotation method: promax with Kaiser Normalisation.

Table A4 Range, means, standard deviations, skewness, kurtosis, and Cronbach's alpha for all subscales for total sample.

Scale	Min-Max	M	SD	Skewness	Kurtosis	Cronbach's alpha
Attitudes towards traffic
Attitude towards violation of traffic regulations	8–40	17.50	6.17	0.31	0.32	0.79
Attitude towards speed	7–35	17.14	6.58	0.28	0.61	0.85
Attitude towards drinking and driving	5–23	8.24	3.92	1.51	1.97	0.80
Attitude towards joyriding	6–30	13.59	4.93	0.48	0.16	0.73
Serbian BYNDS
Transient rule violations	7–35	17.33	6.13	0.26	0.64	0.88
Fixed rule violations	5–25	11.93	4.52	0.41	0.41	0.79
Misjudgement	8–36	14.29	4.91	1.11	1.60	0.86
Risky driving exposure	8–40	27.80	7.22	0.49	0.16	0.88
Driver mood and risky driving	7–33	12.14	4.99	1.30	1.59	0.83
Self-assessed driving ability
General driving ability	8–40	25.25	6.71	0.17	0.15	0.89
Safety orientation	6–30	21.27	4.65	0.76	0.81	0.80
Body dimension	5–25	17.33	4.30	0.37	0.09	0.85
Specific task skills	3–15	10.37	3.07	0.41	0.39	0.82
Driving risk perception	11–50	35.32	6.40	0.17	0.20	0.84

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Predrag Stanojevic´, Ph.D. is a Professor at The Academy of Applied Studies of Kosovo and Metohija, Serbia. His research interests are in Traffic Safety Psychology and Behaviour. He has participated in more than 15 research projects and studies, as well as in more than 10 scientific committees in Serbia and abroad and he has published more than 50 scientific papers. Author and coauthor of number of scholarly or professional papers published in many national and international Journals and Proceedings of International and National Conferences. His recent publications have appeared in Accident Analysis and Prevention and Transportation Research Part F-Traffic Psychology and Behaviour.

Timo Lajunen, Ph.D. is a Full Professor at Norwegian University of Science and Technology, Department of Psychology, Norway. His main field of research is Traffic Safety Psychology and Behaviour. He has participated in more than 30 research projects and studies, as well as in more than 15 scientific committees in Turkey and abroad and he has published more than 100 scientific papers. His recent publications have appeared in Accident Analysis and Prevention and Transportation Research Part F-Traffic Psychology and Behaviour.

Dragana Jakšic´, Ph.D. is Teaching Assistant at at The Academy of Applied Studies of Kosovo and Metohija, Serbia. Her research interests are in Traffic Safety Psychology and Behaviour. She has participated in more than 10 research projects and studies in Serbia. He is the author and coauthor of a number of publications in journals and conference proceedings. Her recent publication has appeared in Traffic Injury Prevention.

Dragan Jovanovic´, Ph.D. is a Full Professor and Head of Department at University of Novi Sad, Faculty of Technical Sciences, Department of Transport Engineering, Novi Sad, Serbia. His main field of research is Road Safety. He has participated in more than 20 research projects and studies, as well as in more than 15 scientific committees in Serbia and abroad and he has published more than 80 scientific papers. His recent publications have appeared in Accident Analysis and Prevention, Safety Sciences, Transportation Research Part F-Traffic Psychology and Behaviour.

Bosko Matovic´, Ph.D. is an Assistant Professor at University of Montenegro, Faculty of Mechanical Engineering, Podgorica, Montenegro. His research interests are in Traffic Safety Psychology and Behaviour. He has participated in more than 10 research projects and studies in Serbia and Montenegro. He is the author and coauthor of a number of publications in journals and conference proceedings. His recent publications has appeared in Accident Analysis and Prevention and Traffic Injury Prevention.

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