Effective measures for behavioural change

Indeed, human behaviour plays a role in more than 90% of road crashes. An American study [1] analysed over 2 million crashes involving (car) drivers and found that in 94% of the cases the crash could be attributed to the driver. The study examined the last critical event that led to the crash. However, crashes rarely have a single cause, but usually result from a combination of factors [2]. For example, when a person goes off the road in a curve due to a steering error, the steering error is the last action leading to the crash, but road design (e.g., curve radius), absence of warning signs, excessive driving speed, and conditions such as slipperiness, may also have contributed to the occurrence of the crash. 

Human errors and unsafe actions may occur partly due to errors or imperfections in the traffic system. Figure 1 shows how crashes may occur when errors in the traffic system and unsafe actions by road users inconveniently coincide. 

Therefore, the key to crash prevention is not only education and public communication, but a combination of vehicle and infrastructure measures, and education, public communication and enforcement as supporting measures [4]. See the question Which measures may change road user behaviour?.

The following behaviour has been shown to adversely affect road safety [5]:

• Driving under the influence of alcohol, drugs or medication
• Inappropriate speed or exceeding the speed limit
• Fatigue
• Distraction
• Red light negation
• Headway times that are too short
• Inadequate use of lighting (especially by cyclists)
• Failure to use, or misuse means of protection such as helmets or seat belts

For more information on risky road user behaviour, see SWOV fact sheet Risky road user behaviour, aggression and repeat offenders.

No, people make mistakes and these cannot always be avoided, even if people are motivated, well-informed and well-trained [6]. It is important to design the traffic system in such a way that mistakes made by road users (and by road safety professionals) are avoided as far as possible and that the mistakes that are still made do not lead to serious crashes. This is the core of Sustainable Road Safety. More information can be found in SWOV fact sheet Sustainable Road Safety.

Measures to affect road user behaviour are also referred to as the 3Es [4]:

• Engineering: design of vehicle, road network, road and road environment
• Education: driver training, traffic education, public communication and educational measures
• Enforcement

Engineering: design of vehicles, road network, road and road environment

The design of vehicles, the road network, the road and the road environment affect road user behaviour and can help enforce or elicit the right (safe) behaviour. Smart technology can also help. An example of a measure that enforces safe behaviour is physical separation of driving directions that prevents drivers from ending up on the wrong side of the road, for example, due to unsafe overtaking. An example of a measure that elicits safe behaviour is in-vehicle speed assistance that warns drivers if they are speeding. For more information, see SWOV fact sheets Principles for a safe road network, Infrastructure for pedestrians and cyclists and Safe passenger cars.

Education: driver training, traffic education, public communication and educational measures

Traffic education and driver training can be used to teach skills. Public communication can focus on increasing knowledge about, for example, (changed) traffic rules or at bringing about a change in attitude. Publicity campaigns seem especially effective in combination with other measures, in particular police surveillance and enforcement. For more information, see SWOV fact sheets Public communication, Traffic education, Driver training and driving tests; and the following questions in this fact sheet: How effective is traffic education? en How effective is public communication?

In addition, there are educational measures or rehabilitation courses for offenders. In the Netherlands there are rehabilitation courses for alcohol offenders - EMA (Educational Measure Alcohol) and LEMA (Light Educational Measure Alcohol) - and a more general EMBT (Educational Measure Behaviour and Traffic). Since April 2023, there has also been an Educational Measure Drugs (EMD). For more information, see Traffic enforcement – What are rehabilitation courses and how effective are they?

Enforcement

Enforcement aims to enforce rules by means of sanctions and thus to deter violations. The greater the subjective probability of detection, the more effective enforcement is. For more information, see SWOV fact sheet Traffic enforcement and the question How effective is enforcement? in this fact sheet.

Most effective are measures that enforce safe road user behaviour - making unsafe behaviour impossible - and measures that elicit safe road user behaviour - ensuring that road users subconsciously exhibit the correct (safe) behaviour [4] [7]. Thus, road users do not have to (consciously) think in order to exhibit safe behaviour. The measures are mostly vehicle and infrastructure measures. Public communication, education and enforcement are important supporting measures.

Behavioural change is hard to accomplish. Behaviour is often subconscious and consists of automatisms, routines and choices we make out of habit (or convenience) [8]. A medium to large intention to change behaviour leads at best to a small to medium behavioural change [4] [9]. Therefore, behavioural measures that ensure that road users do not have to (consciously) think in order to exhibit safe road user behaviour  are most effective [4] [9]. A credible road design is an example of a measure aimed at subconsciously ´enforcing´ the desired behaviour (for more information, see SWOV fact sheet Principles for a safe road network).

For most education programs, the effect on crash involvement is unknown. Two specific types of traffic education that do positively affect crash involvement are hazard perception training [10] [11] and general resilience training [12] [13].

Not much research has been done on the effects of traffic education, and certainly not much research that is methodologically sound. For most education programmes, the effect on crash involvement is unknown. The research that has been done concerns, for the most part, primary and secondary school programs. That research shows that some traffic education projects can lead to (small) changes in behaviour and increased knowledge [14] [15] [16] [17] [18] [19] [20]. In a few cases, however, traffic education can also have an undesired effect [21] [22].

For more information, see SWOV fact sheets Traffic education and Driver training and driving tests.

Public communication seems particularly effective in combination with other measures, such as stepping up enforcement. There is little evidence that using mass media alone is effective in changing behaviour or improving road safety.

International research [23] [24] [25] [26] does show a positive effect of campaigns on road safety, but in most cases the campaigns were accompanied by other measures, such as stricter enforcement. It cannot be determined how the campaigns specifically contributed to improving road safety. There are studies that do show an effect on behavioural intention; after a publicity campaign, people indicate that they will exhibit different behaviour [27]. But since it is known that there is a major difference between intention and behaviour [9], no firm conclusion about the effectiveness of public communication in terms of crash prevention can be drawn on the basis of behavioural intention alone. For more information, see SWOV fact sheet Public communication.

Enforcement is an effective way to achieve safer road user behaviour and thus reduce injury crashes. How effective enforcement is differs per type of violation. SWOV Fact sheet Traffic enforcement discusses what is known about the effectiveness of each enforcement priority.

The effectiveness of enforcement primarily depends on the probability of detection. The amount of the sanction only has a limited effect. In addition to its preventive effect, police surveillance is also a selection tool to ban dangerous drivers from traffic.

Nudging is the encouragement of desired behaviour using small, smart and often subconscious temptations. An example of nudging is placing Dick Bruna drawings along 30km/h roads to entice drivers - through the association with children - to reduce their speed. Nudging can have an effect on behaviour, but the effects are often small and the sustainability and generalisability of any effects are a matter of concern [28].

For bringing about more lasting behavioural changes, nudging seems insufficient without additional measures. This was also shown in an evaluation study of the Dick Bruna drawings, which found a small effect that disappeared within a few weeks. Within the European project MeBeSafe, various types of nudging were also developed and tried out. The results of these field studies showed mostly positive effects, but longer-term effects were not examined [29].

Systems that use black boxes or smartphone apps to monitor driving behaviour and provide feedback could lead to an improvement in driving behaviour (e.g. [30] [31] [32] [33] [34] [35]. However, three conditions must be met [32] : 1) there must be regular feedback, 2) there must be consequences for unsafe behaviour, and 3) the persons providing feedback must have learned how to do this properly.

An Australian study [34] also found that feedback by itself may not motivate enough to change behaviour, whereas feedback combined with a financial incentive led to a significant improvement in road user behaviour. In addition, other studies found a decrease in longer-term effects (e.g. [36] and [37]. Frequently, drivers also appear unwilling to participate in monitoring and feedback interventions at all, for example due to privacy concerns [38] [39].

Driving style insurance policies in which insurers give discounts on car insurance premiums based on driving style, monitored with a black box or a smartphone app (see the question How effective are monitoring and feedback systems (with black boxes or smartphone apps)?), can positively affect driving behaviour. This is shown, for example, in a study by Bolderdijk [40] in which proper speed behaviour of young novice drivers was rewarded with a discount on their insurance premium. The driving style-dependent premium led to fewer violations of the speed limit, but after the reward was discontinued, behaviour appeared to return to its old level.

An evaluation of ANWB’s Safe Driving car insurance also shows positive results [41]. ANWB has offered the Safe Driving car insurance since 2016; safe driving behaviour is rewarded with an extra premium discount and unsafe driving behaviour leads to a lower discount. Policyholders also gain insight and get advice regarding their driving behaviour. Analysis of driving behaviour shows that the feedback initially improves driving behaviour, but that this effect is temporary. However, the resulting reduction in premium discount does subsequently lead to an improvement in driving behaviour. The number of claims also appears to decrease.

However, it does appear that drivers who drive relatively safely are more likely to take out a driving style insurance policy than drivers who exhibit more risky driving behaviour [42] [43].

Rewarding safe behaviour can have a positive effect on road user behaviour. For example, a discount for safe driving behaviour can lead to safer behaviour. Another example of rewarding safe behaviour is feedback on speed behaviour by smileys; drivers who stick to the speed limit see a smiley face, drivers who exceed the limit see a sad face. Research shows that these types of feedback signs can have a (limited) positive effect on driving speeds at that location [44] [45]. Driving style insurance policies that reward desired driving behaviour with a discount on the insurance premium can also be effective as long as the reward is maintained ([40], see the question How effective is driving style insurance?).

Supporting apps can positively affect road user behaviour, especially when they are combined with feedback and rewards (see the questions How effective are monitoring and feedback systems (with black boxes or smartphone apps)? and How effective is rewarding safe behaviour?) and when they help road users intending to change their behaviour to actually do so.

There are different types of apps that support road users to engage in safe road user behaviour. For example, there are apps that ensure that incoming phone calls and messages are stopped while driving, such as ‘InTraffic Reply’ and ‘Automodus’, and there are apps that monitor driving behaviour and provide feedback, such as the ‘ANWB Veilig Rijden’ app (‘Safe Driving’app). In addition, both types of apps can be combined with driving style insurance (see the question How effective is driving style insurance?) or some other form of reward (see the question How effective are monitoring and feedback systems (with black boxes or smartphone apps)?).

An evaluation of Interpolis' AutoModus app [46] found that eight weeks after installation use of the app led to a small but statistically significant decrease in self-reported smartphone use among young drivers. Interpolis has also developed an app to counter phone use by cyclists, the PhoNo app. An evaluation study [47] found that this app was viewed positively by study participants, but the study did not provide a clear picture of its effect on smartphone use by cyclists. There is some evidence that the PhoNo app has a positive effect on self-reported smartphone use, but the findings are inconsistent and sometimes hard to interpret.

It’s highly questionable whether people will really behave more safely if they become more aware of road (un)safety. In the first place, people have a tendency to 'reason away' problems, for example by thinking that they are better drivers than other road users and therefore the risk is lower for them than for others (cognitive dissonance [48]). In addition, although people may intend to improve their behaviour, in practice it proves difficult to actually do so. Changing habitual behaviour takes a lot of trouble and effort in the short term, while the potentially negative consequences often lie far into the future and the (health) gains of behavioural change are by no means always immediate [49] [50]. Research shows that medium to large intention leads at most to a small to medium actual behavioural change [9]. This is called the Intention-behaviour-gap [51]. Behavioural measures that ensure that road users do not have to (consciously) think to behave safely are therefore most effective (see also the question What measures are most effective in changing behaviour).

Social norms play an important role in road user behaviour and can either have a positive or negative effect. On the one hand, social norms can cause people to avoid engaging in undesirable behaviour, such as drunk driving, because they believe it is socially undesirable. On the other hand, social norms can make people copy others in exhibiting undesirable behaviours. For example, drivers appear to be guided in their choice of speed by other road users more than by speed limits [52].

Social norms refer to the expectations people have about other people’s assessment of behaviour [53]; is behaviour ‘normal’ and ‘desirable’. People have a strong need to belong somewhere and therefore tend to copy other people’s behaviour [54].

Social norms can play a role in behavioural change. To achieve this change, it is important to emphasise desired behaviour and to emphasise that this desired behaviour is exhibited by the majority of the group to which the target group belongs or wants to belong. Important in this approach is that the exemplary behaviour is indeed prevalent (do not say something is prevalent if it is not [55]). It is also important that the desired behaviour is propagated by a person or group that the target group sees as relevant [55].

A company’s safety culture indicates how (road) safety is viewed in a company (from top to bottom). It is reflected in visible features (such as posters about safety), rules and regulations, and in clear norms and values. Most studies show that by improving the road safety culture, drivers behave more safely [56]. There is evidence that effective measures include having group discussions, training higher-order skills such as hazard perception, risk awareness and acceptance, and rewarding safe driving behaviour [56].

MONO-zakelijk (monozakelijk.nl) supports employers in creating awareness about travelling; should you actually travel? If you travel, at what time? And how do you drive safely? Road safety is thus anchored in an employer’s culture and piggybacks on other themes, such as climate change and being a good employer.

Below you will find the list of references that are used in this fact sheet; all sources can be consulted or retrieved. Via Publications you can find more literature on the subject of road safety.

[1]. Singh, S. (2018). Critical reasons for crashes investigated in the National Motor Vehicle Crash Causation Survey. Traffic Safety Facts Crash • Stats. Report No. DOT HS 812 506. National Highway Traffic Safety Administration, Washington DC.

[2]. Aarts, L.T. & Dijkstra, A. (2018). DV3 - Achtergronden en uitwerking van de verkeersveiligheidsvisie. De visie Duurzaam Veilig Wegverkeer voor de periode 2018 – 2030 onderbouwd [Sustainable Safety version 3 – Backgrounds and elaboration of the updated road safety vision. Substantiation of the second advanced Sustainable Safety vision for the period 2018-2030]. R-2018-6B [Summary in English]. SWOV, Den Haag.

[3]. Reason, J., Manstead, A., Stradling, S., Baxter, J., et al. (1990). Errors and violations on the road: a real distinction? In: Ergonomics, vol. 33, nr. 10/11, p. 1315-1332.

[4]. SWOV & CROW (2021). Handreiking gedragsverandering in het verkeer. KN SPV 2021-4. Kennisnetwerk SPV, Utrecht.

[5]. Weijermars, W., Stipdonk, H., Aarts, L., Bos, N., et al. (2014). Verkeersveiligheidsbalans 2000-2012. Oorzaken en gevolgen van verkeersonveiligheid [Road safety assessment 2000-2012. Causes and consequences of road unsafety]. R-2014-24 [Summary in English]. SWOV, Den Haag.

[6]. Weijermars, W.A.M. & Schagen, I.N.L.G. van (2009). Tien jaar Duurzaam Veilig. Verkeersveiligheidsbalans 1998-2007 [Ten years of Sustainable Safety. Road safety assessment 1998-2007]. R-2009-14 [Summary in English]. SWOV, Leidschendam.

[7]. Shinar, D. (2019). Crash causes, countermeasures, and safety policy implications. In: Accident Analysis & Prevention, vol. 125, p. 224-234.

[8]. Knaap, P. van der (2021). Verkeer is ‘gedrag’, maar verkeersveiligheid is méér dan ‘gedrag’. De effecten van voorlichting en educatie worden makkelijk overschat zolang goede evaluatie uitblijft. In: Verkeerskunde, vol. 72, nr. 2, p. 18-19.

[9]. Webb, T.L. & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. In: Psychological Bulletin, vol. 132, nr. 2, p. 249-268.

[10]. Thomas, F.D., Rilea, S., Blomberg, R.D., Peck, R.C., et al. (2016). Evaluation of the safety benefits of the risk awareness and perception training program for novice teen drivers. DOT HS 812 235. National Highway Traffic Safety Administration NHTSA, Washington, D.C.

[11]. Fisher, D.L., Agrawal, R., Divekar, G., Hamid, M.A., et al. (2024). Novice driver crashes: The relation between putative causal factors, countermeasures, real world implementations, and policy – A case study in simple, scalable solutions. In: Accident Analysis & Prevention, vol. 198, p. 107397.

[12]. Senserrick, T., Ivers, R., Boufous, S., Chen, H.-Y., et al. (2009). Young driver education programs that build resilience have potential to reduce road crashes. In: Pediatrics, vol. 124, nr. 5, p. 1287-1292.

[13]. Senserrick, T., Möller, H., Rogers, K., Cullen, P., et al. (2021). Youth resilience education and 13-year motor vehicle crash risk. In: Pediatrics, vol. 148, nr. 6.

[14]. Duperrex, O., Bunn, F. & Roberts, I. (2002). Safety education of pedestrians for injury prevention: a systematic review of randomised controlled trials. In: British Medical Journal, vol. 324, nr. 7346, p. 1129-1131.

[15]. Twisk, D.A.M., Vlakveld, W.P. & Commandeur, J.J.F. (2007). Wanneer is verkeerseducatie effectief? Systematische evaluatie van educatieprojecten [When is education effective? Systematic evaluation of education projects]. R-2006-28 [Summary in English]. SWOV, Leidschendam.

[16]. Twisk, D.A.M., Vlakveld, W.P., Commandeur, J.J.F., Shope, J.T., et al. (2014). Five road safety education programmes for young adolescent pedestrians and cyclists: A multi-programme evaluation in a field setting. In: Accident Analysis & Prevention, vol. 66, p. 55-61.

[17]. Bishop, D.T., Dkaidek, T.S., Atanasova, G. & Broadbent, D.P. (2022). Improving children’s on-road cycling with immersive video-based training: A pilot study. In: Transportation Research Interdisciplinary Perspectives, vol. 16, p. 100699.

[18]. Box, E. & Dorn, L. (2023). A cluster randomised controlled trial (cRCT) evaluation of a pre-driver education intervention using the Theory of Planned Behaviour. In: Transportation Research Part F: Traffic Psychology and Behaviour, vol. 94, p. 379-397.

[19]. Kovácsová, N., Vlakveld, W.P., de Winter, J.C.F. & Hagenzieker, M.P. (2020). PC-based hazard anticipation training for experienced cyclists: Design and evaluation. In: Safety Science, vol. 123, p. 104561.

[20]. Kint, S.T. van der, Schermers, G., Gebhard, S.E. & Hermens, F. (2022). Veilige Snelheden, Geloofwaardige Snelheidslimieten (VSGS). Hoe valide is de GS-bepaling met de VSGS-methode? [Safe Speeds, Credible Speed Limits: How valid is the credible speed limit methodology?] R-2022-5 [Summary in English]. SWOV, Den Haag.

[21]. Gregersen, N.P. & Nolén, S. (1994). Children's road safety and the strategy of voluntary traffic safety clubs. In: Accident Analysis & Prevention, vol. 26, nr. 4, p. 463-470.

[22]. Feenstra, H., Ruiter, R.A.C. & Kok, G. (2014). Evaluating traffic informers: Testing the behavioral and social-cognitive effects of an adolescent bicycle safety education program. In: Accident Analysis & Prevention, vol. 73, p. 288-295.

[23]. Delhomme, P., Dobbeleer, W. de, Forward, S., Simões, A., et al. (2009). Manual for designing, implementing, and evaluating road safety communication campaigns. Campaigns and Awareness Raising Strategies in Traffic Safety (CAST), Brussels.

[24]. Phillips, R.O., Ulleberg, P. & Vaa, T. (2011). Meta-analysis of the effect of road safety campaigns on accidents. In: Accident Analysis & Prevention, vol. 43, nr. 3, p. 1204-1218.

[25]. Fisa, R., Musukuma, M., Sampa, M., Musonda, P., et al. (2022). Effects of interventions for preventing road traffic crashes: an overview of systematic reviews. In: BMC Public Health, vol. 22, nr. 1, p. 513.

[26]. Faus, M., Alonso, F., Fernández, C. & Useche, S.A. (2021). Are traffic announcements really effective? A systematic review of evaluations of crash-prevention communication campaigns. In: Safety, vol. 7, nr. 4, p. 66.

[27]. Kremers, S. & Munnik, Z. (2022). Campagne-effectonderzoek MONO automobilisten en fietsers DVJ Insights. In opdracht van het Ministerie van Infrastructuur en Waterstaat, Utrecht.

[28]. Groot-Mesken, J. de & Vlakveld, W.P. (2014). Een duwtje in de goede richting - verkeersveilig gedrag : hoe kan verkeersveiligheidsbeleid profiteren van inzichten rondom automatische gedragsbeïnvloeding? [A nudge in the right direction: safe traffic behaviour. How can road safety policy benefit from knowledge about automatic behaviour change?] R-2014-13 [Summary in English]. SWOV, Den Haag.

[29]. Ljung Aust, M., Baldanzini, N., Bakker, B., Berghaus, M., et al. (2020). Final Measures. Deliverable D5.5 of the H2020 project MeBeSafe. European Commission, Brussels.

[30]. Bell, J.L., Taylor, M.A., Chen, G.X., Kirk, R.D., et al. (2017). Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior. In: Journal of Safety Research, vol. 60, p. 125-136.

[31]. Dijksterhuis, C., Lewis-Evans, B., Jelijs, B., Waard, D. de, et al. (2015). The impact of immediate or delayed feedback on driving behaviour in a simulated Pay-As-You-Drive system. In: Accident Analysis and Prevention, vol. 75, p. 93-104.

[32]. Farah, H., Musicant, O., Shimshoni, Y., Toledo, T., et al. (2014). Can providing feedback on driving behavior and training on parental vigilant care affect male teen drivers and their parents? In: Accident Analysis & Prevention, vol. 69, p. 62-70.

[33]. Peer, S., Muermann, A. & Sallinger, K. (2020). App-based feedback on safety to novice drivers: Learning and monetary incentives. In: Transportation Research Part F: Traffic Psychology and Behaviour, vol. 71, p. 198-219.

[34]. Stevenson, M., Harris, A., Wijnands, J.S. & Mortimer, D. (2021). The effect of telematic based feedback and financial incentives on driving behaviour: A randomised trial. In: Accident Analysis & Prevention, vol. 159, p. 106278.

[35]. Vlakveld, W. (2018). Notitie Monitor- en Feedbacksystemen. Literatuurstudie naar de effecten van monitor- en feedbacksystemen op het rijgedrag. R-2018-26. SWOV, Den Haag.

[36]. Toledo, T. & Lotan, T. (2006). In-Vehicle Data Recorder for Evaluation of Driving Behavior and Safety. In: Transportation Research Record, vol. 1953, nr. 1, p. 112-119.

[37]. Farmer, C.M., Kirley, B.B. & McCartt, A.T. (2010). Effects of in-vehicle monitoring on the driving behavior of teenagers. In: Journal of Safety Research, vol. 41, nr. 1, p. 39-45.

[38]. McNally, B. & Bradley, G.L. (2018). Predicting young, novice drivers’ intentions to install in-vehicle data recorders. In: Transportation Research Part F: Traffic Psychology and Behaviour, vol. 59, p. 401-417.

[39]. Al-Hussein, W.A., Kiah, M.L.M., Por, L.Y. & Zaidan, B.B. (2021). A systematic review on sensor-based driver behaviour studies: coherent taxonomy, motivations, challenges, recommendations, substantial analysis and future directions. In: PeerJ Computer Science, vol. 7.

[40]. Bolderdijk, J.W., Knockaert, J., Steg, E.M. & Verhoef, E.T. (2011). Effects of Pay-As-You-Drive vehicle insurance on young drivers’ speed choice: Results of a Dutch field experiment. In: Accident Analysis & Prevention, vol. 43, nr. 3, p. 1181-1186.

[41]. ANWB (2019). ANWB Veilig Rijden rapport 2019. ANWB, Den Haag.

[42]. Elvik, R. (2014). Rewarding safe and environmentally sustainable driving: systematic review of trials. In: Transportation Research Record, vol. 2465, nr. 1, p. 1-7.

[43]. Pugnetti, C. & Elmer, S. (2020). Self-assessment of driving style and the willingness to share personal information. In: Journal of Risk and Financial Management, vol. 13, nr. 3, p. 53.

[44]. Malin, F. & Luoma, J. (2020). Effects of speed display signs on driving speed at pedestrian crossings on collector streets. In: Transportation Research Part F: Traffic Psychology and Behaviour, vol. 74, p. 433-438.

[45]. Karimpour, A., Kluger, R., Liu, C. & Wu, Y.-J. (2021). Effects of speed feedback signs and law enforcement on driver speed. In: Transportation Research Part F: Traffic Psychology and Behaviour, vol. 77, p. 55-72.

[46]. Groot-Mesken, J. de, Wijnen, W., Stelling-Konczak, A. & Commandeur, J.J.F. (2016). Interpolis SlimOpWeg-programma: de AutoModus-app. Vragenlijstonderzoek naar het effect van een app om smartphonegebruik in de auto te verminderen [Interpolis SlimOpWeg programme: the AutoModus app. Survey into the effect of an app on reducing smartphone use while driving a car]. R-2016-3 [Summary in English]. SWOV, Den Haag.

[47]. Stelling-Kończak, A., Hermens, F. & Kint, S.T. van der (2019). Effectiviteit van een app tegen smartphonegebruik op de fiets. Evaluatiestudie van de PhoNo-app. R-2019-27. SWOV, Den Haag.

[48]. Carpenter, C.J. (2019). Cognitive dissonance, ego-involvement, and motivated reasoning. In: Annals of the International Communication Association, vol. 43, nr. 1, p. 1-23.

[49]. Kelly, M.P. & Barker, M. (2016). Why is changing health-related behaviour so difficult? In: Public Health, vol. 136, p. 109-116.

[50]. Urbina, D.A. & Ruiz-Villaverde, A. (2019). A critical review of Homo Economicus from five approaches. In: American Journal of Economics and Sociology, vol. 78, nr. 1, p. 63-93.

[51]. Sheeran, P. & Webb, T.L. (2016). The Intention–Behavior Gap. In: Social and Personality Psychology Compass, vol. 10, nr. 9, p. 503-518.

[52]. Musselwhite, C., Avineri, E., Susilo, Y., Fulche, E., et al. (2010). Understanding public attitudes to road user safety. Road Safety Research Report No. 111. Centre for Transport & Society, University of the West of England, Bristol.

[53]. La Barbera, F. & Ajzen, I. (2020). Control interactions in the Theory of Planned Behavior: Rethinking the role of subjective norm. In: Europe's Journal of Psychology, vol. 16, nr. 3, p. 401-417.

[54]. Dijksterhuis, A. (2003). Automaticiteit en controle. In: Vonk, R. (red.), Cognitieve sociale psychologie. Psychologie van het dagelijks denken en doen. Lemma, Utrecht.

[55]. Hoekstra, A.T.G., Twisk, D.A.M., Stelling, A. & Houtenbos, M. (2013). Gebruik van mobiele apparatuur door fietsende jongeren. Bouwstenen voor effectieve maatregelen [The use of mobile devices by cycling youths. A basis for effective measures]. R-2013-12 [Summary in English]. SWOV, Leidschendam.

[56]. Vlakveld, W., Goldenbeld, C., Knapper, A. & Bax, C.A. (2014). Veiligheidscultuur in het wegtransport. R-2014-12. SWOV, Den Haag.