Mobility management to prevent, reduce, or delay driving a car in teenagers

Rates of injury and death caused by car crashes with teenage drivers remain high in most high-income countries. In addition to injury and death, car use includes other non-traffic risks; these may be health-related, such as physical inactivity or respiratory disease caused by air pollution, or have global significance, such as the environmental impact of car use. Research demonstrates that reducing the amount of time driving reduces the risk of injury, and it is expected that it would also reduce other risks that are unrelated to traffic. Mobility management interventions aim to increase mobility awareness and encourage a shift from private car use to active (walking, cycling, skateboarding), and public (bus, tram, train), transportation. 'Soft' mobility management interventions include the application of strategies and policies to reduce travel demand and may be instigated locally or more widely, to target a specific or a non-specific population group; 'hard' mobility management interventions include changes to the built environment or transport infrastructure and are not the focus of this review. Between the ages of 15 to 19 years, young people enter a development stage known as the 'transition teens' in which they are likely to make long-lasting lifestyle changes. It is possible that using this specific time point to introduce mobility management interventions may influence a person's long-term mobility behaviour.

To assess whether 'soft' mobility management interventions prevent, reduce, or delay car driving in teenagers aged 15 to 19 years, and to assess whether these mobility management interventions also reduce crashes caused by teenage drivers.

We searched the Cochrane Injuries Group Specialised Register, CENTRAL, MEDLINE, Embase, Web of Science, and Social Policy and Practice on 16 August 2019. We searched clinical trials registers, relevant conference proceedings, and online media sources of transport organisations, and conducted backward- and forward-citation searching of relevant articles.

We included randomised controlled trials (RCTs) or controlled before-after studies (CBAs) evaluating mobility management interventions in teenagers aged 15 to 19 years. We included informational, educational, or behavioural interventions that aimed to prevent, reduce, or delay car driving in this age group, and we compared these interventions with no intervention or with standard practice. We excluded studies that evaluated graduated drivers licensing (GDL) programmes, separate components of GDL, or interventions that act in conjunction with, or as an extension of, GDL. Such programmes aim to increase driving experience and skills through stages of supervised and unsupervised exposure, but assume that all participants will drive; they do not attempt to encourage people to drive less in the long term or promote alternatives to driving. We also excluded studies which evaluated school-based safe-driving initiatives.

Two review authors independently assessed studies for inclusion, extracted data, and assessed risks of bias. We assessed the certainty of evidence with GRADE.

We included one RCT with 178 participants and one CBA with 860 participants. The RCT allocated university students, with a mean age of 18 years, who had not yet acquired a driving licence, to one of four interventions that provided educational information about negative aspects of car use, or to a fifth group in which no information was given. Types of educational information about car use related to cost, risk, or stress, or all three types of educational information combined. In the CBA, 860 school students, aged 17 to 18 years taking a driving theory course, had an additional interactive lesson about active transport (walking or cycling), and some were invited to join a relevant Facebook group with posts targeting awareness and habit. We did not conduct meta-analyses because we had insufficient studies. We could not be certain whether educational interventions versus no information affected people's decision to obtain a driving licence 18 months after receiving the intervention (risk ratio 0.62, 95% confidence interval 0.45 to 0.85; very low-certainty evidence). We noted that fewer participants who were given information obtained a driving licence (42.6%) compared to those who did not receive information (69%), but we had very little confidence in the effect estimate; the study had high or unclear risks of bias and the evidence was from one small study and was therefore imprecise. We could not be certain whether interventions about active transport, given during a driving theory course, could influence behavioural predictors of car use. Study authors noted: - an increased intention to use active transport after obtaining a driving licence between postintervention and an eight-week follow-up in students who were given an active transport lesson and a Facebook invitation compared to those given only the active transport lesson; and - a decrease in intention between pre- and postintervention in those given an active transport lesson and Facebook invitation compared to those given the active transport lesson only. There were high risks of bias in this CBA study design, a large amount of missing data (very few participants accepted the Facebook invitation), and data came from a single study only, so we judged the evidence to be of very low certainty. These studies did not measure our primary outcome (driving frequency), or other secondary outcomes (driving distance, driving hours, use of alternative modes of transport, or car crashes).

We found only two small studies, and could not determine whether mobility management interventions were effective to prevent, reduce, or delay car driving in teenagers. The lack of evidence in this review raises two points. First, more foundational research is needed to discover how and why young people make decisions surrounding their personal transport, in order to find out what might encourage them to delay licensing and driving. Second, we need longitudinal studies with a robust study design - such as RCTs - and with large sample sizes that incorporate different socioeconomic groups in order to evaluate the feasibility and effectiveness of relevant interventions. Ideally, evaluations will include an assessment of how attitudes and beliefs evolve in teenagers during these transition years, and the potential effect of these on the design of a mobility management intervention for this age group.