Literature DB >> 32799320

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

Aimee Ward1,2, Sharon R Lewis3, Harold Weiss1.   

Abstract

BACKGROUND: 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.
OBJECTIVES: 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. SEARCH
METHODS: 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. SELECTION CRITERIA: 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. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed studies for inclusion, extracted data, and assessed risks of bias. We assessed the certainty of evidence with GRADE. MAIN
RESULTS: 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). AUTHORS'
CONCLUSIONS: 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.
Copyright © 2020 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.

Entities:  

Mesh:

Year:  2020        PMID: 32799320      PMCID: PMC8094927          DOI: 10.1002/14651858.CD009438.pub2

Source DB:  PubMed          Journal:  Cochrane Database Syst Rev        ISSN: 1361-6137


  40 in total

1.  Changes in alcohol involvement, cognitions and drinking and driving behavior for youth after they obtain a driver's license.

Authors:  Denis M McCarthy; Sandra A Brown
Journal:  J Stud Alcohol       Date:  2004-05

Review 2.  Graduated driver licensing for reducing motor vehicle crashes among young drivers.

Authors:  L Hartling; N Wiebe; K Russell; J Petruk; C Spinola; T P Klassen
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3.  Assessing the residual teen crash risk factors after graduated drivers license implementation.

Authors:  Craig P Thor; Hampton C Gabler
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4.  Traffic safety in the U.S.: re-examining major opportunities.

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Journal:  J Safety Res       Date:  2007-05-30

5.  Toward understanding the recent large reductions in the proportion of young persons with a driver's license: a response to Le Vine et al. (2013).

Authors:  Michael Sivak; Brandon Schoettle
Journal:  Traffic Inj Prev       Date:  2013       Impact factor: 1.491

6.  Trends in driver licensing status and driving among high school seniors in the United States, 1996-2010.

Authors:  Ruth A Shults; Allan F Williams
Journal:  J Safety Res       Date:  2013-05-07

7.  GRADE: an emerging consensus on rating quality of evidence and strength of recommendations.

Authors:  Gordon H Guyatt; Andrew D Oxman; Gunn E Vist; Regina Kunz; Yngve Falck-Ytter; Pablo Alonso-Coello; Holger J Schünemann
Journal:  BMJ       Date:  2008-04-26

8.  Public health benefits of strategies to reduce greenhouse-gas emissions: food and agriculture.

Authors:  Sharon Friel; Alan D Dangour; Tara Garnett; Karen Lock; Zaid Chalabi; Ian Roberts; Ainslie Butler; Colin D Butler; Jeff Waage; Anthony J McMichael; Andy Haines
Journal:  Lancet       Date:  2009-12-12       Impact factor: 79.321

9.  Crash involvement during the different phases of the New Zealand Graduated Driver Licensing System (GDLS).

Authors:  Ben Lewis-Evans
Journal:  J Safety Res       Date:  2010-06-23

10.  Health impacts of free bus travel for young people: evaluation of a natural experiment in London.

Authors:  Phil Edwards; Rebecca Steinbach; Judith Green; Mark Petticrew; Anna Goodman; Alasdair Jones; Helen Roberts; Charlotte Kelly; John Nellthorp; Paul Wilkinson
Journal:  J Epidemiol Community Health       Date:  2013-06-13       Impact factor: 3.710

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  2 in total

1.  Sociodemographic and Built Environment Associates of Travel to School by Car among New Zealand Adolescents: Meta-Analysis.

Authors:  Sandra Mandic; Erika Ikeda; Tom Stewart; Nicholas Garrett; Debbie Hopkins; Jennifer S Mindell; El Shadan Tautolo; Melody Smith
Journal:  Int J Environ Res Public Health       Date:  2020-12-07       Impact factor: 3.390

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

Authors:  Aimee Ward; Sharon R Lewis; Harold Weiss
Journal:  Cochrane Database Syst Rev       Date:  2020-08-16
  2 in total

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