The use of meta-analysis or research synthesis to combine driving simulation or naturalistic study results on driver distraction

•Depending on the severity and frequency, distractions impact the safety of drivers, passengers and vulnerable road users.•Research synthesis and meta-analysis provide comprehensive estimates of the impact of distractions on driving performance.•Based on our synthesis and review of texting and driving, additional countermeasures such as legislation, enforcement, blocking technologies, social media, education and social norms will be required to reduce future injuries and fatalities.•Passengers may protect or distract drivers and a more complete understanding of the negative and positive effects is needed.•A number of gaps in research and methodological quality are noted that will improve future research on driver distraction.

Three important and inter-related topics are addressed in this paper. First, the importance of meta-analysis and research synthesis methods to combine studies on traffic safety, in general, and on driver distraction, in particular, is briefly reviewed. Second, naturalistic, epidemiologic, and driving simulation studies on driver distraction are used to illustrate convergent and divergent results that have accumulated thus far in this domain of research. In particular, mobile phone conversation, passenger presence, and text messaging naturalistic studies use meta-analyses and research syntheses to illustrate important patterns of results that are in need of more in-depth study. Third, a number of driver distraction study limitations such as poorly defined dependent variables, lack of methodological detail, and omission of statistical information prevent the integration of many studies into meta-analyses. In addition, the overall quality of road safety studies suffers from these same limitations and suggestions for improvement are made to guide researchers and reviewers. Practical Applications. The use of research synthesis and meta-analysis provide comprehensive estimates of the impact of distractions on driving performance, which can be used to guide public policy and future research.