title: Assessing the reliability and validity of direct observation and traffic camera streams to measure helmet and motorcycle use.
abstract: There is a need to develop motorcycle helmet surveillance approaches that are less labour intensive than direct observation (DO), which is the commonly recommended but never formally validated approach, particularly in developing settings. This study sought to assess public traffic camera feeds as an alternative to DO, in addition to the reliability of DO under field conditions. DO had high inter-rater reliability, κ=0.88 and 0.84, respectively, for cycle type and helmet type, which reinforces its use as a gold standard. However, traffic camera-based data collection was found to be unreliable, with κ=0.46 and 0.53 for cycle type and helmet type. When bicycles, motorcycles and scooters were classified based on traffic camera streams, only 68.4% of classifications concurred with those made via DO. Given the current technology, helmet surveillance via traffic camera streams is infeasible, and there remains a need for innovative traffic safety surveillance approaches in low-income urban settings.
authors.affiliation: Department of International Health, Georgetown University, Washington, DC, USA.
authors.forename: Heather N
authors.initials: HN
authors.lastname: Zaccaro
authors.affiliation: Department of Human Science, Georgetown University, Washington, DC, USA.
authors.forename: Emily C
authors.initials: EC
authors.lastname: Carbone
authors.affiliation: Department of Human Science, Georgetown University, Washington, DC, USA.
authors.forename: Nishita
authors.initials: N
authors.lastname: Dsouza
authors.affiliation: Department of Health Systems Administration, Georgetown University, Washington, DC, USA.
authors.forename: Michelle R
authors.initials: MR
authors.lastname: Xu
authors.affiliation: Department of Human Science, Georgetown University, Washington, DC, USA.
authors.forename: Mary C
authors.initials: MC
authors.lastname: Byrne
authors.affiliation: Department of Health Systems Administration, Georgetown University, Washington, DC, USA.
authors.forename: John D
authors.identifier: http://orcid.org/0000-0002-8769-3393
authors.initials: JD
authors.lastname: Kraemer
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control*; D001642:Bicycling / Q000293:injuries*; D006259:Craniocerebral Trauma / Q000517:prevention & control*; D004219:District of Columbia; D006260:Head Protective Devices / Q000706:statistics & numerical data*; D006801:Humans; D009049:Motorcycles; D010781:Photography / Q000592:standards; D011159:Population Surveillance / Q000379:methods*; D015203:Reproducibility of Results
keywords: direct observation; helmets; motorcycles; traffic camera